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)

Model-X Sequential Testing for Conditional Independence via Testing by Betting AISTATS 2023
Mixed-Effect Thompson Sampling AISTATS 2023
Mixed Linear Regression via Approximate Message Passing AISTATS 2023
Vector Optimization with Stochastic Bandit Feedback AISTATS 2023
Knowledge Acquisition for Human-In-The-Loop Image Captioning AISTATS 2023
A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning AISTATS 2023
Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General Initialization AISTATS 2023
“Plus/minus the learning rate”: Easy and Scalable Statistical Inference with SGD AISTATS 2023
Fast Computation of Branching Process Transition Probabilities via ADMM AISTATS 2023
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization AISTATS 2023
Robust Linear Regression for General Feature Distribution AISTATS 2023
Fast Block Coordinate Descent for Non-Convex Group Regularizations AISTATS 2023
Nonparametric Indirect Active Learning AISTATS 2023
{PF}$^2$ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization AISTATS 2023
Learning Constrained Structured Spaces with Application to Multi-Graph Matching AISTATS 2023
On the Strategyproofness of the Geometric Median AISTATS 2023
Conformal Off-Policy Prediction AISTATS 2023
Sparse Spectral Bayesian Permanental Process with Generalized Kernel AISTATS 2023
Nearly Optimal Latent State Decoding in Block MDPs AISTATS 2023
Agnostic PAC Learning of $k$-juntas Using $L_2$-Polynomial Regression AISTATS 2023
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group AISTATS 2023
Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems AISTATS 2023
Clustering above Exponential Families with Tempered Exponential Measures AISTATS 2023
Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets AISTATS 2023
Learning Physics-Informed Neural Networks without Stacked Back-propagation AISTATS 2023