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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)

Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision EMNLP 2017 Maximum Selection and Ranking under Noisy Comparisons ICML 2017 Maxing and Ranking with Few Assumptions NeurIPS 2017 Max-value Entropy Search for Efficient Bayesian Optimization ICML 2017 Mean Field Residual Networks: On the Edge of Chaos NeurIPS 2017 Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results NeurIPS 2017 Measuring Encoding Efficiency in Swedish and English Language Learner Speech Production Interspeech 2017 Measuring Sample Quality with Kernels ICML 2017 Measuring the Intensity of Attacks in Argumentation Graphs with Shapley Value IJCAI 2017 Measuring Topic Coherence through Optimal Word Buckets EACL 2017 Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch Prox COLT 2017 Memory Efficient Kernel Approximation JMLR 2017 meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting ICML 2017 Meritocratic Fairness for Cross-Population Selection ICML 2017 Metaheuristic Approaches to Lexical Substitution and Simplification EACL 2017 Metrics for Modeling Code-Switching Across Corpora Interspeech 2017 Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems ACML 2017 Minimax Approach to Variable Fidelity Data Interpolation AISTATS 2017 Minimax Density Estimation for Growing Dimension AISTATS 2017 Minimax Estimation of Bandable Precision Matrices NeurIPS 2017 Minimax Estimation of Kernel Mean Embeddings JMLR 2017 Minimax Gaussian Classification & Clustering AISTATS 2017 Minimax Regret Bounds for Reinforcement Learning ICML 2017 Minimizing a Submodular Function from Samples NeurIPS 2017 MIPA: Mutual Information Based Paraphrase Acquisition via Bilingual Pivoting IJCNLP 2017