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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
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Papers (including subtopics)

Large-Scale Learning with Less RAM via Randomization ICML 2013 Large-Scale Video Hashing via Structure Learning ICCV 2013 Lasso Screening Rules via Dual Polytope Projection NeurIPS 2013 Latent Data Association: Bayesian Model Selection for Multi-target Tracking ICCV 2013 Latent Maximum Margin Clustering NeurIPS 2013 Layer Depth Denoising and Completion for Structured-Light RGB-D Cameras CVPR 2013 Learning Adaptive Value of Information for Structured Prediction NeurIPS 2013 Learning Chordal Markov Networks by Constraint Satisfaction NeurIPS 2013 Learning Connections in Financial Time Series ICML 2013 Learning Convex QP Relaxations for Structured Prediction ICML 2013 Learning Coupled Feature Spaces for Cross-Modal Matching ICCV 2013 Learning CRFs for Image Parsing with Adaptive Subgradient Descent ICCV 2013 Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions NeurIPS 2013 Learning Feature Selection Dependencies in Multi-task Learning NeurIPS 2013 Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets CVPR 2013 Learning Gaussian Graphical Models with Observed or Latent FVSs NeurIPS 2013 Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching COLT 2013 Learning Hash Functions Using Column Generation ICML 2013 Learning Heteroscedastic Models by Convex Programming under Group Sparsity ICML 2013 Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition NeurIPS 2013 Learning Kernels Using Local Rademacher Complexity NeurIPS 2013 Learning Locally-Adaptive Decision Functions for Person Verification CVPR 2013 Learning Markov Networks With Arithmetic Circuits AISTATS 2013 Learning Maximum Margin Temporal Warping for Action Recognition ICCV 2013 Learning Multi-level Sparse Representations NeurIPS 2013