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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)

Generalized equivalences between subsampling and ridge regularization NIPS 2023
Core-sets for Fair and Diverse Data Summarization NIPS 2023
Energy-Efficient Scheduling with Predictions NIPS 2023
DISCS: A Benchmark for Discrete Sampling NIPS 2023
Learning Cuts via Enumeration Oracles NIPS 2023
On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds NIPS 2023
Strategic Apple Tasting NIPS 2023
A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance NIPS 2023
LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees NIPS 2023
SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization NIPS 2023
CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure AUTOML 2023
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization AUTOML 2023
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts AUTOML 2023
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization AUTOML 2023
Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection AUTOML 2023
Stealthy Terrain-Aware Multi-Agent Active Search CORL 2023
Online Learning for Obstacle Avoidance CORL 2023
Online Model Adaptation with Feedforward Compensation CORL 2023
User-Controllable Arbitrary Style Transfer via Entropy Regularization AAAI 2023
Fast Fluid Simulation via Dynamic Multi-Scale Gridding AAAI 2023
A Learnable Radial Basis Positional Embedding for Coordinate-MLPs AAAI 2023
Siamese-Discriminant Deep Reinforcement Learning for Solving Jigsaw Puzzles with Large Eroded Gaps AAAI 2023
Learning Fractals by Gradient Descent AAAI 2023
Learnable Blur Kernel for Single-Image Defocus Deblurring in the Wild AAAI 2023
IKOL: Inverse Kinematics Optimization Layer for 3D Human Pose and Shape Estimation via Gauss-Newton Differentiation AAAI 2023