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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)

Alleviating Privacy Attacks via Causal Learning ICML 2020 Alleviation of Gradient Exploding in GANs: Fake Can Be Real CVPR 2020 All in One Bad Weather Removal Using Architectural Search CVPR 2020 All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference ICML 2020 All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation NeurIPS 2020 All your loss are belong to Bayes NeurIPS 2020 Almost No News on the Complexity of MAP in Bayesian Networks PGM 2020 Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition NeurIPS 2020 Almost Surely Stable Deep Dynamics NeurIPS 2020 Almost Tune-Free Variance Reduction ICML 2020 A Locally Linear Procedure for Word Translation COLING 2020 A Logic of Directions IJCAI 2020 A Low Complexity Algorithm with O(√T) Regret and O(1) Constraint Violations for Online Convex Optimization with Long Term Constraints JMLR 2020 Altruism in Coalition Formation Games IJCAI 2020 A Lyapunov analysis for accelerated gradient methods: from deterministic to stochastic case AISTATS 2020 AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC AISTATS 2020 A mathematical model for automatic differentiation in machine learning NeurIPS 2020 A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices NeurIPS 2020 A matter of framing: The impact of linguistic formalism on probing results EMNLP 2020 A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth ICML 2020 A Model-Driven Deep Neural Network for Single Image Rain Removal CVPR 2020 Amortised Learning by Wake-Sleep ICML 2020 Amortized Bayesian Optimization over Discrete Spaces UAI 2020 Amortized Inference of Variational Bounds for Learning Noisy-OR AISTATS 2020 Amortized Nesterov’s Momentum: A Robust Momentum and Its Application to Deep Learning UAI 2020