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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)

Learning Attribute-weighted Voter Model over Social Networks ACML 2011 Learning Eigenvectors for Free NeurIPS 2011 Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NeurIPS 2011 Learning large-margin halfspaces with more malicious noise NeurIPS 2011 Learning mixtures of Gaussians with maximum-a-posteriori oracle AISTATS 2011 Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities NeurIPS 2011 Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries NeurIPS 2011 Learning to Locate Relative Outliers ACML 2011 Learning to Search Efficiently in High Dimensions NeurIPS 2011 Learning unbelievable probabilities NeurIPS 2011 Learning with Structured Sparsity JMLR 2011 Learning with the weighted trace-norm under arbitrary sampling distributions NeurIPS 2011 Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation AISTATS 2011 Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation NeurIPS 2011 Linear Submodular Bandits and their Application to Diversified Retrieval NeurIPS 2011 Linear-Time Estimators for Propensity Scores AISTATS 2011 Locally Defined Principal Curves and Surfaces JMLR 2011 Logistic Stick-Breaking Process JMLR 2011 Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas COLT 2011 Lower Bounds for Passive and Active Learning NeurIPS 2011 Manifold Precis: An Annealing Technique for Diverse Sampling of Manifolds NeurIPS 2011 MAP Inference for Bayesian Inverse Reinforcement Learning NeurIPS 2011 Matrix Completion for Multi-label Image Classification NeurIPS 2011 Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation COLT 2011 Maximum Margin Multi-Label Structured Prediction NeurIPS 2011