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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)

Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers ECCV 2024 Tight Bounds for Learning RUMs from Small Slates NeurIPS 2024 Tight Bounds for Local Glivenko-Cantelli ALT 2024 Tight bounds for maximum ℓ_1-margin classifiers ALT 2024 Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions JMLR 2024 Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective NeurIPS 2024 Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders ICML 2024 Tight Rates for Bandit Control Beyond Quadratics NeurIPS 2024 Tight Rates in Supervised Outlier Transfer Learning ICLR 2024 Tight Verification of Probabilistic Robustness in Bayesian Neural Networks AISTATS 2024 Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration ICML 2024 Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks ICML 2024 Time–Approximation Trade-Offs for Learning Bayesian Networks PGM 2024 TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models ACL 2024 Time-Constrained Robust MDPs NeurIPS 2024 Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme IJCAI 2024 Time Fairness in Online Knapsack Problems ICLR 2024 Time Machine GPT NAACL 2024 Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning ICML 2024 TLCR: Token-Level Continuous Reward for Fine-grained Reinforcement Learning from Human Feedback ACL 2024 tnGPS: Discovering Unknown Tensor Network Structure Search Algorithms via Large Language Models (LLMs) ICML 2024 To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty NeurIPS 2024 To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO ICML 2024 To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models ICML 2024 To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets ICLR 2024