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DatePresenterTopicPaper Title
Conferences
Paper URLSlidesQuiz
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Jan 6Jiawei ZhangIntroductionCourse Introduction.NANA
https://drive.google.com/file/d/1WeTYYWm_UD7tZL6Z93LdLuo30g19f79m/view?usp=sharing
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Jan 8Jiawei ZhangIntroductionMachine Learning Overview (Sections 2.1-2.4)Book Chapter
http://www.ifmlab.org/files/book/broad_learning/chap2.pdf
https://drive.google.com/file/d/1UdStOxdRfu0UlrbtfhSW30KnP1bNAjbH/view?usp=sharing
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Jan 13Jiawei ZhangIntroductionMachine Learning Overview (Sections 2.5-2.7)Book Chapter
http://www.ifmlab.org/files/book/broad_learning/chap2.pdf
https://drive.google.com/file/d/1GAIa6OOXfFlXQxc2OAnaG26u1VkZwfeD/view?usp=sharing
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A Hands-on Tutorial IntroductionNANA
https://drive.google.com/file/d/1DYTEFPsmKRQ_bQMFB6SGS1vYZbQxg6_1/view?usp=sharing
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Jan 15Haeseung Jeong
Deep Learning & Optimization Algorithms
An overview of gradient descent optimization algorithmsarXivhttps://arxiv.org/pdf/1609.04747.pdf
https://drive.google.com/open?id=1zpGLVgHKHx8aXpmRect6YKJywNU1-2lw
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Jan 22Yixin Chen
Deep Learning & Optimization Algorithms
On the Variance of the Adaptive Learning Rate and BeyondICLR'20https://arxiv.org/abs/1908.03265
https://drive.google.com/open?id=1xgky5VVCq4N4YrmvCdsFm3RRZacwtL1j
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Jan 27Mohsen Gavahi
Deep Learning & Optimization Algorithms
Putting An End to End-to-End: Gradient-Isolated Learning of Representations
NIPS'19
https://papers.nips.cc/paper/8568-putting-an-end-to-end-to-end-gradient-isolated-learning-of-representations.pdf
https://drive.google.com/open?id=11JF5Ekg2F5cbKUMX4_XgpqNJ7Tw0C2eZ
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Jan 29Daniel BisText Mining & NLPXLNet: Generalized Autoregressive Pretraining for Language UnderstandingNIPS'19
https://papers.nips.cc/paper/8812-xlnet-generalized-autoregressive-pretraining-for-language-understanding.pdf
https://drive.google.com/open?id=12Cx5LhSDuV8LyBTOcF_1JMwh-2UiodrD
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Feb 3Yan Ai
Deep Learning & Optimization Algorithms
Weight Agnostic Neural NetworksNIPS'19
https://papers.nips.cc/paper/8777-weight-agnostic-neural-networks
https://drive.google.com/open?id=1trRbAiSLNYG1CpUy4s7l9GNOD8NwMXX7
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Feb 5Yixin Chen
Deep Learning & Optimization Algorithms
Probabilistic Logic Neural Networks for ReasoningNIPS'19
https://papers.nips.cc/paper/8987-probabilistic-logic-neural-networks-for-reasoning.pdf
https://drive.google.com/open?id=17rIzHpt11BkoROSSCOUw5vVkwCKOL9aZ
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Feb 10Haopeng ZhangText Mining & NLPCode completion with neural attention and pointer networksIJCAI'18
https://www.ijcai.org/proceedings/2018/0578.pdf
https://drive.google.com/open?id=12eCharGGdhDUAoA-l8FsNhWCweoEP0lI
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Feb 12Jiyang BaiNetwork Embedding & Graph MiningHyperbolic Graph Neural NetworksNIPS'19
https://papers.nips.cc/paper/9033-hyperbolic-graph-neural-networks.pdf
https://drive.google.com/open?id=1-Z9sKqRuYV6ushdCInAQWZlHhWcSfp-s
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Feb 17Jiyang BaiNetwork Embedding & Graph MiningHyperbolic Graph Convolutional Neural NetworksNIPS'19
https://papers.nips.cc/paper/8733-hyperbolic-graph-convolutional-neural-networks.pdf
https://drive.google.com/open?id=10g6O-xTxsYNsj6JrKh707heLRn-zWaBM
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Feb 19Yixin ChenNetwork Embedding & Graph MiningGraph Classification using Structural AttentionKDD'18
http://ryanrossi.com/pubs/KDD18-graph-attention-model.pdf
https://drive.google.com/open?id=1AKVBL-N6HdSC-nujdVmqlXYl-t_N9rGi
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Feb 24Yuxiang RenNetwork Embedding & Graph Mining
