ICML 2024 "gradient-based optimization" Papers
9 papers found
Challenges in Training PINNs: A Loss Landscape Perspective
Pratik Rathore, Weimu Lei, Zachary Frangella et al.
ICML 2024poster
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
Jonas Beck, Nathanael Bosch, Michael Deistler et al.
ICML 2024poster
How to Escape Sharp Minima with Random Perturbations
Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra
ICML 2024poster
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd, Louis Sharrock, Chris Nemeth
ICML 2024spotlight
Learning with 3D rotations, a hitchhiker's guide to SO(3)
Andreas René Geist, Jonas Frey, Mikel Zhobro et al.
ICML 2024poster
Operator SVD with Neural Networks via Nested Low-Rank Approximation
Jongha (Jon) Ryu, Xiangxiang Xu, Hasan Sabri Melihcan Erol et al.
ICML 2024poster
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.
ICML 2024poster
Smooth Tchebycheff Scalarization for Multi-Objective Optimization
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang et al.
ICML 2024poster
UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers
Duo Peng, Qiuhong Ke, Jun Liu
ICML 2024poster