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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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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints JMLR 2023 Proximal Splitting Adversarial Attack for Semantic Segmentation CVPR 2023 Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization AAAI 2023 ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-Cost Proxies AAAI 2023 Prune Spatio-temporal Tokens by Semantic-aware Temporal Accumulation ICCV 2023 Pruning Pre-trained Language Models with Principled Importance and Self-regularization ACL 2023 Pruning via Sparsity-indexed ODE: a Continuous Sparsity Viewpoint ICML 2023 PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization AutoML 2023 Pseudointelligence: A Unifying Lens on Language Model Evaluation EMNLP 2023 Pseudo-Likelihood Inference NeurIPS 2023 Pseudonorm Approachability and Applications to Regret Minimization ALT 2023 PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer EMNLP 2023 Pushing the Efficiency Limit Using Structured Sparse Convolutions WACV 2023 PyPose: A Library for Robot Learning With Physics-Based Optimization CVPR 2023 Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling ICML 2023 QAP: A Quantum-Inspired Adaptive-Priority-Learning Model for Multimodal Emotion Recognition ACL 2023 Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML AutoML 2023 qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization AISTATS 2023 Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows ICML 2023 QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules NeurIPS 2023 QLoRA: Efficient Finetuning of Quantized LLMs NeurIPS 2023 QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning NeurIPS 2023 QuadAttacK: A Quadratic Programming Approach to Learning Ordered Top-K Adversarial Attacks NeurIPS 2023 Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal COLT 2023 Quantification of Uncertainty with Adversarial Models NeurIPS 2023