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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 Translations via Matrix Completion EMNLP 2017 Learning Unknown Markov Decision Processes: A Thompson Sampling Approach NeurIPS 2017 Learning User Dependencies for Recommendation IJCAI 2017 Learning with Average Top-k Loss NeurIPS 2017 Learning with Feature Evolvable Streams NeurIPS 2017 Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons COLT 2017 Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix ACL 2017 Least-Squares Log-Density Gradient Clustering for Riemannian Manifolds AISTATS 2017 Less than a Single Pass: Stochastically Controlled Stochastic Gradient AISTATS 2017 Let It Flow: Resilient Asymmetric Load Balancing with Flowlet Switching NSDI 2017 Leveraging Node Attributes for Incomplete Relational Data ICML 2017 Lexicalized Reordering for Left-to-Right Hierarchical Phrase-based Translation EACL 2017 Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search ACL 2017 Lexical Sememe Prediction via Word Embeddings and Matrix Factorization IJCAI 2017 LightGBM: A Highly Efficient Gradient Boosting Decision Tree NeurIPS 2017 Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization NeurIPS 2017 Limits of End-to-End Learning ACML 2017 Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls NeurIPS 2017 Linear Convergence of Stochastic Frank Wolfe Variants AISTATS 2017 Linearly constrained Gaussian processes NeurIPS 2017 Linear regression without correspondence NeurIPS 2017 Linear Thompson Sampling Revisited AISTATS 2017 Linear Time Computation of Moments in Sum-Product Networks NeurIPS 2017 Linking Image and Text With 2-Way Nets CVPR 2017 Linking Micro Event History to Macro Prediction in Point Process Models AISTATS 2017