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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
3,646
5,854
2000
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Papers (including subtopics)

Focused Large Language Models are Stable Many-Shot Learners EMNLP 2024 Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training CVPR 2024 Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds COLT 2024 Forced Exploration in Bandit Problems AAAI 2024 Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective AAAI 2024 Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics ICML 2024 Forgetting Curve: A Reliable Method for Evaluating Memorization Capability for Long-Context Models EMNLP 2024 Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning NeurIPS 2024 Formality is Favored: Unraveling the Learning Preferences of Large Language Models on Data with Conflicting Knowledge EMNLP 2024 Formal Verification of Parameterised Neural-symbolic Multi-agent Systems IJCAI 2024 Fortify the Shortest Stave in Attention: Enhancing Context Awareness of Large Language Models for Effective Tool Use ACL 2024 Fortuna: A Library for Uncertainty Quantification in Deep Learning JMLR 2024 Forward χ^2 Divergence Based Variational Importance Sampling ICLR 2024 Forward-Backward Reasoning in Large Language Models for Mathematical Verification ACL 2024 Forward Learning of Graph Neural Networks ICLR 2024 Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization ICLR 2024 FOSI: Hybrid First and Second Order Optimization ICLR 2024 Foundation Inference Models for Markov Jump Processes NeurIPS 2024 Foundations of Reactive Synthesis for Declarative Process Specifications AAAI 2024 Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization ACL 2024 Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting NeurIPS 2024 Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling JMLR 2024 Fractal Patterns May Illuminate the Success of Next-Token Prediction NeurIPS 2024 FREB-TQA: A Fine-Grained Robustness Evaluation Benchmark for Table Question Answering NAACL 2024 Fréchet Distance for Offline Evaluation of Information Retrieval Systems with Sparse Labels EACL 2024