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
NIPS'19
https://papers.nips.cc/paper/8809-graph-neural-tangent-kernel-fusing-graph-neural-networks-with-graph-kernels.pdf
https://drive.google.com/open?id=17e-AiIUd4WabieY0jqF69uqmDB_wQ69K
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Feb 26Yuxiang RenNetwork Embedding & Graph MiningUniversal Invariant and Equivariant Graph Neural NetworksNIPS'19
https://papers.nips.cc/paper/8931-universal-invariant-and-equivariant-graph-neural-networks.pdf
https://drive.google.com/open?id=1N9arFSTZxcZo1_yt7woAc5WWshApSdnk
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March 2Lin MengNetwork Embedding & Graph Mining
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
NIPS'19
https://papers.nips.cc/paper/9303-layer-dependent-importance-sampling-for-training-deep-and-large-graph-convolutional-networks.pdf
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March 4Mohsen Gavahi
Deep Learning & Optimization Algorithms
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
NIPS'19
https://papers.nips.cc/paper/9063-wide-neural-networks-of-any-depth-evolve-as-linear-models-under-gradient-descent.pdf
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March 9Haopeng ZhangText Mining & NLP
Bridging the Gap between Training and Inference for Neural Machine Translation
ACL'19
https://www.aclweb.org/anthology/P19-1426.pdf
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March 11Lin Meng
Deep Learning & Optimization Algorithms
Towards Understanding the Importance of Shortcut Connections in Residual Networks
NIPS'19
https://papers.nips.cc/paper/9003-towards-understanding-the-importance-of-shortcut-connections-in-residual-networks.pdf
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March 23Xibo ChenText Mining & NLPLambdaNet: Probabilistic Type Inference using Graph Neural NetworksICLR'20
https://openreview.net/forum?id=Hkx6hANtwH
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March 25Daniel BisText Mining & NLP
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
ICLR'19https://arxiv.org/pdf/1810.09536.pdf
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March 30Yan AiImage & VisionExploring Visual Relationship for Image CaptioningCVPR'18
http://openaccess.thecvf.com/content_ECCV_2018/papers/Ting_Yao_Exploring_Visual_Relationship_ECCV_2018_paper.pdf
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April 1Jiyang BaiImage & VisionGraph R-CNN for Scene Graph GenerationCVPR'18
http://openaccess.thecvf.com/content_ECCV_2018/papers/Jianwei_Yang_Graph_R-CNN_for_ECCV_2018_paper.pdf
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April 6Xibo ChenImage & Vision
Reasoning-RCNN: Unifying Adaptive Global Reasoning into Large-scale Object Detection
CVPR'19
http://openaccess.thecvf.com/content_CVPR_2019/papers/Xu_Reasoning-RCNN_Unifying_Adaptive_Global_Reasoning_Into_Large-Scale_Object_Detection_CVPR_2019_paper.pdf
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April 8Haeseung JeongImage & VisionA Style-Based Generator Architecture for Generative Adversarial NetworksCVPR'19https://arxiv.org/abs/1812.04948
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April 13Haopeng ZhangImage & Vision
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
ICLR'19
https://openreview.net/forum?id=Bygh9j09KX
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April 15Yili RenRecommendationHierarchical Gating Networks for Sequential RecommendationKDD'19
https://www.kdd.org/kdd2019/accepted-papers/view/hierarchical-gating-networks-for-sequential-recommendation
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April 20Yili RenRecommendation
Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination
KDD'19
https://www.kdd.org/kdd2019/accepted-papers/view/dual-sequential-prediction-models-linking-sequential-recommendation-and-inf
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April 22Lin MengRecommendationKGAT: Knowledge Graph Attention Network for RecommendationKDD'19
https://www.kdd.org/kdd2019/accepted-papers/view/kgat-knowledge-graph-attention-network-for-recommendation
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