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• Hierarchical Relational Inference

  Aleksandar Stanić, Sjoerd van Steenkiste, Jürgen Schmidhuber

  9730-9738

  2021-05-18

• `Less Than One'-Shot Learning: Learning N Classes From M < N Samples

  Ilia Sucholutsky, Matthias Schonlau

  9739-9746

  2021-05-18

• HiABP: Hierarchical Initialized ABP for Unsupervised Representation Learning

  Jiankai Sun, Rui Liu, Bolei Zhou

  9747-9755

  2021-05-18

• Stability and Generalization of Decentralized Stochastic Gradient Descent

  Tao Sun, Dongsheng Li, Bao Wang

  9756-9764

  2021-05-18

• TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL

  Yanchao Sun, Xiangyu Yin, Furong Huang

  9765-9773

  2021-05-18

• PAC Learning of Causal Trees with Latent Variables

  Prasad Tadepalli, Stuart J. Russell

  9774-9781

  2021-05-18

• Learning Dynamics Models with Stable Invariant Sets

  Naoya Takeishi, Yoshinobu Kawahara

  9782-9790

  2021-05-18

• Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions

  Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi

  9791-9798

  2021-05-18

• Explicitly Modeled Attention Maps for Image Classification

  Andong Tan, Duc Tam Nguyen, Maximilian Dax, Matthias Nießner, Thomas Brox

  9799-9807

  2021-05-18

• Proxy Graph Matching with Proximal Matching Networks

  Hao-Ru Tan, Chuang Wang, Si-Tong Wu, Tie-Qiang Wang, Xu-Yao Zhang, Cheng-Lin Liu

  9808-9815

  2021-05-18

• Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks

  Weihao Tan, Devdhar Patel, Robert Kozma

  9816-9824

  2021-05-18

• Empowering Adaptive Early-Exit Inference with Latency Awareness

  Xinrui Tan, Hongjia Li, Liming Wang, Xueqing Huang, Zhen Xu

  9825-9833

  2021-05-18

• Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction

  Hongyao Tang, Zhaopeng Meng, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Jianye Hao

  9834-9842

  2021-05-18

• Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization

  Wei Tao, Wei Li, Zhisong Pan, Qing Tao

  9843-9850

  2021-05-18

• Evolutionary Approach for AutoAugment Using the Thermodynamical Genetic Algorithm

  Akira Terauchi, Naoki Mori

  9851-9858

  2021-05-18

• Semi-Supervised Knowledge Amalgamation for Sequence Classification

  Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A Rundensteiner

  9859-9867

  2021-05-18

• Online Non-Monotone DR-Submodular Maximization

  Nguyễn Kim Thắng, Abhinav Srivastav

  9868-9876

  2021-05-18

• Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain

  Jinyu Tian, Jiantao Zhou, Yuanman Li, Jia Duan

  9877-9885

  2021-05-18

• Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration

  Christian Tomani, Florian Buettner

  9886-9896

  2021-05-18

• Meta Learning for Causal Direction

  Jean-François Ton, Dino Sejdinovic, Kenji Fukumizu

  9897-9905

  2021-05-18

• Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior

  Anh Tong, Toan M Tran, Hung Bui, Jaesik Choi

  9906-9914

  2021-05-18

• Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems

  Anh Tong, Jaesik Choi

  9915-9922

  2021-05-18

• Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods

  Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso

  9923-9931

  2021-05-18

• Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach

  Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck

  9932-9939

  2021-05-18

• Learning Adjustment Sets from Observational and Limited Experimental Data

  Sofia Triantafillou, Greg Cooper

  9940-9948

  2021-05-18