Skip to content
conftrace_

Optimization & Theory

43,292 papers (3 classified directly here)

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

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization JMLR 2024 Optimistic Rates for Learning from Label Proportions COLT 2024 Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes UAI 2024 Optimistic Search: Change Point Estimation for Large-scale Data via Adaptive Logarithmic Queries JMLR 2024 Optimistic Verifiable Training by Controlling Hardware Nondeterminism NeurIPS 2024 Optimization Algorithm Design via Electric Circuits NeurIPS 2024 Optimization-based Causal Estimation from Heterogeneous Environments JMLR 2024 Optimization-based Uncertainty Attribution Via Learning Informative Perturbations ECCV 2024 Optimization Can Learn Johnson Lindenstrauss Embeddings NeurIPS 2024 Optimization Framework for Semi-supervised Attributed Graph Coarsening UAI 2024 Optimization Under Epistemic Uncertainty Using Prediction IJCAI 2024 Optimization without Retraction on the Random Generalized Stiefel Manifold ICML 2024 Optimize & Reduce: A Top-Down Approach for Image Vectorization AAAI 2024 Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs EMNLP 2024 Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems AAAI 2024 Optimizing Automatic Differentiation with Deep Reinforcement Learning NeurIPS 2024 Optimizing Diffusion Noise Can Serve As Universal Motion Priors CVPR 2024 Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs EMNLP 2024 Optimizing Instruction Synthesis: Effective Exploration of Evolutionary Space with Tree Search EMNLP 2024 Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning EMNLP 2024 Optimizing LLM Based Retrieval Augmented Generation Pipelines in the Financial Domain NAACL 2024 Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes AAAI 2024 Optimizing Noise for f-Differential Privacy via Anti-Concentration and Stochastic Dominance JMLR 2024 Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition NeurIPS 2024 Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits NeurIPS 2024