← Optimization & Theory
Deep Learning › Optimization & Theory ›

Optimization

1638 directly classified papers

Papers per year

Papers

Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing ICML 2023
ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing CVPR 2023
A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates ICML 2023
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks ICML 2023
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching ICML 2023
Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity ICML 2023
Transformer-Based Learned Optimization CVPR 2023
Deep Equilibrium Models for Snapshot Compressive Imaging AAAI 2023
Gradient Descent Finds the Global Optima of Two-Layer Physics-Informed Neural Networks ICML 2023
Moccasin: Efficient Tensor Rematerialization for Neural Networks ICML 2023
Gradient Descent Converges Linearly for Logistic Regression on Separable Data ICML 2023
Implementing Contextual Biasing in GPU Decoder for Online ASR INTERSPEECH 2023
SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance ICML 2023
Improved Distribution Matching for Dataset Condensation CVPR 2023
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization ICML 2023
Principled Acceleration of Iterative Numerical Methods Using Machine Learning ICML 2023
SGD with Large Step Sizes Learns Sparse Features ICML 2023
SAM operates far from home: eigenvalue regularization as a dynamical phenomenon ICML 2023
Tunable Convolutions With Parametric Multi-Loss Optimization CVPR 2023
Learning Fractals by Gradient Descent AAAI 2023
Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization CVPR 2023
RobustNeRF: Ignoring Distractors With Robust Losses CVPR 2023
FIANCEE: Faster Inference of Adversarial Networks via Conditional Early Exits CVPR 2023
Efficient Robust Principal Component Analysis via Block Krylov Iteration and CUR Decomposition CVPR 2023
Sliced Optimal Partial Transport CVPR 2023