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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)

A Field Guide for Pacing Budget and ROS Constraints ICML 2024 A Fixed-Parameter Tractable Algorithm for Counting Markov Equivalence Classes with the Same Skeleton AAAI 2024 A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024 AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models ACL 2024 AFPQ: Asymmetric Floating Point Quantization for LLMs ACL 2024 A Framework for Centralized Traffic Routing in Urban Areas IJCAI 2024 A Framework for Data-Driven Explainability in Mathematical Optimization AAAI 2024 A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024 A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks ICML 2024 A Frustratingly Simple Decoding Method for Neural Text Generation COLING 2024 A General and Efficient Training for Transformer via Token Expansion CVPR 2024 A General Framework for Sequential Decision-Making under Adaptivity Constraints ICML 2024 A General Framework for the Analysis of Kernel-based Tests JMLR 2024 A generalized neural tangent kernel for surrogate gradient learning NeurIPS 2024 A General Search-Based Framework for Generating Textual Counterfactual Explanations AAAI 2024 A General Theoretical Paradigm to Understand Learning from Human Preferences AISTATS 2024 A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts ICML 2024 AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents NeurIPS 2024 A Geometric Explanation of the Likelihood OOD Detection Paradox ICML 2024 A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models NeurIPS 2024 Aggregation of Continuous Preferences in One Dimension IJCAI 2024 Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge AAAI 2024 A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization NeurIPS 2024 Agnostic Active Learning of Single Index Models with Linear Sample Complexity COLT 2024 Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms ICML 2024