conftrace_

Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

Using Sliced Mutual Information to Study Memorization and Generalization in Deep Neural Networks AISTATS 2023
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation AISTATS 2023
Meta-Uncertainty in Bayesian Model Comparison AISTATS 2023
PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time AISTATS 2023
Entropic Risk Optimization in Discounted MDPs AISTATS 2023
An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization AISTATS 2023
Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision AISTATS 2023
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods AISTATS 2023
Scalable marked point processes for exchangeable and non-exchangeable event sequences AISTATS 2023
Bayesian Variable Selection in a Million Dimensions AISTATS 2023
Gradient-Informed Neural Network Statistical Robustness Estimation AISTATS 2023
A Case of Exponential Convergence Rates for SVM AISTATS 2023
Adaptive Cholesky Gaussian Processes AISTATS 2023
Sample Complexity of Kernel-Based Q-Learning AISTATS 2023
A principled framework for the design and analysis of token algorithms AISTATS 2023
Learning k-qubit Quantum Operators via Pauli Decomposition AISTATS 2023
Semi-Verified PAC Learning from the Crowd AISTATS 2023
On the Capacity Limits of Privileged ERM AISTATS 2023
Bayesian Structure Scores for Probabilistic Circuits AISTATS 2023
Langevin Diffusion Variational Inference AISTATS 2023
Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity AISTATS 2023
Kernel Conditional Moment Constraints for Confounding Robust Inference AISTATS 2023
From Shapley Values to Generalized Additive Models and back AISTATS 2023
Global Convergence of Over-parameterized Deep Equilibrium Models AISTATS 2023
A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space AISTATS 2023