AISTATS 2021: Poster schedule (final)


1	Session	Paper IDs	Title

2	Session 1: April 13 at 14:00-16:00 PDT	8	Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and Applications
3	Session 1: April 13 at 14:00-16:00 PDT	681	Maximizing Agreements for Ranking, Clustering and Hierarchical Clustering via MAX-CUT
4	Session 1: April 13 at 14:00-16:00 PDT	218	SONIA: A Symmetric Blockwise Truncated Optimization Algorithm
5	Session 1: April 13 at 14:00-16:00 PDT	246	Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant Updates
6	Session 1: April 13 at 14:00-16:00 PDT	504	Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes
7	Session 1: April 13 at 14:00-16:00 PDT	1076	Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
8	Session 1: April 13 at 14:00-16:00 PDT	1118	Random Coordinate Underdamped Langevin Monte Carlo
9	Session 1: April 13 at 14:00-16:00 PDT	82	Alternating Direction Method of Multipliers for Quantization
10	Session 1: April 13 at 14:00-16:00 PDT	349	Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms
11	Session 1: April 13 at 14:00-16:00 PDT	1134	Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization
12	Session 1: April 13 at 14:00-16:00 PDT	920	Distributionally Robust Optimization for Deep Kernel MultipleInstance Learning
13	Session 1: April 13 at 14:00-16:00 PDT	391	Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model.
14	Session 1: April 13 at 14:00-16:00 PDT	943	Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach
15	Session 1: April 13 at 14:00-16:00 PDT	1257	Detection and Defense of Topological Adversarial Attacks on Graphs
16	Session 1: April 13 at 14:00-16:00 PDT	1342	Principal Subspace Estimation Under Information Diffusion
17	Session 1: April 13 at 14:00-16:00 PDT	1511	Online Robust Control of Nonlinear Systems with Large Uncertainty
18	Session 1: April 13 at 14:00-16:00 PDT	1312	Associative Convolutional Layers
19	Session 1: April 13 at 14:00-16:00 PDT	621	On the Privacy Properties of GAN-generated Samples
20	Session 1: April 13 at 14:00-16:00 PDT	1019	Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
21	Session 1: April 13 at 14:00-16:00 PDT	1332	A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
22	Session 1: April 13 at 14:00-16:00 PDT	1327	Sketch based Memory for Neural Networks
23	Session 1: April 13 at 14:00-16:00 PDT	1427	Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC
24	Session 1: April 13 at 14:00-16:00 PDT	309	Shapley Flow: A Graph-based Approach to Interpreting Model Predictions
25	Session 1: April 13 at 14:00-16:00 PDT	580	Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
26	Session 1: April 13 at 14:00-16:00 PDT	1119	Influence Decompositions For Neural Network Attribution
27	Session 1: April 13 at 14:00-16:00 PDT	1815	Improving Classifier Confidence using Lossy Label-Invariant Transformations
28	Session 1: April 13 at 14:00-16:00 PDT	478	Algorithms for Fairness in Sequential Decision Making
29	Session 1: April 13 at 14:00-16:00 PDT	357	Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning
30	Session 1: April 13 at 14:00-16:00 PDT	525	Differentially Private Online Submodular Maximization
31	Session 1: April 13 at 14:00-16:00 PDT	880	No-Regret Algorithms for Private Gaussian Process Bandit Optimization
32	Session 1: April 13 at 14:00-16:00 PDT	1027	Differentially Private Weighted Sampling
33	Session 1: April 13 at 14:00-16:00 PDT	690	Competing AI: How does competition feedback affect machine learning?
34	Session 1: April 13 at 14:00-16:00 PDT	1115	Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration
35	Session 1: April 13 at 14:00-16:00 PDT	1362	Density of States Estimation for Out of Distribution Detection
36	Session 1: April 13 at 14:00-16:00 PDT	1483	Active Learning under Label Shift
37	Session 1: April 13 at 14:00-16:00 PDT	1782	Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty
38	Session 1: April 13 at 14:00-16:00 PDT	1350	A Hybrid Approximation to the Marginal Likelihood
39	Session 1: April 13 at 14:00-16:00 PDT	62	Regression Discontinuity Design under Self-selection
40	Session 1: April 13 at 14:00-16:00 PDT	816	Counterfactual Representation Learning with Balancing Weights
41	Session 1: April 13 at 14:00-16:00 PDT	977	Differentiable Causal Discovery Under Unmeasured Confounding
42	Session 1: April 13 at 14:00-16:00 PDT	1069	Designing Transportable Experiments
43	Session 1: April 13 at 14:00-16:00 PDT	927	List Learning with Attribute Noise
44	Session 1: April 13 at 14:00-16:00 PDT	562	Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits
45	Session 1: April 13 at 14:00-16:00 PDT	624	Multitask Bandit Learning Through Heterogeneous Feedback Aggregation
46	Session 1: April 13 at 14:00-16:00 PDT	1261	Training a Single Bandit Arm
47	Session 1: April 13 at 14:00-16:00 PDT	344	A constrained risk inequality for general losses
48	Session 1: April 13 at 14:00-16:00 PDT	1116	Sample Elicitation
49	Session 1: April 13 at 14:00-16:00 PDT	497	Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function
50	Session 1: April 13 at 14:00-16:00 PDT	1146	Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions
51	Session 1: April 13 at 14:00-16:00 PDT	1401	Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences
52	Session 1: April 13 at 14:00-16:00 PDT	648	An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling
53	Session 1: April 13 at 14:00-16:00 PDT	876	Active Online Learning with Hidden Shifting Domains
54	Session 1: April 13 at 14:00-16:00 PDT	1060	Non-Stationary Off-Policy Optimization
55	Session 1: April 13 at 14:00-16:00 PDT	1210	An Optimal Reduction of TV-Denoising to Adaptive Online Learning
56	Session 1: April 13 at 14:00-16:00 PDT	823	Learning with Gradient Descent and Weakly Convex Losses
57	Session 1: April 13 at 14:00-16:00 PDT	908	Misspecification in Prediction Problems and Robustness via Improper Learning
58	Session 1: April 13 at 14:00-16:00 PDT	987	The Sample Complexity of Meta Sparse Regression
59	Session 1: April 13 at 14:00-16:00 PDT	1062	Efficient Interpolation of Density Estimators
60	Session 1: April 13 at 14:00-16:00 PDT	1050	Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering
61	Session 1: April 13 at 14:00-16:00 PDT	444	A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix
62	Session 1: April 13 at 14:00-16:00 PDT	1315	Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
63	Session 1: April 13 at 14:00-16:00 PDT	319	Sharp Analysis of a Simple Model for Random Forests
64	Session 1: April 13 at 14:00-16:00 PDT	317	Nonparametric Variable Screening with Optimal Decision Stumps
65	Session 1: April 13 at 14:00-16:00 PDT	799	The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain
66	Session 1: April 13 at 14:00-16:00 PDT	1080	Matérn Gaussian Processes on Graphs
67	Session 1: April 13 at 14:00-16:00 PDT	1131	Fast Adaptation with Linearized Neural Networks
68	Session 1: April 13 at 14:00-16:00 PDT	703	On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow
69	Session 1: April 13 at 14:00-16:00 PDT	1032	Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
70	Session 1: April 13 at 14:00-16:00 PDT	1231	Fast Statistical Leverage Score Approximation in Kernel Ridge Regression
71	Session 1: April 13 at 14:00-16:00 PDT	1239	Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression
72	Session 1: April 13 at 14:00-16:00 PDT	1086	Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
73	Session 1: April 13 at 14:00-16:00 PDT	1321	TenIPS: Inverse Propensity Sampling for Tensor Completion
74	Session 1: April 13 at 14:00-16:00 PDT	1044	Reinforcement Learning for Mean Field Games with Strategic Complementarities
