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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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Papers (including subtopics)

Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization JMLR 2024 Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems. ICLR 2024 Monte Carlo Tree Search based Space Transfer for Black Box Optimization NeurIPS 2024 Monte Carlo Tree Search in the Presence of Transition Uncertainty AAAI 2024 Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-Loop and Hessian-Free Solution Strategy ICML 2024 More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning ICML 2024 More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms ICML 2024 More Insightful Feedback for Tutoring: Enhancing Generation Mechanisms and Automatic Evaluation EMNLP 2024 More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory ICLR 2024 More Labels or Cases? Assessing Label Variation in Natural Language Inference EACL 2024 More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity JMLR 2024 More Samples or More Prompts? Exploring Effective Few-Shot In-Context Learning for LLMs with In-Context Sampling NAACL 2024 More than Just Statistical Recurrence: Human and Machine Unsupervised Learning of Māori Word Segmentation across Morphological Processes NAACL 2024 MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization EMNLP 2024 MOSEL: Inference Serving Using Dynamic Modality Selection EMNLP 2024 Most Influential Subset Selection: Challenges, Promises, and Beyond NeurIPS 2024 MOTE-NAS: Multi-Objective Training-based Estimate for Efficient Neural Architecture Search NeurIPS 2024 Motion Capture Analysis of Verb and Adjective Types in Austrian Sign Language (ÖGS) COLING 2024 Motor: Enabling Multi-Versioning for Distributed Transactions on Disaggregated Memory OSDI 2024 MPCC++: Model Predictive Contouring Control for Time-Optimal Flight with Safety Constraints RSS 2024 MPC-inspired reinforcement learning for verifiable model-free control L4DC 2024 MQuinE: a Cure for “Z-paradox” in Knowledge Graph Embedding EMNLP 2024 MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs NeurIPS 2024 MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data ICML 2024 MSA-DPCRN: A Multi-Scale Asymmetric Dual-Path Convolution Recurrent Network with Attentional Feature Fusion for Acoustic Echo Cancellation Interspeech 2024