Papers
Learning a Universal Template for Few-shot Dataset Generalization
Eleni Triantafillou, Hugo Larochelle, Richard Zemel et al.
Learning Binary Decision Trees by Argmin Differentiation
Valentina Zantedeschi, Matt Kusner, Vlad Niculae
Learning Bounds for Open-Set Learning
Zhen Fang, Jie Lu, Anjin Liu et al.
Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister et al.
Learning Curves for Analysis of Deep Networks
Derek Hoiem, Tanmay Gupta, Zhizhong Li et al.
Learning Deep Neural Networks under Agnostic Corrupted Supervision
Boyang Liu, Mengying Sun, Ding Wang et al.
Learning de-identified representations of prosody from raw audio
Jack Weston, Raphael Lenain, Udeepa Meepegama et al.
Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi et al.
Learning Diverse-Structured Networks for Adversarial Robustness
Xuefeng Du, Jingfeng Zhang, Bo Han et al.
Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Claire Glanois, Umer Siddique et al.
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