69 citations · 455 across the 44 of their papers we have counts for
3 papers · 1 filter
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang +2
Sampling a probability distribution with an unknown normalization constant is a fundamental problem in computational science and engineering. This task may be cast as an optimizati…
Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes
Kenji Kawaguchi, Jiaoyang Huang
In this paper, we theoretically prove that gradient descent can find a global minimum of non-convex optimization of all layers for nonlinear deep neural networks of sizes commonly…
Every Local Minimum Value is the Global Minimum Value of Induced Model in Non-convex Machine Learning
Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling
For nonconvex optimization in machine learning, this article proves that every local minimum achieves the globally optimal value of the perturbable gradient basis model at any diff…