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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)

Differentially Private Learning of Geometric Concepts ICML 2019 Differentially Private Markov Chain Monte Carlo NeurIPS 2019 Differentially Private Online Submodular Minimization AISTATS 2019 Differentially Private Optimal Transport: Application to Domain Adaptation IJCAI 2019 Differentiated Distribution Recovery for Neural Text Generation AAAI 2019 Diffusion Scattering Transforms on Graphs ICLR 2019 Dimensionality reduction: theoretical perspective on practical measures NeurIPS 2019 Dimension-Free Bounds for Low-Precision Training NeurIPS 2019 Dimension-Free Error Bounds from Random Projections AAAI 2019 Dimensions of Prosodic Prominence in an Attractor Model Interspeech 2019 Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning ICML 2019 DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization NeurIPS 2019 Direct Acceleration of SAGA using Sampled Negative Momentum AISTATS 2019 Direct Estimation of Differential Functional Graphical Models NeurIPS 2019 Direct Training for Spiking Neural Networks: Faster, Larger, Better AAAI 2019 Dirichlet Multinomial Mixture with Variational Manifold Regularization: Topic Modeling over Short Texts AAAI 2019 Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm COLT 2019 Discovering Conditionally Salient Features with Statistical Guarantees ICML 2019 Discovering Neural Wirings NeurIPS 2019 Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms IJCAI 2019 Discovering Temporal Patterns from Insurance Interaction Data AAAI 2019 Discovery of Natural Language Concepts in Individual Units of CNNs ICLR 2019 Discrepancy, Coresets, and Sketches in Machine Learning COLT 2019 Discrimination in Online Markets: Effects of Social Bias on Learning from Reviews and Policy Design NeurIPS 2019 Discriminative Topic Modeling with Logistic LDA NeurIPS 2019