Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

The Mamba in the Llama: Distilling and Accelerating Hybrid Models NeurIPS 2024 The Many Faces of Optimal Weak-to-Strong Learning NeurIPS 2024 The Marginal Value of Momentum for Small Learning Rate SGD ICLR 2024 The mechanistic basis of data dependence and abrupt learning in an in-context classification task ICLR 2024 The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels NeurIPS 2024 The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes CVPR 2024 The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis EMNLP 2024 The Mystery of the Pathological Path-star Task for Language Models EMNLP 2024 The Non-linear F-Design and Applications to Interactive Learning ICML 2024 The Non-Overlapping Statistical Approximation to Overlapping Group Lasso JMLR 2024 The Nyström method for convex loss functions JMLR 2024 The Open-World Lottery Ticket Hypothesis for OOD Intent Classification COLING 2024 The optimality of kernel classifiers in Sobolev space ICLR 2024 Theoretical Analysis of Learned Database Operations under Distribution Shift through Distribution Learnability ICML 2024 Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach ICLR 2024 Theoretical Analysis of Weak-to-Strong Generalization NeurIPS 2024 Theoretical and Empirical Analysis of Cost-Function Merging for Implicit Hitting Set WCSP Solving AAAI 2024 Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks NeurIPS 2024 Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks NeurIPS 2024 Theoretical Foundations of Deep Selective State-Space Models NeurIPS 2024 Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians ICML 2024 Theoretical guarantees in KL for Diffusion Flow Matching NeurIPS 2024 Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning NeurIPS 2024 Theoretically Achieving Continuous Representation of Oriented Bounding Boxes CVPR 2024 Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention AISTATS 2024