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Theory

4,950 papers

Papers per year

Papers

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms NIPS 2022
Identifiability of deep generative models without auxiliary information NIPS 2022
On Batch Teaching with Sample Complexity Bounded by VCD NIPS 2022
The Hessian Screening Rule NIPS 2022
Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality NIPS 2022
No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit NIPS 2022
On the Importance of Gradient Norm in PAC-Bayesian Bounds NIPS 2022
On the Identifiability of Nonlinear ICA: Sparsity and Beyond NIPS 2022
Robust Testing in High-Dimensional Sparse Models NIPS 2022
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets NIPS 2022
Function Classes for Identifiable Nonlinear Independent Component Analysis NIPS 2022
coVariance Neural Networks NIPS 2022
On the non-universality of deep learning: quantifying the cost of symmetry NIPS 2022
A Single-timescale Analysis for Stochastic Approximation with Multiple Coupled Sequences NIPS 2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference NIPS 2022
When Combinatorial Thompson Sampling meets Approximation Regret NIPS 2022
The Role of Baselines in Policy Gradient Optimization NIPS 2022
If Influence Functions are the Answer, Then What is the Question? NIPS 2022
Reproducibility in Optimization: Theoretical Framework and Limits NIPS 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? NIPS 2022
Benefits of Permutation-Equivariance in Auction Mechanisms NIPS 2022
Optimal Binary Classification Beyond Accuracy NIPS 2022
On Scrambling Phenomena for Randomly Initialized Recurrent Networks NIPS 2022
Most Activation Functions Can Win the Lottery Without Excessive Depth NIPS 2022
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression NIPS 2022