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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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2000
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Papers (including subtopics)

Exploiting the Social-Like Prior in Transformer for Visual Reasoning AAAI 2024 EXPLORA: Efficient Exemplar Subset Selection for Complex Reasoning EMNLP 2024 Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring ICML 2024 Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization ICML 2024 Exploration of the Search Space of Gaussian Graphical Models for Paired Data JMLR 2024 Explore 3D Dance Generation via Reward Model from Automatically-Ranked Demonstrations AAAI 2024 Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling ECCV 2024 Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks NeurIPS 2024 Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations NeurIPS 2024 Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation AAAI 2024 Exploring Quantization for Efficient Pre-Training of Transformer Language Models EMNLP 2024 Exploring the cloud of feature interaction scores in a Rashomon set ICLR 2024 Exploring the Complexity of Deep Neural Networks through Functional Equivalence ICML 2024 Exploring the Inefficiency of Heavy Ball as Momentum Parameter Approaches 1 IJCAI 2024 Exploring the Learning Capabilities of Language Models using LEVERWORLDS EMNLP 2024 Exploring the limits of decoder-only models trained on public speech recognition corpora Interspeech 2024 Exploring the Limits of Fine-grained LLM-based Physics Inference via Premise Removal Interventions EMNLP 2024 Exploring the Promise and Limits of Real-Time Recurrent Learning ICLR 2024 Exploring the Relationship between In-Context Learning and Instruction Tuning EMNLP 2024 Exploring the Trade-off Between Model Performance and Explanation Plausibility of Text Classifiers Using Human Rationales NAACL 2024 Exploring the Traditional NMT Model and Large Language Model for Chat Translation EMNLP 2024 Exploring Transformer Extrapolation AAAI 2024 Exploring Very Low-Resource Translation with LLMs: The University of Edinburgh’s Submission to AmericasNLP 2024 Translation Task NAACL 2024 eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling NeurIPS 2024 Exponential Hardness of Optimization from the Locality in Quantum Neural Networks AAAI 2024