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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)

ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls NeurIPS 2019 Addressing Failure Prediction by Learning Model Confidence NeurIPS 2019 Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment ICML 2019 A Debiased MDI Feature Importance Measure for Random Forests NeurIPS 2019 A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem CVPR 2019 A Deep Bi-directional Attention Network for Human Motion Recovery IJCAI 2019 A Deep Cascade Model for Multi-Document Reading Comprehension AAAI 2019 ADef: an Iterative Algorithm to Construct Adversarial Deformations ICLR 2019 Ad Hoc Teamwork With Behavior Switching Agents IJCAI 2019 A Differential Volumetric Approach to Multi-View Photometric Stereo ICCV 2019 A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport NeurIPS 2019 A Discrete Hard EM Approach for Weakly Supervised Question Answering EMNLP 2019 ADMMBO: Bayesian Optimization with Unknown Constraints using ADMM JMLR 2019 A Domain Agnostic Measure for Monitoring and Evaluating GANs NeurIPS 2019 A Dual Approach to Verify and Train Deep Networks IJCAI 2019 Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network ICLR 2019 Adversarial Attacks on Graph Neural Networks via Meta Learning ICLR 2019 Adversarial Examples Are a Natural Consequence of Test Error in Noise ICML 2019 Adversarial Examples for Graph Data: Deep Insights into Attack and Defense IJCAI 2019 Adversarial examples from computational constraints ICML 2019 Adversarial Imitation via Variational Inverse Reinforcement Learning ICLR 2019 Adversarial Learning of a Sampler Based on an Unnormalized Distribution AISTATS 2019 Adversarial Online Learning with noise ICML 2019 Adversarial Regularization for End-to-End Robust Speaker Verification Interspeech 2019 Adversarial Variational Optimization of Non-Differentiable Simulators AISTATS 2019