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

How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective ICML 2024 How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model ICML 2024 How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization? NeurIPS 2024 How does Gradient Descent Learn Features --- A Local Analysis for Regularized Two-Layer Neural Networks NeurIPS 2024 How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach NeurIPS 2024 How does PDE order affect the convergence of PINNs? NeurIPS 2024 How Does Unlabeled Data Provably Help Out-of-Distribution Detection? ICLR 2024 How Does Variance Shape the Regret in Contextual Bandits? NeurIPS 2024 How Do Hyenas Deal with Human Speech? Speech Recognition and Translation with ConfHyena COLING 2024 How Do Large Language Models Acquire Factual Knowledge During Pretraining? NeurIPS 2024 How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? ICML 2024 How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad NeurIPS 2024 How Flawed Is ECE? An Analysis via Logit Smoothing ICML 2024 How Free is Parameter-Free Stochastic Optimization? ICML 2024 How Good Are LLMs at Out-of-Distribution Detection? COLING 2024 How Good is a Single Basin? AISTATS 2024 How Graph Neural Networks Learn: Lessons from Training Dynamics ICML 2024 How Hard Is It to Impact the Impact of Your Paper? IJCAI 2024 How many classifiers do we need? NeurIPS 2024 How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? ICLR 2024 How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization ICLR 2024 How Reliable Are Automatic Evaluation Methods for Instruction-Tuned LLMs? EMNLP 2024 How safe am I given what I see? Calibrated prediction of safety chances for image-controlled autonomy L4DC 2024 How Smooth Is Attention? ICML 2024 How Sparse Can We Prune A Deep Network: A Fundamental Limit Perspective NeurIPS 2024