75	Session 1: April 13 at 14:00-16:00 PDT	1844	Does Invariant Risk Minimization Capture Invariance?
76	Session 1: April 13 at 14:00-16:00 PDT	27	Semi-Supervised Learning with Meta-Gradient
77	Session 1: April 13 at 14:00-16:00 PDT	1028	Learning the Truth From Only One Side of the Story
78	Session 1: April 13 at 14:00-16:00 PDT	1157	Animal pose estimation from video data with a hierarchical von Mises-Fisher-Gaussian model
79	Session 1: April 13 at 14:00-16:00 PDT	77	Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series
80	Session 1: April 13 at 14:00-16:00 PDT	1148	Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective
81	Session 1: April 13 at 14:00-16:00 PDT	197	Learning GPLVM with arbitrary kernels using the unscented transformation
82	Session 1: April 13 at 14:00-16:00 PDT	1388	Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
83	Session 1: April 13 at 14:00-16:00 PDT	481	On Learning Continuous Pairwise Markov Random Fields
84	Session 1: April 13 at 14:00-16:00 PDT	1310	Dynamic Cutset Networks
85	Session 1: April 13 at 14:00-16:00 PDT	76	Accelerating Metropolis-Hastings with Lightweight Inference Compilation
86	Session 1: April 13 at 14:00-16:00 PDT	1565	The Base Measure Problem and its Solution
87	Session 1: April 13 at 14:00-16:00 PDT	164	Deep Spectral Ranking
88	Session 1: April 13 at 14:00-16:00 PDT	643	Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
89	Session 1: April 13 at 14:00-16:00 PDT	1025	On the linear convergence of policy gradient methods for finite MDPs
90	Session 1: April 13 at 14:00-16:00 PDT	1139	Provably Eﬃcient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case
91	Session 1: April 13 at 14:00-16:00 PDT	1415	Online Model Selection for Reinforcement Learning with Function Approximation
92	Session 2: April 13 at 18:30-20:30 PDT	476	Consistent k-Median: Simpler, Better and Robust
93	Session 2: April 13 at 18:30-20:30 PDT	252	Generalization Bounds for Stochastic Saddle Point Problems
94	Session 2: April 13 at 18:30-20:30 PDT	1784	Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization
95	Session 2: April 13 at 18:30-20:30 PDT	1490	Tracking Regret Bounds for Online Submodular Optimization
96	Session 2: April 13 at 18:30-20:30 PDT	14	One-Round Communication Efficient Distributed M-Estimation
97	Session 2: April 13 at 18:30-20:30 PDT	654	Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization
98	Session 2: April 13 at 18:30-20:30 PDT	923	vqSGD: Vector Quantized Stochastic Gradient Descent
99	Session 2: April 13 at 18:30-20:30 PDT	506	Maximal Couplings of the Metropolis-Hastings Algorithm
100	Session 2: April 13 at 18:30-20:30 PDT	599	Shadow Manifold Hamiltonian Monte Carlo
101	Session 2: April 13 at 18:30-20:30 PDT	171	On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery Problems
102	Session 2: April 13 at 18:30-20:30 PDT	1003	RankDistil: Knowledge Distillation for Ranking
103	Session 2: April 13 at 18:30-20:30 PDT	1601	Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain
104	Session 2: April 13 at 18:30-20:30 PDT	264	CADA: Communication-Adaptive Distributed Adam
105	Session 2: April 13 at 18:30-20:30 PDT	372	Understanding the wiring evolution in differentiable neural architecture search
106	Session 2: April 13 at 18:30-20:30 PDT	384	Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
107	Session 2: April 13 at 18:30-20:30 PDT	628	Independent Innovation Analysis for Nonlinear Vector Autoregressive Process
108	Session 2: April 13 at 18:30-20:30 PDT	1630	GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
109	Session 2: April 13 at 18:30-20:30 PDT	613	Understanding Gradient Clipping In Incremental Gradient Methods
110	Session 2: April 13 at 18:30-20:30 PDT	1158	Mirror Descent View for Neural Network Quantization
111	Session 2: April 13 at 18:30-20:30 PDT	647	Q-learning with Logarithmic Regret
112	Session 2: April 13 at 18:30-20:30 PDT	158	The spectrum of Fisher Information of Deep Networks achieving Dynamical Isometry
113	Session 2: April 13 at 18:30-20:30 PDT	1112	Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum
114	Session 2: April 13 at 18:30-20:30 PDT	1609	One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks
115	Session 2: April 13 at 18:30-20:30 PDT	962	Optimal query complexity for private sequential learning against eavesdropping
116	Session 2: April 13 at 18:30-20:30 PDT	1218	Differentially Private Monotone Submodular Maximization Under Matroid and Knapsack Constraints
117	Session 2: April 13 at 18:30-20:30 PDT	222	On the Generalization Properties of Adversarial Training
118	Session 2: April 13 at 18:30-20:30 PDT	1078	Linear Models are Robust Optimal Under Strategic Behavior
119	Session 2: April 13 at 18:30-20:30 PDT	416	Mean-Variance Analysis in Bayesian Optimization under Uncertainty
120	Session 2: April 13 at 18:30-20:30 PDT	123	A comparative study on sampling with replacement vs Poisson sampling in optimal subsampling
121	Session 2: April 13 at 18:30-20:30 PDT	1359	Prediction with Finitely many Errors Almost Surely
122	Session 2: April 13 at 18:30-20:30 PDT	1055	Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
123	Session 2: April 13 at 18:30-20:30 PDT	1825	Graph Gamma Process Linear Dynamical Systems
124	Session 2: April 13 at 18:30-20:30 PDT	68	Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint
125	Session 2: April 13 at 18:30-20:30 PDT	398	Regret Minimization for Causal Inference on Large Treatment Space
126	Session 2: April 13 at 18:30-20:30 PDT	400	Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions
127	Session 2: April 13 at 18:30-20:30 PDT	523	Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions
128	Session 2: April 13 at 18:30-20:30 PDT	1026	Minimal enumeration of all possible total effects in a Markov equivalence class
129	Session 2: April 13 at 18:30-20:30 PDT	1151	Causal Inference with Selectively Deconfounded Data
130	Session 2: April 13 at 18:30-20:30 PDT	1269	Causal Modeling with Stochastic Confounders
131	Session 2: April 13 at 18:30-20:30 PDT	168	Tight Regret Bounds for Infinite-armed Linear Contextual Bandits
