Papers
A Dynamical System Perspective for Lipschitz Neural Networks
Laurent Meunier, Blaise J Delattre, Alexandre Araujo et al.
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh X Nguyen, Yonatan Bisk, Hal Daumé Iii
A Functional Information Perspective on Model Interpretation
Itai Gat, Nitay Calderon, Roi Reichart et al.
A General Recipe for Likelihood-free Bayesian Optimization
Jiaming Song, Lantao Yu, Willie Neiswanger et al.
AGNAS: Attention-Guided Micro and Macro-Architecture Search
Zihao Sun, Yu Hu, Shun Lu et al.
Agnostic Learnability of Halfspaces via Logistic Loss
Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi et al.
A Hierarchical Bayesian Approach to Inverse Reinforcement Learning with Symbolic Reward Machines
Weichao Zhou, Wenchao Li
A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs
Lu Bai, Lixin Cui, Hancock Edwin
A Joint Exponential Mechanism For Differentially Private Top-$k$
Jennifer Gillenwater, Matthew Joseph, Andres Munoz et al.
A Langevin-like Sampler for Discrete Distributions
Ruqi Zhang, Xingchao Liu, Qiang Liu
Algorithms for the Communication of Samples
Lucas Theis, Noureldin Y Ahmed
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu et al.
A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving
Luca Carminati, Federico Cacciamani, Marco Ciccone et al.
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes
Chengchun Shi, Masatoshi Uehara, Jiawei Huang et al.
A Modern Self-Referential Weight Matrix That Learns to Modify Itself
Kazuki Irie, Imanol Schlag, Róbert Csordás et al.
A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity
Michinari Momma, Chaosheng Dong, Jia Liu
Analysis of Stochastic Processes through Replay Buffers
Shirli Di-Castro, Shie Mannor, Dotan Di Castro
Analyzing and Mitigating Interference in Neural Architecture Search
Jin Xu, Xu Tan, Kaitao Song et al.
An Analytical Update Rule for General Policy Optimization
Hepeng Li, Nicholas Clavette, Haibo He
Anarchic Federated Learning
Haibo Yang, Xin Zhang, Prashant Khanduri et al.
An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings
Meyer Scetbon, Laurent Meunier, Yaniv Romano
A Natural Actor-Critic Framework for Zero-Sum Markov Games
Ahmet Alacaoglu, Luca Viano, Niao He et al.
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks
Sadegh Farhadkhani, Rachid Guerraoui, Lê Nguyên Hoang et al.
A Neural Tangent Kernel Perspective of GANs
Jean-Yves Franceschi, Emmanuel De Bézenac, Ibrahim Ayed et al.