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Theory

4,950 papers

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Papers

Perturbation Theory for the Information Bottleneck NIPS 2021
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs NIPS 2021
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators NIPS 2021
Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation NIPS 2021
Surrogate Regret Bounds for Polyhedral Losses NIPS 2021
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model NIPS 2021
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks NIPS 2021
Best-case lower bounds in online learning NIPS 2021
A Comprehensively Tight Analysis of Gradient Descent for PCA NIPS 2021
On Robust Optimal Transport: Computational Complexity and Barycenter Computation NIPS 2021
Learning rule influences recurrent network representations but not attractor structure in decision-making tasks NIPS 2021
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks NIPS 2021
Unifying lower bounds on prediction dimension of convex surrogates NIPS 2021
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method NIPS 2021
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization NIPS 2021
Reinforcement Learning in Newcomblike Environments NIPS 2021
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs NIPS 2021
Does Preprocessing Help Training Over-parameterized Neural Networks? NIPS 2021
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses NIPS 2021
Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication NIPS 2021
Change Point Detection via Multivariate Singular Spectrum Analysis NIPS 2021
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models NIPS 2021
On the Equivalence between Neural Network and Support Vector Machine NIPS 2021
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction NIPS 2021
Analytic Insights into Structure and Rank of Neural Network Hessian Maps NIPS 2021