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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)

Examining Citations of Natural Language Processing Literature ACL 2020 ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks NeurIPS 2020 Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data JMLR 2020 Expected Information Maximization: Using the I-Projection for Mixture Density Estimation ICLR 2020 Experimental Design for Optimization of Orthogonal Projection Pursuit Models AAAI 2020 Experimental Evaluation and Development of a Silver-Standard for the MIMIC-III Clinical Coding Dataset ACL 2020 Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms ICML 2020 Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation NeurIPS 2020 Explainable Data Decompositions AAAI 2020 Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions ACL 2020 Explaining Knowledge Distillation by Quantifying the Knowledge CVPR 2020 Explaining Propagators for String Edit Distance Constraints AAAI 2020 Explicit Gradient Learning for Black-Box Optimization ICML 2020 Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation AISTATS 2020 Explicit Regularisation in Gaussian Noise Injections NeurIPS 2020 Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NeurIPS 2020 Exploiting Joint Robustness to Adversarial Perturbations CVPR 2020 Exploiting Model Sparsity in Adaptive MPC: A Compressed Sensing Viewpoint L4DC 2020 Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network IJCAI 2020 Exploiting the Surrogate Gap in Online Multiclass Classification NeurIPS 2020 Exploration by Optimisation in Partial Monitoring COLT 2020 Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits ICML 2020 Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects CoRL 2020 Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling NeurIPS 2020 Exploring End-to-End Differentiable Natural Logic Modeling COLING 2020