132	Session 2: April 13 at 18:30-20:30 PDT	267	Bandit algorithms: Letting go of logarithmic regret for statistical robustness
133	Session 2: April 13 at 18:30-20:30 PDT	442	Unifying Clustered and Non-stationary Bandits
134	Session 2: April 13 at 18:30-20:30 PDT	518	Dominate or Delete: Decentralized Competing Bandits in Serial Dictatorship
135	Session 2: April 13 at 18:30-20:30 PDT	571	Tractable contextual bandits beyond realizability
136	Session 2: April 13 at 18:30-20:30 PDT	1226	Federated Multi-armed Bandits with Personalization
137	Session 2: April 13 at 18:30-20:30 PDT	1302	Experimental Design for Regret Minimization in Linear Bandits
138	Session 2: April 13 at 18:30-20:30 PDT	1429	A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits
139	Session 2: April 13 at 18:30-20:30 PDT	891	On the Suboptimality of Negative Momentum for Minimax Optimization
140	Session 2: April 13 at 18:30-20:30 PDT	383	On the High Accuracy Limitation of Adaptive Property Estimation
141	Session 2: April 13 at 18:30-20:30 PDT	612	Identification of Matrix Joint Block Diagonalization
142	Session 2: April 13 at 18:30-20:30 PDT	101	Online Forgetting Process for Linear Regression Models
143	Session 2: April 13 at 18:30-20:30 PDT	893	Corralling Stochastic Bandit Algorithms
144	Session 2: April 13 at 18:30-20:30 PDT	1287	Meta Learning in the Continuous Time Limit
145	Session 2: April 13 at 18:30-20:30 PDT	19	Regularized Policies are Reward Robust
146	Session 2: April 13 at 18:30-20:30 PDT	733	γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator
147	Session 2: April 13 at 18:30-20:30 PDT	1371	Taming heavy-tailed features by shrinkage
148	Session 2: April 13 at 18:30-20:30 PDT	114	On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
149	Session 2: April 13 at 18:30-20:30 PDT	221	Predictive Power of Nearest Neighbors Algorithm under Random Perturbation
150	Session 2: April 13 at 18:30-20:30 PDT	223	Adversarially Robust Estimate and Risk Analysis in Linear Regression
151	Session 2: April 13 at 18:30-20:30 PDT	370	Robustness and scalability under heavy tails, without strong convexity
152	Session 2: April 13 at 18:30-20:30 PDT	378	Learning with risk-averse feedback under potentially heavy tails
153	Session 2: April 13 at 18:30-20:30 PDT	808	Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features
154	Session 2: April 13 at 18:30-20:30 PDT	1319	Contrastive learning of strong-mixing continuous-time stochastic processes
155	Session 2: April 13 at 18:30-20:30 PDT	1436	Good Classifiers are Abundant in the Interpolating Regime
156	Session 2: April 13 at 18:30-20:30 PDT	1777	Learning Shared Subgraphs in Ising Model Pairs
157	Session 2: April 13 at 18:30-20:30 PDT	669	Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation
158	Session 2: April 13 at 18:30-20:30 PDT	1186	DAG-structured Clustering by Nearest-Neighbors
159	Session 2: April 13 at 18:30-20:30 PDT	698	Stability and Risk Bounds of Iterative Hard Thresholding
160	Session 2: April 13 at 18:30-20:30 PDT	1233	Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms
161	Session 2: April 13 at 18:30-20:30 PDT	660	On the Faster Alternating Least-Squares for CCA
162	Session 2: April 13 at 18:30-20:30 PDT	358	Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
163	Session 2: April 13 at 18:30-20:30 PDT	1230	Hierarchical Inducing Point Gaussian Process for Inter-domian Observations
164	Session 2: April 13 at 18:30-20:30 PDT	821	Gradient Descent in RKHS with Importance Labeling
165	Session 2: April 13 at 18:30-20:30 PDT	1691	Entropy Partial Transport with Tree Metrics: Theory and Practice
166	Session 2: April 13 at 18:30-20:30 PDT	1753	Flow-based Alignment Approaches for Probability Measures in Different Spaces
167	Session 2: April 13 at 18:30-20:30 PDT	1301	Tensor Networks for Probabilistic Sequence Modeling
168	Session 2: April 13 at 18:30-20:30 PDT	379	Parametric Programming Approach for More Powerful and General Lasso Selective Inference
169	Session 2: April 13 at 18:30-20:30 PDT	1339	Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees
170	Session 2: April 13 at 18:30-20:30 PDT	312	Sample efficient learning of image-based diagnostic classifiers via probabilistic labels
171	Session 2: April 13 at 18:30-20:30 PDT	1671	Learning Temporal Point Processes with Intermittent Observations
172	Session 2: April 13 at 18:30-20:30 PDT	1043	Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference
173	Session 2: April 13 at 18:30-20:30 PDT	1279	Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances
174	Session 2: April 13 at 18:30-20:30 PDT	1394	Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
175	Session 2: April 13 at 18:30-20:30 PDT	1637	Minimax Estimation of Laplacian Constrained Precision Matrices
176	Session 2: April 13 at 18:30-20:30 PDT	795	PClean: Bayesian Data Cleaning at Scale via Domain-Specific Probabilistic Programming
177	Session 2: April 13 at 18:30-20:30 PDT	688	Non-Volume Preserving Hamiltonian Monte Carlo and No-U-Turn Samplers
178	Session 2: April 13 at 18:30-20:30 PDT	135	Robust Imitation Learning from Noisy Demonstrations
179	Session 2: April 13 at 18:30-20:30 PDT	658	Minimax Model Learning
180	Session 2: April 13 at 18:30-20:30 PDT	1192	Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning
181	Session 2: April 13 at 18:30-20:30 PDT	1396	Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
182	Session 2: April 13 at 18:30-20:30 PDT	1445	No-Regret Reinforcement Learning with Heavy-Tailed Rewards
183	Session 3: April 14 at 6:00am-8:00am PDT	406	Adaptive Sampling for Fast Constrained Maximization of Submodular Functions
184	Session 3: April 14 at 6:00am-8:00am PDT	120	Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation
185	Session 3: April 14 at 6:00am-8:00am PDT	527	Anderson acceleration of coordinate descent
186	Session 3: April 14 at 6:00am-8:00am PDT	716	Improved Complexity Bounds in Wasserstein Barycenter Problem
187	Session 3: April 14 at 6:00am-8:00am PDT	1717	Differentiating the Value Function by using Convex Duality
188	Session 3: April 14 at 6:00am-8:00am PDT	1861	A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
