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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)

Learning Triangular Distribution in Visual World CVPR 2024 Learning Ultrametric Trees for Optimal Transport Regression AAAI 2024 Learning Under Random Distributional Shifts AISTATS 2024 Learning Universal Predictors ICML 2024 Learning via Surrogate PAC-Bayes NeurIPS 2024 Learning Visuotactile Estimation and Control for Non-prehensile Manipulation under Occlusions CoRL 2024 Learning What to Monitor: Using Machine Learning to Improve past STL Monitoring IJCAI 2024 Learning Where to Edit Vision Transformers NeurIPS 2024 Learning with a linear loss function: excess risk and estimation bounds for ERM, minmax MOM and their regularized versions with applications to robustness in sparse PCA. JMLR 2024 Learning with Fitzpatrick Losses NeurIPS 2024 Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks JMLR 2024 Learning with Posterior Sampling for Revenue Management under Time-varying Demand IJCAI 2024 Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency CVPR 2024 Learning World Models for Unconstrained Goal Navigation NeurIPS 2024 Least Squares Regression Can Exhibit Under-Parameterized Double Descent NeurIPS 2024 Leave-one-out Distinguishability in Machine Learning ICLR 2024 Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize AAAI 2024 LEMON: Reviving Stronger and Smaller LMs from Larger LMs with Linear Parameter Fusion ACL 2024 Lemur: Integrating Large Language Models in Automated Program Verification ICLR 2024 Length-Aware Multi-Kernel Transformer for Long Document Classification NAACL 2024 Length Generalization of Causal Transformers without Position Encoding ACL 2024 Length independent PAC-Bayes bounds for Simple RNNs AISTATS 2024 Length Optimization in Conformal Prediction NeurIPS 2024 Less is More for Improving Automatic Evaluation of Factual Consistency NAACL 2024 Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective ACL 2024