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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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Papers (including subtopics)

Weighted Sampling without Replacement for Deep Top-k Classification ICML 2023 Weighted Von Mises Distribution-based Loss Function for Real-time STFT Phase Reconstruction Using DNN Interspeech 2023 We Need to Talk About Reproducibility in NLP Model Comparison EMNLP 2023 What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization ACL 2023 What can a Single Attention Layer Learn? A Study Through the Random Features Lens NeurIPS 2023 What Can Be Learnt With Wide Convolutional Neural Networks? ICML 2023 What can online reinforcement learning with function approximation benefit from general coverage conditions? ICML 2023 What Can We Learn by Predicting Accuracy? WACV 2023 What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability EMNLP 2023 What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners? NeurIPS 2023 What do CNNs Learn in the First Layer and Why? A Linear Systems Perspective ICML 2023 What do neural networks learn in image classification? A frequency shortcut perspective ICCV 2023 What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding NeurIPS 2023 What Is Missing in IRM Training and Evaluation? Challenges and Solutions ICLR 2023 What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models NeurIPS 2023 What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization IJCAI 2023 What Makes Convolutional Models Great on Long Sequence Modeling? ICLR 2023 What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. NeurIPS 2023 What shapes the loss landscape of self supervised learning? ICLR 2023 When are ensembles really effective? NeurIPS 2023 When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality NeurIPS 2023 When Can We Track Significant Preference Shifts in Dueling Bandits? NeurIPS 2023 When Congestion Games Meet Mobile Crowdsourcing: Selective Information Disclosure AAAI 2023 When Do Curricula Work in Federated Learning? ICCV 2023 When Does Confidence-Based Cascade Deferral Suffice? NeurIPS 2023