189	Session 3: April 14 at 6:00am-8:00am PDT	208	On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions
190	Session 3: April 14 at 6:00am-8:00am PDT	533	Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence
191	Session 3: April 14 at 6:00am-8:00am PDT	534	SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation
192	Session 3: April 14 at 6:00am-8:00am PDT	1666	Direct-Search Methods for a Class of Non-Convex Min-Max Games
193	Session 3: April 14 at 6:00am-8:00am PDT	1668	Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry
194	Session 3: April 14 at 6:00am-8:00am PDT	1246	SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups
195	Session 3: April 14 at 6:00am-8:00am PDT	1495	Offline detection of change-points in the mean for stationary graph signals.
196	Session 3: April 14 at 6:00am-8:00am PDT	796	Adaptive wavelet pooling for convolutional neural networks
197	Session 3: April 14 at 6:00am-8:00am PDT	161	Fisher Auto-Encoders
198	Session 3: April 14 at 6:00am-8:00am PDT	1598	Learning Bijective Feature Maps for Linear ICA
199	Session 3: April 14 at 6:00am-8:00am PDT	1705	Local Competition and Stochasticity for Adversarial Robustness in Deep Learning
200	Session 3: April 14 at 6:00am-8:00am PDT	284	Logical Team Q-learning: An approach towards factored policies in cooperative MARL
201	Session 3: April 14 at 6:00am-8:00am PDT	355	Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
202	Session 3: April 14 at 6:00am-8:00am PDT	1676	On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity
203	Session 3: April 14 at 6:00am-8:00am PDT	332	Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints
204	Session 3: April 14 at 6:00am-8:00am PDT	731	All of the Fairness for Edge Prediction with Optimal Transport
205	Session 3: April 14 at 6:00am-8:00am PDT	397	Interpretable Random Forests via Rule Extraction
206	Session 3: April 14 at 6:00am-8:00am PDT	726	Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
207	Session 3: April 14 at 6:00am-8:00am PDT	780	CONTRA: Contrarian statistics for controlled variable selection
208	Session 3: April 14 at 6:00am-8:00am PDT	1520	An Analysis of LIME for Text Data
209	Session 3: April 14 at 6:00am-8:00am PDT	244	Foundations of Bayesian Learning from Synthetic Data
210	Session 3: April 14 at 6:00am-8:00am PDT	657	Robust and Private Learning of Halfspaces
211	Session 3: April 14 at 6:00am-8:00am PDT	740	DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation
212	Session 3: April 14 at 6:00am-8:00am PDT	753	Free-rider Attacks on Model Aggregation in Federated Learning
213	Session 3: April 14 at 6:00am-8:00am PDT	511	Gaming Helps! Learning from Strategic Interactions in Natural Dynamics
214	Session 3: April 14 at 6:00am-8:00am PDT	294	Predictive Complexity Priors
215	Session 3: April 14 at 6:00am-8:00am PDT	559	Hyperparameter Transfer Learning with Adaptive Complexity
216	Session 3: April 14 at 6:00am-8:00am PDT	103	A Bayesian nonparametric approach to count-min sketch under power-law data streams
217	Session 3: April 14 at 6:00am-8:00am PDT	327	An analysis of the adaptation speed of causal models
218	Session 3: April 14 at 6:00am-8:00am PDT	739	Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
219	Session 3: April 14 at 6:00am-8:00am PDT	626	Learning Complexity of Simulated Annealing
220	Session 3: April 14 at 6:00am-8:00am PDT	954	Aggregating Incomplete and Noisy Rankings
221	Session 3: April 14 at 6:00am-8:00am PDT	1563	Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
222	Session 3: April 14 at 6:00am-8:00am PDT	78	Fully Gap-Dependent Bounds for Multinomial Logit Bandit
223	Session 3: April 14 at 6:00am-8:00am PDT	461	Top-m identification for linear bandits
224	Session 3: April 14 at 6:00am-8:00am PDT	1268	Multi-armed bandits with cost subsidy
225	Session 3: April 14 at 6:00am-8:00am PDT	729	Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
226	Session 3: April 14 at 6:00am-8:00am PDT	41	On the proliferation of support vectors in high dimensions
227	Session 3: April 14 at 6:00am-8:00am PDT	811	High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding
228	Session 3: April 14 at 6:00am-8:00am PDT	1523	Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information
229	Session 3: April 14 at 6:00am-8:00am PDT	190	The Sample Complexity of Level Set Approximation
230	Session 3: April 14 at 6:00am-8:00am PDT	426	On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
231	Session 3: April 14 at 6:00am-8:00am PDT	575	Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes
232	Session 3: April 14 at 6:00am-8:00am PDT	867	Budgeted and Non-Budgeted Causal Bandits
233	Session 3: April 14 at 6:00am-8:00am PDT	238	Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications
234	Session 3: April 14 at 6:00am-8:00am PDT	274	Kernel regression in high dimensions: Refined analysis beyond double descent
235	Session 3: April 14 at 6:00am-8:00am PDT	664	Collaborative Classification from Noisy Labels
236	Session 3: April 14 at 6:00am-8:00am PDT	736	Online probabilistic label trees
237	Session 3: April 14 at 6:00am-8:00am PDT	475	Online k-means clustering
238	Session 3: April 14 at 6:00am-8:00am PDT	707	Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects
239	Session 3: April 14 at 6:00am-8:00am PDT	457	Linearly Constrained Gaussian Processes with Boundary Conditions
240	Session 3: April 14 at 6:00am-8:00am PDT	747	Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations
241	Session 3: April 14 at 6:00am-8:00am PDT	1508	Calibrated Adaptive Probabilistic ODE Solvers
242	Session 3: April 14 at 6:00am-8:00am PDT	104	Nonlinear Functional Output Regression: A Dictionary Approach
243	Session 3: April 14 at 6:00am-8:00am PDT	175	Fast learning in reproducing kernel Krein spaces via signed measures
244	Session 3: April 14 at 6:00am-8:00am PDT	431	Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy
245	Session 3: April 14 at 6:00am-8:00am PDT	1789	Regularized ERM on random subspaces
246	Session 3: April 14 at 6:00am-8:00am PDT	776	Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
