Papers
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks
Spencer Frei, Yuan Cao, Quanquan Gu
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
Zhiqi Bu, Jason Klusowski, Cynthia Rush et al.
Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors
Gauri Jagatap, Chinmay Hegde
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations
Fenglin Liu, Yuanxin Liu, Xuancheng Ren et al.
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning
Zhihui Zhu, Tianyu Ding, Daniel Robinson et al.
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Sulaiman Alghunaim, Kun Yuan, Ali H. Sayed
A Little Is Enough: Circumventing Defenses For Distributed Learning
Gilad Baruch, Moran Baruch, Yoav Goldberg
Alleviating Label Switching with Optimal Transport
Pierre Monteiller, Sebastian Claici, Edward Chien et al.
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model
Andrea Zanette, Mykel J Kochenderfer, Emma Brunskill
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off
Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry
A Meta-Analysis of Overfitting in Machine Learning
Rebecca Roelofs, Vaishaal Shankar, Benjamin Recht et al.
A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning
Francisco Garcia, Philip S. Thomas
A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation
Xueying Bai, Jian Guan, Hongning Wang
A Model to Search for Synthesizable Molecules
John Bradshaw, Brooks Paige, Matt J Kusner et al.
Amortized Bethe Free Energy Minimization for Learning MRFs
Sam Wiseman, Yoon Kim
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
Hadrien Hendrikx, Francis Bach, Laurent Massoulié
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
Wei Deng, Xiao Zhang, Faming Liang et al.
An adaptive Mirror-Prox method for variational inequalities with singular operators
Kimon Antonakopoulos, Veronica Belmega, Panayotis Mertikopoulos
An adaptive nearest neighbor rule for classification
Akshay Balsubramani, Sanjoy Dasgupta, yoav Freund et al.
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan Kulkarni et al.
An Algorithm to Learn Polytree Networks with Hidden Nodes
Firoozeh Sepehr, Donatello Materassi
A Necessary and Sufficient Stability Notion for Adaptive Generalization
Moshe Shenfeld, Katrina Ligett
An Embedding Framework for Consistent Polyhedral Surrogates
Jessica Finocchiaro, Rafael Frongillo, Bo Waggoner
A neurally plausible model for online recognition and postdiction in a dynamical environment
Li Kevin Wenliang, Maneesh Sahani
A neurally plausible model learns successor representations in partially observable environments
Eszter Vértes, Maneesh Sahani