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)

Approximate Information Tests on Statistical Submanifolds JMLR 2024 Approximate Leave-one-out Cross Validation for Regression with ℓ_1 Regularizers AISTATS 2024 Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering NeurIPS 2024 Approximately Piecewise E(3) Equivariant Point Networks ICLR 2024 Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo WACV 2024 Approximating mutual information of high-dimensional variables using learned representations NeurIPS 2024 Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization ICLR 2024 Approximating the Top Eigenvector in Random Order Streams NeurIPS 2024 Approximation-Aware Bayesian Optimization NeurIPS 2024 Approximation Rate of the Transformer Architecture for Sequence Modeling NeurIPS 2024 A Precise Characterization of SGD Stability Using Loss Surface Geometry ICLR 2024 A Primal-Dual Algorithm for Hybrid Federated Learning AAAI 2024 A Primal-Dual Approach to Solving Variational Inequalities with General Constraints ICLR 2024 A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints NeurIPS 2024 A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement Learning AISTATS 2024 A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model ICLR 2024 A projected semismooth Newton method for a class of nonconvex composite programs with strong prox-regularity JMLR 2024 A Proposal for Scaling the Scaling Laws EACL 2024 A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness NeurIPS 2024 A Provable Decision Rule for Out-of-Distribution Detection ICML 2024 A Provably Accurate Randomized Sampling Algorithm for Logistic Regression AAAI 2024 A Quadratic Synchronization Rule for Distributed Deep Learning ICLR 2024 A Quantum-Inspired Matching Network with Linguistic Theories for Metaphor Detection COLING 2024 A Rainbow in Deep Network Black Boxes JMLR 2024 A Random Projection Approach to Personalized Federated Learning: Enhancing Communication Efficiency, Robustness, and Fairness JMLR 2024