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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)

Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations COLT 2023 Private Distribution Learning with Public Data: The View from Sample Compression NeurIPS 2023 Private Federated Frequency Estimation: Adapting to the Hardness of the Instance NeurIPS 2023 Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses ICLR 2023 Private Non-Convex Federated Learning Without a Trusted Server AISTATS 2023 Private Statistical Estimation of Many Quantiles ICML 2023 Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks NeurIPS 2023 Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses ALT 2023 Probabilistically robust conformal prediction UAI 2023 Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse ICLR 2023 Probabilistic Attention-to-Influence Neural Models for Event Sequences ICML 2023 Probabilistic circuits that know what they don’t know UAI 2023 Probabilistic Conformal Prediction Using Conditional Random Samples AISTATS 2023 Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs ICML 2023 Probabilistic Exponential Integrators NeurIPS 2023 Probabilistic Generalization of Backdoor Trees with Application to SAT AAAI 2023 Probabilistic Inference in Reinforcement Learning Done Right NeurIPS 2023 Probabilistic Invariance for Gaussian Process State Space Models L4DC 2023 Probabilistic Invariant Learning with Randomized Linear Classifiers NeurIPS 2023 Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs NeurIPS 2023 Probabilistic Programs as an Action Description Language AAAI 2023 Probabilistic Querying of Continuous-Time Event Sequences AISTATS 2023 Probabilistic Reasoning and Learning for Trustworthy AI AAAI 2023 Probabilistic Safeguard for Reinforcement Learning Using Safety Index Guided Gaussian Process Models L4DC 2023 Probabilistic Shape Models of Anatomy Directly from Images AAAI 2023