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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)

Learning What to Defer for Maximum Independent Sets ICML 2020 Learning with Differentiable Pertubed Optimizers NeurIPS 2020 Learning with Feature and Distribution Evolvable Streams ICML 2020 Learning with Fenchel-Young losses JMLR 2020 Learning with Good Feature Representations in Bandits and in RL with a Generative Model ICML 2020 Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data IJCAI 2020 Learning with Multiple Complementary Labels ICML 2020 Learning with Operator-valued Kernels in Reproducing Kernel Krein Spaces NeurIPS 2020 Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions NeurIPS 2020 Learning With Subquadratic Regularization : A Primal-Dual Approach IJCAI 2020 Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium COLT 2020 Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition CVPR 2020 Learn with Noisy Data via Unsupervised Loss Correction for Weakly Supervised Reading Comprehension COLING 2020 Least General Generalizations in Description Logic: Verification and Existence AAAI 2020 Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NeurIPS 2020 Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data AISTATS 2020 LEEP: A New Measure to Evaluate Transferability of Learned Representations ICML 2020 Less Is Better: Unweighted Data Subsampling via Influence Function AAAI 2020 Leverage Score Sampling for Faster Accelerated Regression and ERM ALT 2020 Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning NeurIPS 2020 Leveraging Discourse Rewards for Document-Level Neural Machine Translation COLING 2020 Leveraging Document-Level Label Consistency for Named Entity Recognition IJCAI 2020 Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-based Algorithms NeurIPS 2020 Lexicalization of Probabilistic Linear Context-free Rewriting Systems ACL 2020 LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud Based Deep Networks CVPR 2020