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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)

Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods ICML 2016 Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests JMLR 2016 Quantized Random Projections and Non-Linear Estimation of Cosine Similarity NeurIPS 2016 Quantum Perceptron Models NeurIPS 2016 Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels JMLR 2016 Random Features for Sparse Signal Classification CVPR 2016 Randomization and The Pernicious Effects of Limited Budgets on Auction Experiments AISTATS 2016 Rapid Update of Multilingual Deep Neural Network for Low-Resource Keyword Search Interspeech 2016 Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices JMLR 2016 Real-Time Tracking of Speakers’ Emotions, States, and Traits on Mobile Platforms Interspeech 2016 Reconstructing Parameters of Spreading Models from Partial Observations NeurIPS 2016 Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates NeurIPS 2016 Recovery guarantee of weighted low-rank approximation via alternating minimization ICML 2016 Recurrent Orthogonal Networks and Long-Memory Tasks ICML 2016 Recursive Decentralized Collaborative Localization for Sparsely Communicating Robots RSS 2016 Refined Error Bounds for Several Learning Algorithms JMLR 2016 Refined Lower Bounds for Adversarial Bandits NeurIPS 2016 Refining Architectures of Deep Convolutional Neural Networks CVPR 2016 Regime Aware Learning PGM 2016 Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks PGM 2016 Regret Analysis of the Finite-Horizon Gittins Index Strategy for Multi-Armed Bandits COLT 2016 Regret Bounds for Non-decomposable Metrics with Missing Labels NeurIPS 2016 Regret of Queueing Bandits NeurIPS 2016 Regularized Nonlinear Acceleration NeurIPS 2016 Reintroducing Credal Networks under Epistemic Irrelevance PGM 2016