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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)

Concentration analysis of multivariate elliptic diffusions JMLR 2023 Concept Gradient: Concept-based Interpretation Without Linear Assumption ICLR 2023 Concurrent Shuffle Differential Privacy Under Continual Observation ICML 2023 ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding NeurIPS 2023 Conditional independence testing under misspecified inductive biases NeurIPS 2023 Conditionally Strongly Log-Concave Generative Models ICML 2023 Conditional Matrix Flows for Gaussian Graphical Models NeurIPS 2023 Conditional score-based diffusion models for Bayesian inference in infinite dimensions NeurIPS 2023 Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models ICML 2023 Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation ICML 2023 Confidence and Uncertainty Assessment for Distributional Random Forests JMLR 2023 Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization CVPR 2023 Confidence Estimation Using Unlabeled Data ICLR 2023 Confidence Intervals and Hypothesis Testing for High-dimensional Quantile Regression: Convolution Smoothing and Debiasing JMLR 2023 Conflicting Interactions among Protection Mechanisms for Machine Learning Models AAAI 2023 Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queries JMLR 2023 Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping ICML 2023 Conformalized matrix completion NeurIPS 2023 Conformalized Unconditional Quantile Regression AISTATS 2023 Conformal Meta-learners for Predictive Inference of Individual Treatment Effects NeurIPS 2023 Conformal Nucleus Sampling ACL 2023 Conformal Off-Policy Prediction AISTATS 2023 Conformal Prediction for Federated Uncertainty Quantification Under Label Shift ICML 2023 Conformal Prediction for Time Series with Modern Hopfield Networks NeurIPS 2023 Conformal Prediction Sets for Ordinal Classification NeurIPS 2023