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• Deep Spiking Neural Network with Neural Oscillation and Spike-Phase Information

  Yi Chen, Hong Qu, Malu Zhang, Yuchen Wang

  7073-7080

  2021-05-18

• HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks

  Yuanyuan Chen, Boyang Li, Han Yu, Pengcheng Wu, Chunyan Miao

  7081-7089

  2021-05-18

• NASGEM: Neural Architecture Search via Graph Embedding Method

  Hsin-Pai Cheng, Tunhou Zhang, Yixing Zhang, Shiyu Li, Feng Liang, Feng Yan, Meng Li, Vikas Chandra, Hai Li, Yiran Chen

  7090-7098

  2021-05-18

• Neighborhood Consensus Networks for Unsupervised Multi-view Outlier Detection

  Li Cheng, Yijie Wang, Xinwang Liu

  7099-7106

  2021-05-18

• Self-Progressing Robust Training

  Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das

  7107-7115

  2021-05-18

• Continuous-Time Attention for Sequential Learning

  Jen-Tzung Chien, Yi-Hsiang Chen

  7116-7124

  2021-05-18

• Transfer Learning for Efficient Iterative Safety Validation

  Anthony Corso, Mykel J. Kochenderfer

  7125-7132

  2021-05-18

• Computationally Tractable Riemannian Manifolds for Graph Embeddings

  Calin Cruceru, Gary Becigneul, Octavian-Eugen Ganea

  7133-7141

  2021-05-18

• Cost-aware Graph Generation: A Deep Bayesian Optimization Approach

  Jiaxu Cui, Bo Yang, Bingyi Sun, Jiming Liu

  7142-7150

  2021-05-18

• Type-augmented Relation Prediction in Knowledge Graphs

  Zijun Cui, Pavan Kapanipathi, Kartik Talamadupula, Tian Gao, Qiang Ji

  7151-7159

  2021-05-18

• The Value-Improvement Path: Towards Better Representations for Reinforcement Learning

  Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver

  7160-7168

  2021-05-18

• Loop Estimator for Discounted Values in Markov Reward Processes

  Falcon Z. Dai, Matthew R. Walter

  7169-7175

  2021-05-18

• Differentially Private Stochastic Coordinate Descent

  Georgios Damaskinos, Celestine Mendler-Dünner, Rachid Guerraoui, Nikolaos Papandreou, Thomas Parnell

  7176-7184

  2021-05-18

• Generalized Adversarially Learned Inference

  Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai

  7185-7192

  2021-05-18

• Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models

  Antoine Dedieu, Miguel Lázaro-Gredilla, Dileep George

  7193-7200

  2021-05-18

• Learning with Retrospection

  Xiang Deng, Zhongfei Zhang

  7201-7209

  2021-05-18

• Mercer Features for Efficient Combinatorial Bayesian Optimization

  Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa

  7210-7218

  2021-05-18

• Differentially Private and Communication Efficient Collaborative Learning

  Jiahao Ding, Guannan Liang, Jinbo Bi, Miao Pan

  7219-7227

  2021-05-18

• Knowledge Refinery: Learning from Decoupled Label

  Qianggang Ding, Sifan Wu, Tao Dai, Hao Sun, Jiadong Guo, Zhang-Hua Fu, Shutao Xia

  7228-7235

  2021-05-18

• Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization

  Kien Do, Truyen Tran, Svetha Venkatesh

  7236-7244

  2021-05-18

• Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences

  Andis Draguns, Emīls Ozoliņš, Agris Šostaks, Matīss Apinis, Karlis Freivalds

  7245-7253

  2021-05-18

• A One-Size-Fits-All Solution to Conservative Bandit Problems

  Yihan Du, Siwei Wang, Longbo Huang

  7254-7261

  2021-05-18

• Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback

  Yihan Du, Yuko Kuroki, Wei Chen

  7262-7270

  2021-05-18

• Knowledge Refactoring for Inductive Program Synthesis

  Sebastijan Dumancic, Tias Guns, Andrew Cropper

  7271-7278

  2021-05-18

• Semi-Supervised Metric Learning: A Deep Resurrection

  Ujjal Kr Dutta, Mehrtash Harandi, C Chandra Shekhar

  7279-7287

  2021-05-18