Min–max problems have broad applications in machine learning, including learning with non-decomposable loss and learning with robustness to data distribution. Convex–concave min–max problem is an active topic
We propose a combination of machine learning and flux limiting for property-preserving subgrid scale modeling in the context of flux-limited finite volume methods for the one-dimensional shallow-water equations. The numerical fluxes of a conservative target scheme are fitted to the coarse-mesh ...
Finally, we investigate the proposed algorithms for an important problem in machine learning: the t-distributed stochastic neighbor embedding. Abstract We address the problem of minimizing the sum of a nonconvex, differentiable function and composite functions by DC (Difference of Convex functions) prog...
Many problems in machine learning and other fields can be (re)formulated as linearly constrained separable convex programs. In most of the cases, there are
Optimization is an important concept to understand and apply carefully in applied machine learning. In this post you discovered 5 convex optimization algorithms with recipes in R that are ready to copy and paste into your own problem. You also learned some background for each method and general ...
Foundations and Trends® in Machine Learning(共66册), 这套丛书还有 《Kernels for Vector-Valued Functions》《Model-based Reinforcement Learning》《A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists》《On the Concentration Properties of Interacting Particle Processes》《Spectral Me...
is convex. thus, proving the acceleration becomes a harder task than the analysis for convex programming. 1.1 related work recently, there is a trend to study the nonconvex problem ( 2 ) in the machine learning and optimization community. recent developments come from two aspects: (1). the ...
Nan W., et al. “The Value of Collaboration in Convex Machine Learning with Differential Privacy.” 2020 IEEE Symposium on Security and Privacy. 304-317. 联邦学习场景中,在适应度函数平滑、强凸、利普斯特连续的条件下,估算各客户端使用不同隐私预算时最终全局模型的信息损失量。实践中,针对适应...
Proteins are a key element of the cell and play an important role in a variety of cellular functions such as ligand binding, metabolic control, cell signaling and gene regulation. The prediction of the tertiary structure of protein complexes is known as the protein-protein docking problem. Severa...
Since then, he has been an Assistant Professor in the School of Electrical and Electronic Engineering, Nanyang Technological University. His current research interests include machine learning, bioinformatics, and networking. He is a senior member of IEEE. Dr. Huang is an Associate Editor of Neuro...