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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

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52
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828
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2000
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Papers (including subtopics)

Harmless Overfitting: Using Denoising Autoencoders in Estimation of Distribution Algorithms JMLR 2020 Harmonic Lowering for Accelerating Harmonic Convolution for Audio Signals Interspeech 2020 Harmonious Coexistence of Structured Weight Pruning and Ternarization for Deep Neural Networks AAAI 2020 Harnessing Structures for Value-Based Planning and Reinforcement Learning ICLR 2020 Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks ICLR 2020 Hasyarasa at SemEval-2020 Task 7: Quantifying Humor as Departure from Expectedness SemEval 2020 Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks NeurIPS 2020 HDK: Toward High-Performance Deep-Learning-Based Kirchhoff Analysis AAAI 2020 Hedging in games: Faster convergence of external and swap regrets NeurIPS 2020 Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads OSDI 2020 Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation MLHC 2020 Hierarchical Clustering: A 0.585 Revenue Approximation COLT 2020 Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights NeurIPS 2020 Hierarchically Robust Representation Learning CVPR 2020 Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction IJCAI 2020 Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract) IJCAI 2020 High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds NeurIPS 2020 High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization NeurIPS 2020 High Dimensional Forecasting via Interpretable Vector Autoregression JMLR 2020 High-dimensional Gaussian graphical models on network-linked data JMLR 2020 High-Dimensional Inference for Cluster-Based Graphical Models JMLR 2020 High-dimensional Linear Discriminant Analysis Classifier for Spiked Covariance Model JMLR 2020 High-dimensional Robust Mean Estimation via Gradient Descent ICML 2020 High Dimensional Robust Sparse Regression AISTATS 2020 High-Dimensional Sparse Linear Bandits NeurIPS 2020