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Andrew ID of Grader:
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10708 Final Presentation Grading Sheet
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Time Project nameteam membersPresentation (20) (individually):
Conciseness; Clarity; QA		Problem (15):
Clarity, Significance, Related Work		Method (30):
Soundness, Originality, Relevance to PGM		Results (15):
Setup;
Comparison; Results/analysis
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S-I:
8:30 - 12:30		8:30
-8:45		1 Non-negative Sparse Probabilistic PCARaied Aljadaany (raljadaa)
Shi Zong (szong)
Chenchen Zhu (chenchez)
Dipan Pal (dipanp)
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8:45
-9:00		2 Word Sense Disambiguation Using Graphical ModelsDevendra Chaplot (dchaplot)
Jakob Bauer (jsbauer)
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9:00
-9:15		3 Dynamic Topic Model for Topic Split and MergeJing Chen
Mengtian Li
Lanxiao Xu
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9:15
-9:30		4 Correlated Topic Modeling via EmbeddingsYuxing Zhang
Lidan Mu (lmu)
Tianshu Ren (tren)
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9:30
-9:45		5 Semi Markov Models with CNNs for Action DetectionAchal Dave (achald)
Ankit Laddha (aladdha)
Mengxin Li (mengxin1)
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9:45
-10:00		6 Stochastic L-BFGS for Restricted Boltzmann MachineHsu-Chieh Hu (hsuchieh)
Chun-Liang Li (chunlial)
Po-Wei Wang (poweiw)
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10:00-10:157 Self-localization for Autonomous Vehicles using Deep Learning and Probabilistic Graphical ModelsHan Lu (hlu2)
Wei-Chiu Ma (weichium)
Chieh Lo (chiehl)
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10:15-10:308 Deep learning model on graph-structured dataXuezhe Ma
Xingyu Yan
Chiqun Zhang
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10:30-10:459 CNNs on a graph-structured dataPurvasha Chakravart
Yotam Hechtlinger
Jining Qin
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10:45-11:0010 Learning Graph Matching with DNNsXuanchong Li
Cuong Nguyen
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11:00-11:1511 Mean Field Inference of High Order CRF for Semantic 3D ReconstructionShichao Yang (shichaoy)
Yulan Huang (yulanh)
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11:15-11:3012 Sketching Based Kernel Belief Propagation for Factor GraphsYining Wang (yiningwa)
Renato Negrinho (renatomp)
Eric Wong (ericwong)
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11:30-11:4513 Thin Neural Network: Does overparameterized nets really need to be that fat?Qi Guo (qiguo)
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11:45-12:0014 Your Bayesian Role Model
A Probabilistic Graphical Model of Roles in Discourse		Keith Maki (kmaki)
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12:00-12:1515 Learning Graph CausalityYanyu Liang (yanyul)
Xiongtao Ruan (xruan)
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Lunch break: 12:30pm - 1:30pm
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S-II:
1:30-5:00		1:30-
1:45		1 Scalable Bayesian Modeling of Corrosion in PipelinesChristoph Dann (cdann)
Petar Stojanov (pstojano)
Rohan Varma (rohanv)
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1:45-
2:00		2 Learning Gene Regulatory Networks under SNP Perturbations using eQTL and RNAseq DataKai-Wen Liang (kaiwenl)
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2:00-
2:15		3 Spectral Learning of Nonparametric HMMsMaruan Al-Shedivat (mshediva)
Kirthevasan Kandasamy (kkandasa)
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2:15-
2:30		4 Toward End-to-End Optical Character Recognition by Deep LearningSilun Wang (silunw)
Longqi Cai (longqic)
Man-Chia Chang (manchiac)
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2:30-
2:45		5 Optical Graph RecognitionBinxuan Huang (binxuanh)
Sumeet Kumar (sumeetku)
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2:45-
3:00		6 Bayesian Approaches for Structured Learning of Deep Neural NetworksOtilia Stretcu
Yichong Xu
Christy Li
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3:00-
3:15		7 Joint GGM Goodness-of-Fit Testing for Time Series DataNatalie Klein (neklein)
Kevin Lin (kevinl1)
Fuchen Liu (fuchenl)
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3:15-
3:30		8 Video concept embeddingAnirudh Vemula
Rahul Nallamothu
Zahir Bokhari
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3:30-
3:45		9 Tracking the Evolution and Migration of Topics through Social NetworksHayden Luse (hluse)
Michael Muehl (mmuehl)
Joseph Runde (jrunde)
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3:45-
4:00		10 Deep Learning Based Semantic Image Segmentation with Conditional Random FieldYu Zhang (yuz4)
Haoqi Fan (haoqif)
Anbang Hu (anbangh)
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4:00-
4:15		11 Context Generative RNN LMSai Bandiatmakuri
Judy Chang
Pankesh Bamotra
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4:15-
4:30		12 Mapping Heterogeneous Label Space via Deep AutoencodersWei-Cheng Chang
Tzu-Ming Kuot
Frederick Liu
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