247	Session 3: April 14 at 6:00am-8:00am PDT	1618	On the Memory Mechanism of Tensor-Power Recurrent Models
248	Session 3: April 14 at 6:00am-8:00am PDT	1636	Deep Generative Pattern-Set Mixture Models
249	Session 3: April 14 at 6:00am-8:00am PDT	783	Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning
250	Session 3: April 14 at 6:00am-8:00am PDT	321	Nested Barycentric Coordinate System as an Explicit Feature Map
251	Session 3: April 14 at 6:00am-8:00am PDT	1581	A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models
252	Session 3: April 14 at 6:00am-8:00am PDT	500	Latent Derivative Bayesian Last Layer Networks
253	Session 3: April 14 at 6:00am-8:00am PDT	366	Deep Fourier kernel for self-attentive point processes
254	Session 3: April 14 at 6:00am-8:00am PDT	875	A Variational Inference Approach to Learning Multivariate Wold Processes
255	Session 3: April 14 at 6:00am-8:00am PDT	885	Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
256	Session 3: April 14 at 6:00am-8:00am PDT	1699	Differentiable Divergences Between Time Series
257	Session 3: April 14 at 6:00am-8:00am PDT	423	ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning
258	Session 3: April 14 at 6:00am-8:00am PDT	70	Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential Inapproximability
259	Session 3: April 14 at 6:00am-8:00am PDT	292	Neural Enhanced Belief Propagation on Factor Graphs
260	Session 3: April 14 at 6:00am-8:00am PDT	529	Inference in Stochastic Epidemic Models via Multinomial Approximations
261	Session 3: April 14 at 6:00am-8:00am PDT	1589	Couplings for Multinomial Hamiltonian Monte Carlo
262	Session 3: April 14 at 6:00am-8:00am PDT	1857	A unified view of likelihood ratio and reparameterization gradients
263	Session 3: April 14 at 6:00am-8:00am PDT	12	Graphical Normalizing Flows
264	Session 3: April 14 at 6:00am-8:00am PDT	568	Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification
265	Session 3: April 14 at 6:00am-8:00am PDT	1530	Scalable Gaussian Process Variational Autoencoders
266	Session 3: April 14 at 6:00am-8:00am PDT	1545	Causal Autoregressive Flows
267	Session 3: April 14 at 6:00am-8:00am PDT	1744	On Multilevel Monte Carlo Unbiased Gradient Estimation for Deep Latent Variable Models
268	Session 3: April 14 at 6:00am-8:00am PDT	577	Efficient Statistics for Sparse Graphical Models from Truncated Samples.
269	Session 3: April 14 at 6:00am-8:00am PDT	758	Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery
270	Session 3: April 14 at 6:00am-8:00am PDT	1587	Dirichlet Pruning for Convolutional Neural Networks
271	Session 3: April 14 at 6:00am-8:00am PDT	1584	Sequential Random Sampling Revisited: Hidden Shuffle Method
272	Session 3: April 14 at 6:00am-8:00am PDT	4	On the Effect of Auxiliary Tasks on Representation Dynamics
273	Session 3: April 14 at 6:00am-8:00am PDT	1582	Logistic Q-Learning
274	Session 3: April 14 at 6:00am-8:00am PDT	1787	Improved Exploration in Factored Average-Reward MDPs
275	Session 3: April 14 at 6:00am-8:00am PDT	1805	On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
276	Session 3: April 14 at 6:00am-8:00am PDT	302	Improving predictions of Bayesian neural nets via local linearization
277	Session 3: April 14 at 6:00am-8:00am PDT	872	Equitable and Optimal Transport with Multiple Agents
278	Session 4: April 14 at 12:45-14:45 PDT	553	Quick Streaming Algorithms for Maximization of Monotone Submodular Functions in Linear Time
279	Session 4: April 14 at 12:45-14:45 PDT	1194	Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience
280	Session 4: April 14 at 12:45-14:45 PDT	560	Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency
281	Session 4: April 14 at 12:45-14:45 PDT	1105	One Sketch for All: Non-linear Random Features from Compressed Linear Measurements
282	Session 4: April 14 at 12:45-14:45 PDT	257	A Deterministic Streaming Sketch for Ridge Regression
283	Session 4: April 14 at 12:45-14:45 PDT	1205	Large Scale K-Median Clustering for Stable Clustering Instances
284	Session 4: April 14 at 12:45-14:45 PDT	1476	Towards Flexible Device Participation in Federated Learning
285	Session 4: April 14 at 12:45-14:45 PDT	259	Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems
286	Session 4: April 14 at 12:45-14:45 PDT	1500	Rao-Blackwellised parallel MCMC
287	Session 4: April 14 at 12:45-14:45 PDT	50	A Fast and Robust Method for Global Topological Functional Optimization
288	Session 4: April 14 at 12:45-14:45 PDT	915	Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization
289	Session 4: April 14 at 12:45-14:45 PDT	1000	Federated Learning with Compression: Unified Analysis and Sharp Guarantees
290	Session 4: April 14 at 12:45-14:45 PDT	615	A Variational Information Bottleneck Approach to Multi-Omics Data Integration
291	Session 4: April 14 at 12:45-14:45 PDT	1094	regret-optimal filtering
292	Session 4: April 14 at 12:45-14:45 PDT	44	Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors
293	Session 4: April 14 at 12:45-14:45 PDT	1736	Rate-Regularization and Generalization in Variational Autoencoders
294	Session 4: April 14 at 12:45-14:45 PDT	193	Curriculum Learning by Optimizing Learning Dynamics
295	Session 4: April 14 at 12:45-14:45 PDT	1780	Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling
296	Session 4: April 14 at 12:45-14:45 PDT	951	Implicit Regularization via Neural Feature Alignment
297	Session 4: April 14 at 12:45-14:45 PDT	1308	DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks
298	Session 4: April 14 at 12:45-14:45 PDT	1400	Understanding Robustness in Teacher-Student Setting: A New Perspective
299	Session 4: April 14 at 12:45-14:45 PDT	111	Learning Smooth and Fair Representations
300	Session 4: April 14 at 12:45-14:45 PDT	1369	Fair for All: Best-effort Fairness Guarantees for Classification
301	Session 4: April 14 at 12:45-14:45 PDT	1503	Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression
302	Session 4: April 14 at 12:45-14:45 PDT	488	Differentially Private Analysis on Graph Streams
