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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)

Posterior Promoted GAN With Distribution Discriminator for Unsupervised Image Synthesis CVPR 2021 Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods ICML 2021 Post-hoc loss-calibration for Bayesian neural networks UAI 2021 Post-Hoc Uncertainty Calibration for Domain Drift Scenarios CVPR 2021 Post-selection inference with HSIC-Lasso ICML 2021 POT: Python Optimal Transport JMLR 2021 Power Constrained Bandits MLHC 2021 Power of Hints for Online Learning with Movement Costs AISTATS 2021 Practical and Private (Deep) Learning Without Sampling or Shuffling ICML 2021 Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression AAAI 2021 Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design ICLR 2021 Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers NeurIPS 2021 Practical Real Time Recurrent Learning with a Sparse Approximation ICLR 2021 Precise characterization of the prior predictive distribution of deep ReLU networks NeurIPS 2021 Precise Minimax Regret for Logistic Regression with Categorical Feature Values ALT 2021 Precision-based Boosting AAAI 2021 Predicting Deep Neural Network Generalization with Perturbation Response Curves NeurIPS 2021 Predicting Molecular Conformation via Dynamic Graph Score Matching NeurIPS 2021 Predicting Numerals in Natural Language Text Using a Language Model Considering the Quantitative Aspects of Numerals NAACL 2021 Predicting Temporal Performance Drop of Deployed Production Spoken Language Understanding Models Interspeech 2021 Predicting the Success of Domain Adaptation in Text Similarity ACL 2021 Predicting What You Already Know Helps: Provable Self-Supervised Learning NeurIPS 2021 Prediction against a limited adversary JMLR 2021 Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations ICML 2021 Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond JMLR 2021