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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)

Sharp thresholds in inference of planted subgraphs COLT 2023 SharPT: Shared Latent Space Prompt Tuning EACL 2023 Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments ICML 2023 Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances ICML 2023 ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer NeurIPS 2023 ShiftDDPMs: Exploring Conditional Diffusion Models by Shifting Diffusion Trajectories AAAI 2023 Shifted PAUQ: Distribution shift in text-to-SQL EMNLP 2023 ShiftNAS: Improving One-shot NAS via Probability Shift ICCV 2023 Shockwave: Fair and Efficient Cluster Scheduling for Dynamic Adaptation in Machine Learning NSDI 2023 Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations CVPR 2023 Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search ICML 2023 Shortest Program Interpolation Learning COLT 2023 Short-term Extrapolation of Speech Signals Using Recursive Neural Networks in the STFT Domain Interspeech 2023 SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning NeurIPS 2023 Should We Learn Most Likely Functions or Parameters? NeurIPS 2023 Show Me How It’s Done: The Role of Explanations in Fine-Tuning Language Models ACML 2023 Show Me the Way! Bilevel Search for Synthesizing Programmatic Strategies AAAI 2023 SigMaNet: One Laplacian to Rule Them All AAAI 2023 Sigmoid Loss for Language Image Pre-Training ICCV 2023 SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning NeurIPS 2023 Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities NeurIPS 2023 SIMPLE: A Gradient Estimator for k-Subset Sampling ICLR 2023 Simple and Effective Out-of-Distribution Detection via Cosine-based Softmax Loss ICCV 2023 Simple and Efficient Confidence Score for Grading Whole Slide Images MIDL 2023 Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints COLT 2023