"gradient-based optimization" Papers
25 papers found
Conference
$\sigma$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
Antonio Emanuele Cinà, Francesco Villani, Maura Pintor et al.
Bridging Arbitrary and Tree Metrics via Differentiable Gromov Hyperbolicity
Pierre Houédry, Nicolas Courty, Florestan Martin-Baillon et al.
Differentiable Decision Tree via "ReLU+Argmin" Reformulation
Qiangqiang Mao, Jiayang Ren, Yixiu Wang et al.
Diverse Rare Sample Generation with Pretrained GANs
Subeen Lee, Jiyeon Han, Soyeon Kim et al.
Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining
Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu et al.
Enhancing Transformers Through Conditioned Embedded Tokens
Hemanth Saratchandran, Simon Lucey
Federated Binary Matrix Factorization Using Proximal Optimization
Sebastian Dalleiger, Jilles Vreeken, Michael Kamp
Information-Driven Design of Imaging Systems
Henry Pinkard, Leyla Kabuli, Eric Markley et al.
LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs
Ran Li, Hao Wang, Chengzhi Mao
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape Reconstruction
Sinisa Stekovic, Arslan Artykov, Stefan Ainetter et al.
SFESS: Score Function Estimators for $k$-Subset Sampling
Klas Wijk, Ricardo Vinuesa, Hossein Azizpour
SUMO: Subspace-Aware Moment-Orthogonalization for Accelerating Memory-Efficient LLM Training
Yehonathan Refael, Guy Smorodinsky, Tom Tirer et al.
YOLO-Count: Differentiable Object Counting for Text-to-Image Generation
Guanning Zeng, Xiang Zhang, Zirui Wang et al.
Challenges in Training PINNs: A Loss Landscape Perspective
Pratik Rathore, Weimu Lei, Zachary Frangella et al.
Differentiable Convex Polyhedra Optimization from Multi-view Images
Daxuan Ren, Haiyi Mei, Hezi Shi et al.
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
Jonas Beck, Nathanael Bosch, Michael Deistler et al.
How to Escape Sharp Minima with Random Perturbations
Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd, Louis Sharrock, Chris Nemeth
Learning with 3D rotations, a hitchhiker's guide to SO(3)
Andreas René Geist, Jonas Frey, Mikel Zhobro et al.
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning
Baoquan Zhang, Chuyao Luo, Demin Yu et al.
Operator SVD with Neural Networks via Nested Low-Rank Approximation
Jongha (Jon) Ryu, Xiangxiang Xu, Hasan Sabri Melihcan Erol et al.
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.
Smooth Tchebycheff Scalarization for Multi-Objective Optimization
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang et al.
Soft Shadow Diffusion (SSD): Physics-inspired Learning for 3D Computational Periscopy
Fadlullah Raji, John Murray-Bruce
UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers
Duo Peng, Qiuhong Ke, Jun Liu