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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)

Agnostic Multi-Robust Learning using ERM AISTATS 2024
GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models AISTATS 2024
Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent AISTATS 2024
Backward Filtering Forward Deciding in Linear Non-Gaussian State Space Models AISTATS 2024
MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization AISTATS 2024
A Doubly Robust Approach to Sparse Reinforcement Learning AISTATS 2024
Stochastic Approximation with Biased MCMC for Expectation Maximization AISTATS 2024
EM for Mixture of Linear Regression with Clustered Data AISTATS 2024
Analysis of Kernel Mirror Prox for Measure Optimization AISTATS 2024
Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity AISTATS 2024
Approximate Leave-one-out Cross Validation for Regression with $\ell_1$ Regularizers AISTATS 2024
Online Learning in Contextual Second-Price Pay-Per-Click Auctions AISTATS 2024
Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data AISTATS 2024
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels AISTATS 2024
Mixed variational flows for discrete variables AISTATS 2024
Optimal Zero-Shot Detector for Multi-Armed Attacks AISTATS 2024
Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective AISTATS 2024
Conformal Contextual Robust Optimization AISTATS 2024
Learning Adaptive Kernels for Statistical Independence Tests AISTATS 2024
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow AISTATS 2024
Bayesian Online Learning for Consensus Prediction AISTATS 2024
Surrogate Bayesian Networks for Approximating Evolutionary Games AISTATS 2024
BlockBoost: Scalable and Efficient Blocking through Boosting AISTATS 2024
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits AISTATS 2024
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo AISTATS 2024