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Optimization

12,959 papers (55 classified directly here)

Subtopics

Continuous Optimization (3,907) Stochastic Methods (2,788) Combinatorial Optimization (2,409) Online Algorithms (2,192) Optimization (1,207) Game Theory (944) Discrete Optimization (705) Convex Optimization (591) Optimal Transport (369) Sparse Optimization (347) Optimal Control (225) Global Optimization (190) Distributed Learning (157) Multi-Objective Optimization (125) Approximation Algorithms (110) Bayesian Optimization (100) Distributed Optimization (99) Theory (98) Non-Convex Optimization (76) Kernel Methods (73) Compressed Sensing (72) Robust Optimization (70) Evolutionary Algorithm (58) Linear Programming (43) Algorithms (10) Algorithm (10) Integer Programming (9) Submodular Optimization (9) Matrix Completion (8) Bilevel Optimization (8) Tensor Decomposition (6) Regularization (5)

Papers per year

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Papers (including subtopics)

Fast Feature Selection with Fairness Constraints AISTATS 2023
On the Complexity of Representation Learning in Contextual Linear Bandits AISTATS 2023
Revisiting Weighted Strategy for Non-stationary Parametric Bandits AISTATS 2023
No time to waste: practical statistical contact tracing with few low-bit messages AISTATS 2023
Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions AISTATS 2023
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games AISTATS 2023
Online Algorithms with Costly Predictions AISTATS 2023
Adaptive Tuning for Metropolis Adjusted Langevin Trajectories AISTATS 2023
Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits AISTATS 2023
PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery AISTATS 2023
Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data AISTATS 2023
Scalable Unbalanced Sobolev Transport for Measures on a Graph AISTATS 2023
Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints AISTATS 2023
Nonstochastic Contextual Combinatorial Bandits AISTATS 2023
Preferential Subsampling for Stochastic Gradient Langevin Dynamics AISTATS 2023
Federated Learning for Data Streams AISTATS 2023
Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023
Second Order Path Variationals in Non-Stationary Online Learning AISTATS 2023
Active Cost-aware Labeling of Streaming Data AISTATS 2023
Krylov–Bellman boosting: Super-linear policy evaluation in general state spaces AISTATS 2023
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023
Pricing against a Budget and ROI Constrained Buyer AISTATS 2023
Incentive-aware Contextual Pricing with Non-parametric Market Noise AISTATS 2023
Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems AISTATS 2023