Papers
Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch et al.
Learning from History for Byzantine Robust Optimization
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
Learning from Nested Data with Ornstein Auto-Encoders
Youngwon Choi, Sungdong Lee, Joong-Ho Won
Learning from Noisy Labels with No Change to the Training Process
Mingyuan Zhang, Jane Lee, Shivani Agarwal
Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu et al.
Learning Generalized Intersection Over Union for Dense Pixelwise Prediction
Jiaqian Yu, Jingtao Xu, Yiwei Chen et al.
Learning Gradient Fields for Molecular Conformation Generation
Chence Shi, Shitong Luo, Minkai Xu et al.
Learning in Nonzero-Sum Stochastic Games with Potentials
David H Mguni, Yutong Wu, Yali Du et al.
Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason J Miller, Hongda Qiu et al.
Learning Intra-Batch Connections for Deep Metric Learning
Jenny Denise Seidenschwarz, Ismail Elezi, Laura Leal-Taixé
Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell C Horton, Carlos Guestrin et al.
Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks
Ciwan Ceylan, Salla Franzén, Florian T. Pokorny
Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
Yivan Zhang, Gang Niu, Masashi Sugiyama
Learning Online Algorithms with Distributional Advice
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.
Learning Optimal Auctions with Correlated Valuations from Samples
Chunxue Yang, Xiaohui Bei
Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis
Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian et al.
Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Learning Representations by Humans, for Humans
Sophie Hilgard, Nir Rosenfeld, Mahzarin R Banaji et al.
Learning Routines for Effective Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
Chao Chen, Haoyu Geng, Nianzu Yang et al.
Learning Stochastic Behaviour from Aggregate Data
Shaojun Ma, Shu Liu, Hongyuan Zha et al.
Learning Task Informed Abstractions
Xiang Fu, Ge Yang, Pulkit Agrawal et al.
Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
Learning to Price Against a Moving Target
Renato Paes Leme, Balasubramanian Sivan, Yifeng Teng et al.
Learning to Rehearse in Long Sequence Memorization
Zhu Zhang, Chang Zhou, Jianxin Ma et al.