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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)

The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits AISTATS 2020 The Gradient Complexity of Linear Regression COLT 2020 The HSIC Bottleneck: Deep Learning without Back-Propagation AAAI 2020 The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent ICML 2020 The impact of preprint servers in the formation of novel ideas EMNLP 2020 The Implications of Local Correlation on Learning Some Deep Functions NeurIPS 2020 The Implicit and Explicit Regularization Effects of Dropout ICML 2020 The Implicit Bias of Depth: How Incremental Learning Drives Generalization ICLR 2020 The Implicit Regularization of Stochastic Gradient Flow for Least Squares ICML 2020 The Importance of the Test Set Size in Quantification Assessment IJCAI 2020 The Indian Chefs Process UAI 2020 The Influence of Shape Constraints on the Thresholding Bandit Problem COLT 2020 The intriguing role of module criticality in the generalization of deep networks ICLR 2020 The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation ICML 2020 The Kalai-Smorodinsky solution for many-objective Bayesian optimization JMLR 2020 The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020 The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning NeurIPS 2020 The Lottery Ticket Hypothesis for Pre-trained BERT Networks NeurIPS 2020 The Many Shapley Values for Model Explanation ICML 2020 The Mean-Squared Error of Double Q-Learning NeurIPS 2020 Themis: Fair and Efficient GPU Cluster Scheduling NSDI 2020 The MSP-Conversation Corpus Interspeech 2020 The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization ICML 2020 The Non-IID Data Quagmire of Decentralized Machine Learning ICML 2020 The Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative due to the Implicit Ridge Regularization JMLR 2020