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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)

A General Framework for Constrained Bayesian Optimization using Information-based Search JMLR 2016 A General Optimization Framework for Multi-Document Summarization Using Genetic Algorithms and Swarm Intelligence COLING 2016 A Gibbs Sampler for Learning DAGs JMLR 2016 Agnostic Estimation for Misspecified Phase Retrieval Models NeurIPS 2016 A Guide to Learning Arithmetic Circuits COLT 2016 A Hybrid Causal Search Algorithm for Latent Variable Models PGM 2016 A Hybrid Deep Learning Architecture for Sentiment Analysis COLING 2016 A Kernelized Stein Discrepancy for Goodness-of-fit Tests ICML 2016 A Kernel Test of Goodness of Fit ICML 2016 A Kronecker-factored approximate Fisher matrix for convolution layers ICML 2016 A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning AISTATS 2016 Algorithms and matching lower bounds for approximately-convex optimization NeurIPS 2016 Algorithms for Optimizing the Ratio of Submodular Functions ICML 2016 A Light Touch for Heavily Constrained SGD COLT 2016 A Linearly-Convergent Stochastic L-BFGS Algorithm AISTATS 2016 Altruistic Scheduling in Multi-Resource Clusters OSDI 2016 A Minimax Approach to Supervised Learning NeurIPS 2016 A Multi-Batch L-BFGS Method for Machine Learning NeurIPS 2016 A Multi-step Inertial Forward-Backward Splitting Method for Non-convex Optimization NeurIPS 2016 An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits COLT 2016 Analysis of Deep Neural Networks with Extended Data Jacobian Matrix ICML 2016 Analysis of Speaker Recognition Systems in Realistic Scenarios of the SITW 2016 Challenge Interspeech 2016 Analytical Assessment of Dual-Stream Merging for Noise-Robust ASR Interspeech 2016 Analyzing Classifiers: Fisher Vectors and Deep Neural Networks CVPR 2016 Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm NeurIPS 2016