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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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'25

Papers (including subtopics)

Explainable Neural Networks with Guarantee: A Sparse Estimation Approach AAAI 2025 Explaining Black-box Model Predictions via Two-level Nested Feature Attributions with Consistency Property IJCAI 2025 Explain It as Simple as Possible, but No Simpler – Explanation via Model Simplification for Addressing Inferential Gap (Abstract Reprint) IJCAI 2025 Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs ACL 2025 Explicit and Implicit Examinee-Question Relation Exploiting for Efficient Computerized Adaptive Testing AAAI 2025 Explicit and Implicit Graduated Optimization in Deep Neural Networks AAAI 2025 Explicit Bayesian Inference to Uncover the Latent Themes of Large Language Models ACL 2025 Explicit Preference Optimization: No Need for an Implicit Reward Model ICML 2025 Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning AAAI 2025 Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning L4DC 2025 Exploiting Curvature in Online Convex Optimization with Delayed Feedback ICML 2025 Exploiting Edited Large Language Models as General Scientific Optimizers NAACL 2025 Exploiting Hidden Symmetry to Improve Objective Perturbation for DP Linear Learners with a Nonsmooth L1-Norm ICLR 2025 Exploiting Position Information in Convolutional Kernels for Structural Re-parameterization IJCAI 2025 Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization ICML 2025 Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank ICLR 2025 Exploiting the Index Gradients for Optimization-Based Jailbreaking on Large Language Models COLING 2025 Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF ICLR 2025 Exploring and Controlling Diversity in LLM-Agent Conversation EMNLP 2025 Exploring Backdoor Vulnerabilities of Chat Models COLING 2025 Exploring channel distinguishability in local neighborhoods of the model space in quantum neural networks ICLR 2025 Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning ICML 2025 Exploring Equity of Climate Policies Using Multi-Agent Multi-Objective Reinforcement Learning IJCAI 2025 Exploring Hybrid Sampling Inference for Aspect-based Sentiment Analysis NAACL 2025 Exploring Learning Complexity for Efficient Downstream Dataset Pruning ICLR 2025