303	Session 4: April 14 at 12:45-14:45 PDT	1066	Shuffled Model of Differential Privacy in Federated Learning
304	Session 4: April 14 at 12:45-14:45 PDT	1071	Private optimization without constraint violations
305	Session 4: April 14 at 12:45-14:45 PDT	1098	Evading the Curse of Dimensionality in Unconstrained Private GLMs
306	Session 4: April 14 at 12:45-14:45 PDT	1202	Location Trace Privacy Under Conditional Priors
307	Session 4: April 14 at 12:45-14:45 PDT	254	Learning to Defend by Learning to Attack
308	Session 4: April 14 at 12:45-14:45 PDT	1087	Evaluating Model Robustness to Dataset Shift
309	Session 4: April 14 at 12:45-14:45 PDT	1664	Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions
310	Session 4: April 14 at 12:45-14:45 PDT	1809	Hidden Cost of Randomized Smoothing
311	Session 4: April 14 at 12:45-14:45 PDT	583	Feedback Coding for Active Learning
312	Session 4: April 14 at 12:45-14:45 PDT	604	Towards Understanding the Behaviors of Optimal Deep Active Algorithms
313	Session 4: April 14 at 12:45-14:45 PDT	513	Goodness-of-Fit Test for Mismatched Self-Exciting Processes
314	Session 4: April 14 at 12:45-14:45 PDT	663	Exploiting Equality Constraints in Causal Inference
315	Session 4: April 14 at 12:45-14:45 PDT	835	Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
316	Session 4: April 14 at 12:45-14:45 PDT	1299	Efficient Balanced Treatment Assignments for Experimentation
317	Session 4: April 14 at 12:45-14:45 PDT	564	On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
318	Session 4: April 14 at 12:45-14:45 PDT	115	Contextual Blocking Bandits
319	Session 4: April 14 at 12:45-14:45 PDT	201	Low-rank Generalized Linear Bandit Problems
320	Session 4: April 14 at 12:45-14:45 PDT	1165	Stochastic Bandits with Linear Constraints
321	Session 4: April 14 at 12:45-14:45 PDT	1170	Significance of Gradient Information in Bayesian Optimization
322	Session 4: April 14 at 12:45-14:45 PDT	1694	Combinatorial Gaussian Process Bandits with Probabilistically Triggered Arms
323	Session 4: April 14 at 12:45-14:45 PDT	547	Reaping the Benefits of Bundling under High Production Costs
324	Session 4: April 14 at 12:45-14:45 PDT	1070	A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
325	Session 4: April 14 at 12:45-14:45 PDT	522	A Study of Condition Numbers for First-Order Optimization
326	Session 4: April 14 at 12:45-14:45 PDT	1374	Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension
327	Session 4: April 14 at 12:45-14:45 PDT	889	Localizing Changes in High-Dimensional Regression Models
328	Session 4: April 14 at 12:45-14:45 PDT	1109	Principal Component Regression with Semirandom Observations via Matrix Completion
329	Session 4: April 14 at 12:45-14:45 PDT	1329	Uniform consistency of cross-validation estimators for high-dimensional ridge regression
330	Session 4: April 14 at 12:45-14:45 PDT	1159	Power of Hints for Online Learning with Movement Costs
331	Session 4: April 14 at 12:45-14:45 PDT	71	False Discovery Rates in Biological Networks
332	Session 4: April 14 at 12:45-14:45 PDT	629	Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers
333	Session 4: April 14 at 12:45-14:45 PDT	1240	Robust hypothesis testing and distribution estimation in Hellinger distance
334	Session 4: April 14 at 12:45-14:45 PDT	351	Learning Prediction Intervals for Regression: Generalization and Calibration
335	Session 4: April 14 at 12:45-14:45 PDT	699	Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation
336	Session 4: April 14 at 12:45-14:45 PDT	869	Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss
337	Session 4: April 14 at 12:45-14:45 PDT	1063	A Statistical Perspective on Coreset Density Estimation
338	Session 4: April 14 at 12:45-14:45 PDT	1788	Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries
339	Session 4: April 14 at 12:45-14:45 PDT	918	Selective Classification via One-Sided Prediction
340	Session 4: April 14 at 12:45-14:45 PDT	1042	Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors
341	Session 4: April 14 at 12:45-14:45 PDT	1058	On the Consistency of Metric and Non-Metric K-Medoids
342	Session 4: April 14 at 12:45-14:45 PDT	1365	Product Manifold Learning
343	Session 4: April 14 at 12:45-14:45 PDT	311	Scalable Constrained Bayesian Optimization
344	Session 4: April 14 at 12:45-14:45 PDT	1072	Direct Loss Minimization for Sparse Gaussian Processes
345	Session 4: April 14 at 12:45-14:45 PDT	1314	Kernel Interpolation for Scalable Online Gaussian Processes
346	Session 4: April 14 at 12:45-14:45 PDT	1130	Approximation Algorithms for Orthogonal Non-negative Matrix Factorization
347	Session 4: April 14 at 12:45-14:45 PDT	1515	Probabilistic Sequential Matrix Factorization
348	Session 4: April 14 at 12:45-14:45 PDT	63	Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns
349	Session 4: April 14 at 12:45-14:45 PDT	108	When MAML Can Adapt Fast and How to Assist When It Cannot
350	Session 4: April 14 at 12:45-14:45 PDT	558	On Data Efficiency of Meta-learning
351	Session 4: April 14 at 12:45-14:45 PDT	996	A Theory of Multiple-Source Adaptation with Limited Target Labeled Data
352	Session 4: April 14 at 12:45-14:45 PDT	271	Geometrically Enriched Latent Spaces
353	Session 4: April 14 at 12:45-14:45 PDT	1291	Fast and Smooth Interpolation on Wasserstein Space
354	Session 4: April 14 at 12:45-14:45 PDT	1271	The Multiple Instance Learning Gaussian Process Probit Model
355	Session 4: April 14 at 12:45-14:45 PDT	1068	CLAR: Contrastive Learning of Auditory Representations
356	Session 4: April 14 at 12:45-14:45 PDT	1806	Meta-Learning Divergences for Variational Inference
357	Session 4: April 14 at 12:45-14:45 PDT	892	Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
358	Session 4: April 14 at 12:45-14:45 PDT	1137	A Change of Variables Method For Rectangular Matrix-Vector Products
359	Session 4: April 14 at 12:45-14:45 PDT	376	Provable Hierarchical Imitation Learning via EM
360	Session 4: April 14 at 12:45-14:45 PDT	1366	Automatic Differentiation Variational Inference with Mixtures
361	Session 4: April 14 at 12:45-14:45 PDT	1497	Hyperbolic graph embedding with enhanced semi-implicit variational inference.
