Papers
Learning De-biased Representations with Biased Representations
Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun et al.
Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu, Wenkai Xu, Jie Lu et al.
Learning disconnected manifolds: a no GAN’s land
Ugo Tanielian, Thibaut Issenhuth, Elvis Dohmatob et al.
Learning Discrete Structured Representations by Adversarially Maximizing Mutual Information
Karl Stratos, Sam Wiseman
Learning Efficient Multi-agent Communication: An Information Bottleneck Approach
Rundong Wang, Xu He, Runsheng Yu et al.
Learning Factorized Weight Matrix for Joint Filtering
Xiangyu Xu, Yongrui Ma, Wenxiu Sun
Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
Umer Siddique, Paul Weng, Matthieu Zimmer
Learning Flat Latent Manifolds with VAEs
Nutan Chen, Alexej Klushyn, Francesco Ferroni et al.
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints
Cong Shen, Zhiyang Wang, Sofia Villar et al.
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective
Steven Cheng-Xian Li, Benjamin Marlin
Learning Human Objectives by Evaluating Hypothetical Behavior
Siddharth Reddy, Anca Dragan, Sergey Levine et al.
Learning Mixtures of Graphs from Epidemic Cascades
Jessica Hoffmann, Soumya Basu, Surbhi Goel et al.
Learning Near Optimal Policies with Low Inherent Bellman Error
Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer et al.
Learning Opinions in Social Networks
Vincent Conitzer, Debmalya Panigrahi, Hanrui Zhang
Learning Optimal Tree Models under Beam Search
Jingwei Zhuo, Ziru Xu, Wei Dai et al.
Learning Portable Representations for High-Level Planning
Steven James, Benjamin Rosman, George Konidaris
Learning Quadratic Games on Networks
Yan Leng, Xiaowen Dong, Junfeng Wu et al.
Learning Reasoning Strategies in End-to-End Differentiable Proving
Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp et al.
Learning Representations that Support Extrapolation
Taylor Webb, Zachary Dulberg, Steven Frankland et al.
Learning Robot Skills with Temporal Variational Inference
Tanmay Shankar, Abhinav Gupta
Learning Selection Strategies in Buchberger’s Algorithm
Dylan Peifer, Michael Stillman, Daniel Halpern-Leistner
Learning Similarity Metrics for Numerical Simulations
Georg Kohl, Kiwon Um, Nils Thuerey
Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective
Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro
Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion
Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low et al.
Learning the piece-wise constant graph structure of a varying Ising model
Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos et al.