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Optimization

14,850 papers (55 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Continuous Optimization (4,424) Stochastic Methods (2,991) Combinatorial Optimization (2,615) Online Algorithms (2,404) Optimization (1,521) Game Theory (1,046) Convex Optimization (864) Discrete Optimization (721) Optimal Transport (474) Sparse Optimization (416) Optimal Control (271) Global Optimization (200) Non-Convex Optimization (182) Distributed Learning (164) Approximation Algorithms (162) Multi-Objective Optimization (151) Distributed Optimization (136) Bayesian Optimization (132) Theory (109) Compressed Sensing (102) Algorithms (89) Robust Optimization (86) Submodular Optimization (77) Kernel Methods (75) Evolutionary Algorithm (72) Linear Programming (54) Tensor Decomposition (48) Bilevel Optimization (42) Integer Programming (38) Matrix Completion (33) Algorithm (21) Regularization (11)

Papers per year

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16
133
440
1,353
1,441
2000
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Papers (including subtopics)

Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory ICML 2024 Practical Shuffle Coding NeurIPS 2024 PRACT: Optimizing Principled Reasoning and Acting of LLM Agent CoNLL 2024 Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg ICML 2024 Predictive Linear Online Tracking for Unknown Targets ICML 2024 Preference-Aware Constrained Multi-Objective Bayesian Optimization (Student Abstract) AAAI 2024 Preferred Reasoning in ABA by Cycle-Breaking IJCAI 2024 Pricing and Competition for Generative AI NeurIPS 2024 Pricing with Contextual Elasticity and Heteroscedastic Valuation ICML 2024 Principal-Agent Reward Shaping in MDPs AAAI 2024 Principled Preferential Bayesian Optimization ICML 2024 PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses ICML 2024 Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions AAAI 2024 Privacy-Aware Randomized Quantization via Linear Programming UAI 2024 Privacy Preserving Adaptive Experiment Design ICML 2024 Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent ICML 2024 Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry NeurIPS 2024 Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems ICML 2024 Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust NeurIPS 2024 Private Geometric Median NeurIPS 2024 Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation ICML 2024 Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses ICML 2024 Privately Learning Smooth Distributions on the Hypercube by Projections ICML 2024 Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions NeurIPS 2024 Private Truly-Everlasting Robust-Prediction ICML 2024