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)

SphereFlow: 6 DoF Scene Flow from RGB-D Pairs CVPR 2014 Spherical Hamiltonian Monte Carlo for Constrained Target Distributions ICML 2014 Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery ICML 2014 Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance ICML 2014 Statistical analysis of stochastic gradient methods for generalized linear models ICML 2014 Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting ICML 2014 Stereo under Sequential Optimal Sampling: A Statistical Analysis Framework for Search Space Reduction CVPR 2014 Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers ICML 2014 Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm NeurIPS 2014 Stochastic Gradient Hamiltonian Monte Carlo ICML 2014 Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices ICML 2014 Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards NeurIPS 2014 Stochastic Network Design in Bidirected Trees NeurIPS 2014 Stochastic Proximal Gradient Descent with Acceleration Techniques NeurIPS 2014 Stochastic Regret Minimization via Thompson Sampling COLT 2014 Stochastic Variational Inference for Bayesian Time Series Models ICML 2014 Stochastic variational inference for hidden Markov models NeurIPS 2014 StoryGraphs: Visualizing Character Interactions as a Timeline CVPR 2014 Streaming, Memory Limited Algorithms for Community Detection NeurIPS 2014 Structured Prediction via Output Space Search JMLR 2014 Structured Recurrent Temporal Restricted Boltzmann Machines ICML 2014 Structure learning of antiferromagnetic Ising models NeurIPS 2014 Structure Regularization for Structured Prediction NeurIPS 2014 Submodular Attribute Selection for Action Recognition in Video NeurIPS 2014 Submodularization for Binary Pairwise Energies CVPR 2014