Non-Convex Optimization with Spectral Radius Regularization
Engineering Sciences and Applied Mathematics, Northwestern University（西北大学工程科学与应用数学系）；Industrial Engineering and Management Sciences, Northwestern University（西北大学工业工程与管理科学系）；Preventive Medicine (Health and Biomedical Informatics), Northwestern University（西北大学预防医学（健康与生物医学信息学））
We develop regularization methods to find flat minima while training deep neural networks. These minima generalize better than sharp minima, yielding models outperforming baselines on real-world test data (which may be distributed differently than the training data). Specifically, we propose a method of regularized optimization to reduce the spectral radius of the Hessian of the loss function. We also derive algorithms to efficiently optimize neural network models and prove that these algorithms almost surely converge. Furthermore, we demonstrate that our algorithm works effectively on applications in different domains, including healthcare. To show that our models generalize well, we introduced various methods for testing generalizability and found that our models outperform comparable baseline models on these tests.
Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM
Institut de Recherche en Informatique de Toulouse（图卢兹计算机科学研究所）；CNRS（法国国家科学研究中心）；Université de Toulouse（图卢兹大学）；Nomao SA（Nomao公司）；Laboratoire Lagrange（拉格朗日实验室）；Université de Nice-Sophia Antipolis（尼斯-索菲亚·安提波利斯大学）；INSA de Rouen（鲁昂国立应用科学学院）；Institut de Mathématiques de Toulouse（图卢兹数学研究所）；Institut Universitaire de Formation de Maîtres（大学教师培训学院）
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport
CREST（法国国家科学研究中心经济与统计研究中心）；ENSAE（法国国家统计与经济管理学院）；Institut Polytechnique de Paris（巴黎综合理工学院）；CNRS（法国国家科学研究中心）；ENS, PSL Research University（巴黎高等师范学院，巴黎文理研究大学）；Google Brain（谷歌大脑）
Don't relax: early stopping for convex regularization
Ecole Politechnique（巴黎综合理工学院）；Istituto Italiano di Tecnologia（意大利技术研究院）；Massachusetts Institute of Technology（麻省理工学院）；Università di Genova（热那亚大学）；Politecnico di Milano（米兰理工大学）；EPFL（洛桑联邦理工学院）
Convex regularization in statistical inverse learning problems
University of Helsinki（赫尔辛基大学）；University of Cambridge（剑桥大学）；Friedrich-Alexander Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡大学）；Lappeenranta University of Technology（拉彭兰塔理工大学）；University of Genoa（热那亚大学）
Successive Convex Approximation Algorithms for Sparse Signal Estimation with Nonconvex Regularizations
Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg（卢森堡大学安全、可靠性与信任跨学科中心）；Technische Universität Darmstadt（达姆施塔特工业大学）
Weakly Convex Ridge Regularization for 3D Non-Cartesian MRI Reconstruction
Faculty of Mathematics, Chemnitz University of Technology（开姆尼茨工业大学数学学院）；NeuroSpin, Frédéric Joliot Institute for Life Sciences, CEA Paris-Saclay（法国原子能委员会巴黎-萨克雷大学弗雷德里克·约里奥生命科学研究所神经自旋中心）；MIND, Inria Saclay Centre（法国国家信息与自动化研究所萨克雷中心MIND团队）；Siemens Healthineers（西门子医疗）
Hyperspectral Image Denoising Using Non-convex Local Low-rank and Sparse Separation with Spatial-Spectral Total Variation Regularization
Qingdao University（青岛大学）；Harbin Institute of Technology（哈尔滨工业大学）；University of Electronic Science and Technology of China（电子科技大学）；University of Kentucky（肯塔基大学）；University of California, Santa Barbara（加州大学圣巴巴拉分校）
