← Optimization & Theory
Deep Learning › Optimization & Theory ›

Theory

1072 directly classified papers

Papers per year

Papers

The First Theoretical Approximation Guarantees for the Non-Dominated Sorting Genetic Algorithm III (NSGA-III) IJCAI 2025
Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective ICCV 2025
Activation Subspaces for Out-of-Distribution Detection ICCV 2025
Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent AAAI 2025
Statistical inference on black-box generative models in the data kernel perspective space ACL 2025
Verification of Neural Networks Against Convolutional Perturbations via Parameterised Kernels AAAI 2025
Interpret and Improve In-Context Learning via the Lens of Input-Label Mappings ACL 2025
Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity AISTATS 2024
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability AISTATS 2024
From Activation to Initialization: Scaling Insights for Optimizing Neural Fields CVPR 2024
Scaling Laws for Data Filtering-- Data Curation cannot be Compute Agnostic CVPR 2024
Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields CVPR 2024
Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK JMLR 2024
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models NIPS 2024
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis CVPR 2024
The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis JMLR 2024
Convergence of Message-Passing Graph Neural Networks with Generic Aggregation on Large Random Graphs JMLR 2024
Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed NIPS 2024
Can Transformers Learn n-gram Language Models? EMNLP 2024
Detection and Measurement of Syntactic Templates in Generated Text EMNLP 2024
High Probability Convergence Bounds for Non-convex Stochastic Gradient Descent with Sub-Weibull Noise JMLR 2024
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers NIPS 2024
Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis EMNLP 2024
Law of Large Numbers and Central Limit Theorem for Wide Two-layer Neural Networks: The Mini-Batch and Noisy Case JMLR 2024
A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks JMLR 2024