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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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828
3,646
5,854
2000
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Papers (including subtopics)

DOGE-Train: Discrete Optimization on GPU with End-to-End Training AAAI 2024 Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA EMNLP 2024 Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning NeurIPS 2024 DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models ICLR 2024 Do Language Models Care about Text Quality? Evaluating Web-Crawled Corpora across 11 Languages COLING 2024 Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models EMNLP 2024 Domain Adaptation with Cauchy-Schwarz Divergence UAI 2024 Domain constraints improve risk prediction when outcome data is missing ICLR 2024 Domain Generalisation via Imprecise Learning ICML 2024 Domain Generalisation via Risk Distribution Matching WACV 2024 Domain Generalization by Rejecting Extreme Augmentations WACV 2024 Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts ICLR 2024 Domain Invariant Learning for Gaussian Processes and Bayesian Exploration AAAI 2024 Domain-Weighted Batch Sampling for Neural Dependency Parsing COLING 2024 Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences NeurIPS 2024 Don’t Forget Your Reward Values: Language Model Alignment via Value-based Calibration EMNLP 2024 Don’t Waste Your Time: Early Stopping Cross-Validation AutoML 2024 Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling NeurIPS 2024 DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction NeurIPS 2024 DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution ACL 2024 Double-Bounded Optimal Transport for Advanced Clustering and Classification AAAI 2024 Double-Descent Curves in Neural Networks: A New Perspective Using Gaussian Processes AAAI 2024 DoubleLingo: Causal Estimation with Large Language Models NAACL 2024 Double Momentum Method for Lower-Level Constrained Bilevel Optimization ICML 2024 Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods ICML 2024