362	Session 4: April 14 at 12:45-14:45 PDT	483	Abstract Value Iteration for Hierarchical Reinforcement Learning
363	Session 4: April 14 at 12:45-14:45 PDT	505	Provably Safe PAC-MDP Exploration Using Analogies
364	Session 4: April 14 at 12:45-14:45 PDT	1263	Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
365	Session 4: April 14 at 12:45-14:45 PDT	1408	Finite-Sample Regret Bound for Distributionally Robust Policy Learning in Tabular RL
366	Session 5: April 15 at 7:30am-9:30am PDT	250	Hierarchical Clustering via Sketches and Hierarchical Correlation Clustering
367	Session 5: April 15 at 7:30am-9:30am PDT	7	Projection-Free Optimization on Uniformly Convex Sets
368	Session 5: April 15 at 7:30am-9:30am PDT	549	Momentum Improves Optimization on Riemannian Manifolds
369	Session 5: April 15 at 7:30am-9:30am PDT	689	Iterative regularization for convex regularizers
370	Session 5: April 15 at 7:30am-9:30am PDT	773	Explicit Regularization of Stochastic Gradient Methods through Duality
371	Session 5: April 15 at 7:30am-9:30am PDT	1557	Local SGD: Unified Theory and New Efficient Methods
372	Session 5: April 15 at 7:30am-9:30am PDT	1772	LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads
373	Session 5: April 15 at 7:30am-9:30am PDT	1814	Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates
374	Session 5: April 15 at 7:30am-9:30am PDT	16	CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices
375	Session 5: April 15 at 7:30am-9:30am PDT	419	Hadamard Wirtinger Flow for Sparse Phase Retrieval
376	Session 5: April 15 at 7:30am-9:30am PDT	898	Learning Matching Representations for Individualized Organ Transplantation Allocation
377	Session 5: April 15 at 7:30am-9:30am PDT	1743	Model updating after interventions paradoxically introduces bias
378	Session 5: April 15 at 7:30am-9:30am PDT	734	Understanding and Mitigating Exploding Inverses in Invertible Neural Networks
379	Session 5: April 15 at 7:30am-9:30am PDT	904	Learning Contact Dynamics using Physically Structured Neural Networks
380	Session 5: April 15 at 7:30am-9:30am PDT	1001	Variational Autoencoder with Learned Latent Structure
381	Session 5: April 15 at 7:30am-9:30am PDT	1558	Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
382	Session 5: April 15 at 7:30am-9:30am PDT	1741	Longitudinal Variational Autoencoder
383	Session 5: April 15 at 7:30am-9:30am PDT	1628	Causal Inference under Networked Interference and Intervention Policy Enhancement
384	Session 5: April 15 at 7:30am-9:30am PDT	494	Learning with Hyperspherical Uniformity
385	Session 5: April 15 at 7:30am-9:30am PDT	73	Fourier Bases for Solving Permutation Puzzles
386	Session 5: April 15 at 7:30am-9:30am PDT	194	Approximating Lipschitz continuous functions with GroupSort neural networks
387	Session 5: April 15 at 7:30am-9:30am PDT	542	Stable ResNet
388	Session 5: April 15 at 7:30am-9:30am PDT	942	Fractional moment-preserving initialization schemes for training deep neural networks
