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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)

Understanding MCMC Dynamics as Flows on the Wasserstein Space ICML 2019 Understanding Persuasion Cascades in Online Product Rating Systems AAAI 2019 Understanding Priors in Bayesian Neural Networks at the Unit Level ICML 2019 Understanding Sparse JL for Feature Hashing NeurIPS 2019 Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets ICLR 2019 Understanding the Disharmony Between Dropout and Batch Normalization by Variance Shift CVPR 2019 Understanding the Impact of Entropy on Policy Optimization ICML 2019 Understanding the Role of Momentum in Stochastic Gradient Methods NeurIPS 2019 Understanding Undesirable Word Embedding Associations ACL 2019 Understanding VAEs in Fisher-Shannon Plane AAAI 2019 Unidirectional Neural Network Architectures for End-to-End Automatic Speech Recognition Interspeech 2019 Unified Sample-Optimal Property Estimation in Near-Linear Time NeurIPS 2019 Uniform concentration and symmetrization for weak interactions COLT 2019 Uniform convergence may be unable to explain generalization in deep learning NeurIPS 2019 Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension ICML 2019 Uniform regret bounds over R^d for the sequential linear regression problem with the square loss ALT 2019 Unifying Orthogonal Monte Carlo Methods ICML 2019 Unifying the Stochastic and the Adversarial Bandits with Knapsack IJCAI 2019 Universal Approximation of Input-Output Maps by Temporal Convolutional Nets NeurIPS 2019 Universal Approximation Property and Equivalence of Stochastic Computing-Based Neural Networks and Binary Neural Networks AAAI 2019 Universal Boosting Variational Inference NeurIPS 2019 Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit AISTATS 2019 Universal Invariant and Equivariant Graph Neural Networks NeurIPS 2019 Universality and individuality in neural dynamics across large populations of recurrent networks NeurIPS 2019 Universality in Learning from Linear Measurements NeurIPS 2019