Papers
A Novel Method to Solve Neural Knapsack Problems
Duanshun Li, Jing Liu, Dongeun Lee et al.
A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang, Ruomin Huang, Wenjie Liu et al.
A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel P Robinson et al.
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong Ki Kim, Miao Liu, Matthew D Riemer et al.
Approximate Group Fairness for Clustering
Bo Li, Lijun Li, Ankang Sun et al.
Approximating a Distribution Using Weight Queries
Nadav Barak, Sivan Sabato
Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
Marc Finzi, Max Welling, Andrew Gordon Wilson
A Precise Performance Analysis of Support Vector Regression
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
A Proxy Variable View of Shared Confounding
Yixin Wang, David Blei
APS: Active Pretraining with Successor Features
Hao Liu, Pieter Abbeel
A Receptor Skeleton for Capsule Neural Networks
Jintai Chen, Hongyun Yu, Chengde Qian et al.
A Regret Minimization Approach to Iterative Learning Control
Naman Agarwal, Elad Hazan, Anirudha Majumdar et al.
A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
Nikunj Saunshi, Arushi Gupta, Wei Hu
A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance
Minhui Huang, Shiqian Ma, Lifeng Lai
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables
Aleksandar Dimitriev, Mingyuan Zhou
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon, Jeongseop Kim, Hyunseo Park et al.
A Sampling-Based Method for Tensor Ring Decomposition
Osman Asif Malik, Stephen Becker
A Scalable Deterministic Global Optimization Algorithm for Clustering Problems
Kaixun Hua, Mingfei Shi, Yankai Cao
A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples
Christian Kümmerle, Claudio M. Verdun
A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance
Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai et al.
A statistical perspective on distillation
Aditya K Menon, Ankit Singh Rawat, Sashank Reddi et al.