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闲情居|机器学习领域顶会ICML20精选论文分享( 六 )


Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions Ahmed Alaa, Mihaela van der Schaar
Disentangling Trainability and Generalization in Deep Neural Networks Lechao Xiao, Jeffrey Pennington, Samuel Schoenholz
Moniqua: Modulo Quantized Communication in Decentralized SGD Yucheng Lu, Christopher De Sa
Expectation Maximization with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation Amr Mohamed Alexandari, Anshul Kundaje, Avanti Shrikumar
Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights and Algorithms Chaosheng Dong, Bo Zeng
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain COUILLET
Optimizing Data Usage via Differentiable Rewards Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Jaime Carbonell, Graham Neubig
Optimistic Policy Optimization with Bandit Feedback Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor
Maximum-and-Concatenation Networks Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin
Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu
Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data Wenkai Xu, Tamara Fernandez, Nicolas Rivera, Arthur Gretton
Efficient Intervention Design for Causal Discovery with Latents Raghavendra Addanki, Shiva Kasiviswanathan, Andrew McGregor, Cameron Musco
Certified Data Removal from Machine Learning Models Chuan Guo, Tom Goldstein, Awni Hannun, Laurens van der Maaten
One Size Fits All: Can We Train One Denoiser for All Noise Levels? Abhiram Gnanasambandam, Stanley Chan
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation Marc Brockschmidt
Sparse Gaussian Processes with Spherical Harmonic Features Vincent Dutordoir, Nicolas Durrande, James Hensman
Asynchronous Coagent Networks James Kostas, Chris Nota, Philip Thomas
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James Duncan
Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling Yao Liu, Pierre-Luc Bacon, Emma Brunskill
Taylor Expansion Policy Optimization Yunhao Tang, Michal Valko, Remi Munos
Reinforcement Learning for Integer Programming: Learning to Cut Yunhao Tang, Shipra Agrawal, Yuri Faenza
Safe Reinforcement Learning in Constrained Markov Decision Processes Akifumi Wachi, Yanan Sui
Layered Sampling for Robust Optimization Problems Hu Ding, Zixiu Wang
Learning to Encode Position for Transformer with Continuous Dynamical Model Xuanqing Liu, Hsiang-Fu Yu, Inderjit Dhillon, Cho-Jui Hsieh
Do RNN and LSTM have Long Memory? Jingyu Zhao, Feiqing Huang, Jia Lv, Yanjie Duan, Zhen Qin, Guodong Li, Guangjian Tian


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