389	Session 5: April 15 at 7:30am-9:30am PDT	1178	Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
390	Session 5: April 15 at 7:30am-9:30am PDT	946	Federated f-Differential Privacy
391	Session 5: April 15 at 7:30am-9:30am PDT	956	Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models
392	Session 5: April 15 at 7:30am-9:30am PDT	1428	Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT
393	Session 5: April 15 at 7:30am-9:30am PDT	339	Efficient Computation and Analysis of Distributional Shapley Values
394	Session 5: April 15 at 7:30am-9:30am PDT	185	Active Learning with Maximum Margin Sparse Gaussian Processes
395	Session 5: April 15 at 7:30am-9:30am PDT	1039	Bayesian Inference with Certifiable Adversarial Robustness
396	Session 5: April 15 at 7:30am-9:30am PDT	1120	Variational inference for nonlinear ordinary differential equations
397	Session 5: April 15 at 7:30am-9:30am PDT	1313	Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon
398	Session 5: April 15 at 7:30am-9:30am PDT	684	Why did the distribution change?
399	Session 5: April 15 at 7:30am-9:30am PDT	940	High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation
400	Session 5: April 15 at 7:30am-9:30am PDT	884	The Teaching Dimension of Kernel Perceptron
401	Session 5: April 15 at 7:30am-9:30am PDT	39	On Information Gain and Regret Bounds in Gaussian Process Bandits
402	Session 5: April 15 at 7:30am-9:30am PDT	272	Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting
403	Session 5: April 15 at 7:30am-9:30am PDT	277	Self-Concordant Analysis of Generalized Linear Bandits with Forgetting
404	Session 5: April 15 at 7:30am-9:30am PDT	420	Stochastic Linear Bandits Robust to Adversarial Attacks
405	Session 5: April 15 at 7:30am-9:30am PDT	759	No-regret Algorithms for Multi-task Bayesian Optimization
406	Session 5: April 15 at 7:30am-9:30am PDT	926	Smooth Bandit Optimization: Generalization to Holder Space
407	Session 5: April 15 at 7:30am-9:30am PDT	1090	Continuum-Armed Bandits: A Function Space Perspective
408	Session 5: April 15 at 7:30am-9:30am PDT	1619	Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
409	Session 5: April 15 at 7:30am-9:30am PDT	187	A Stein goodness of fit test for exponential random graph models
410	Session 5: April 15 at 7:30am-9:30am PDT	975	Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent
411	Session 5: April 15 at 7:30am-9:30am PDT	1689	Convergence Properties of Stochastic Hypergradients
412	Session 5: April 15 at 7:30am-9:30am PDT	439	The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers
413	Session 5: April 15 at 7:30am-9:30am PDT	1738	Asymptotics of Ridge(less) Regression under General Source Condition
414	Session 5: April 15 at 7:30am-9:30am PDT	998	Group testing for connected communities
415	Session 5: April 15 at 7:30am-9:30am PDT	141	Online Active Model Selection for Pre-trained Classifiers
416	Session 5: April 15 at 7:30am-9:30am PDT	1566	Revisiting Projection-free Online Learning: the Strongly Convex Case
417	Session 5: April 15 at 7:30am-9:30am PDT	865	Approximate Data Deletion from Machine Learning Models
418	Session 5: April 15 at 7:30am-9:30am PDT	1652	A Stochastic Approximate Gradient Ascent Method for Bayesian Experimental Design with Implicit Models
419	Session 5: April 15 at 7:30am-9:30am PDT	66	When OT meets MoM: Robust Estimation of Wasserstein Distance
420	Session 5: April 15 at 7:30am-9:30am PDT	1677	Robust Learning under Strong Noise via SQs
421	Session 5: April 15 at 7:30am-9:30am PDT	184	Approximate Message Passing with Spectral Initialization for Generalized Linear Models
422	Session 5: April 15 at 7:30am-9:30am PDT	260	On the role of data in PAC-Bayes
423	Session 5: April 15 at 7:30am-9:30am PDT	574	Learning User Preferences in Non-Stationary Environments
424	Session 5: April 15 at 7:30am-9:30am PDT	950	Clustering multilayer graphs with missing nodes
425	Session 5: April 15 at 7:30am-9:30am PDT	1583	Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
426	Session 5: April 15 at 7:30am-9:30am PDT	6	LassoNet: Neural Networks with Feature Sparsity
427	Session 5: April 15 at 7:30am-9:30am PDT	456	Transforming Gaussian Processes With Normalizing Flows
428	Session 5: April 15 at 7:30am-9:30am PDT	724	Sparse Algorithms for Markovian Gaussian Processes
429	Session 5: April 15 at 7:30am-9:30am PDT	1245	Faster Kernel Interpolation for Gaussian Processes
430	Session 5: April 15 at 7:30am-9:30am PDT	459	Noise Contrastive Meta-Learning for ConditionalDensity Estimation using Kernel Mean Embeddings
431	Session 5: April 15 at 7:30am-9:30am PDT	900	Stochastic Gradient Descent Meets Distribution Regression
432	Session 5: April 15 at 7:30am-9:30am PDT	1467	A Spectral Analysis of Dot-product Kernels
433	Session 5: April 15 at 7:30am-9:30am PDT	1659	Distribution Regression for Sequential Data
434	Session 5: April 15 at 7:30am-9:30am PDT	1682	Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models
435	Session 5: April 15 at 7:30am-9:30am PDT	304	Generalized Spectral Clustering via Gromov-Wasserstein Learning
436	Session 5: April 15 at 7:30am-9:30am PDT	1555	Spectral Tensor Train Parameterization of Deep Learning Layers
437	Session 5: April 15 at 7:30am-9:30am PDT	214	Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
438	Session 5: April 15 at 7:30am-9:30am PDT	434	Aligning Time Series on Incomparable Spaces
439	Session 5: April 15 at 7:30am-9:30am PDT	1546	Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
440	Session 5: April 15 at 7:30am-9:30am PDT	746	Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
441	Session 5: April 15 at 7:30am-9:30am PDT	160	Benchmarking Simulation-Based Inference
442	Session 5: April 15 at 7:30am-9:30am PDT	788	Moment-Based Variational Inference for Stochastic Differential Equations
443	Session 5: April 15 at 7:30am-9:30am PDT	546	Latent variable modeling with random features
444	Session 5: April 15 at 7:30am-9:30am PDT	1635	Latent Gaussian process with composite likelihoods and numerical quadrature
445	Session 5: April 15 at 7:30am-9:30am PDT	290	Automatic structured variational inference
446	Session 5: April 15 at 7:30am-9:30am PDT	441	Measure Transport with Kernel Stein Discrepancy
447	Session 5: April 15 at 7:30am-9:30am PDT	897	Context-Specific Likelihood Weighting
448	Session 5: April 15 at 7:30am-9:30am PDT	1742	An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo
449	Session 5: April 15 at 7:30am-9:30am PDT	147	Online Sparse Reinforcement Learning
450	Session 5: April 15 at 7:30am-9:30am PDT	157	A Contraction Approach to Model-based Reinforcement Learning
451	Session 5: April 15 at 7:30am-9:30am PDT	233	Adaptive Approximate Policy Iteration
452	Session 5: April 15 at 7:30am-9:30am PDT	425	Optimizing Percentile Criterion using Robust MDPs
453	Session 5: April 15 at 7:30am-9:30am PDT	463	When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
454	Session 5: April 15 at 7:30am-9:30am PDT	756	Reinforcement Learning in Parametric MDPs with Exponential Families
455	Session 5: April 15 at 7:30am-9:30am PDT	1107	Reinforcement Learning for Constrained and Multi-Objective Markov Decision Processes
456	Session 5: April 15 at 7:30am-9:30am PDT	1548	A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces