8 citations · 13 across the 9 of their papers we have counts for
4 papers · 1 filter
Replica Symmetry Breaking and Algorithmic Thresholds in Empirical Risk Minimization under Multi-Index Model
Andrea Montanari, Kangjie Zhou
Modern machine learning models are trained by optimizing high-dimensional non-convex empirical risk functions. Such cost functions can have a multitude of local optima and yet, gra…
Learning time-scales in two-layers neural networks
Raphaël Berthier, Andrea Montanari, Kangjie Zhou
Gradient-based learning in multi-layer neural networks displays a number of striking features. In particular, the decrease rate of empirical risk is non-monotone even after averagi…
Lower Bounds for the Convergence of Tensor Power Iteration on Random Overcomplete Models
Yuchen Wu, Kangjie Zhou
Tensor decomposition serves as a powerful primitive in statistics and machine learning, and has numerous applications in problems such as learning latent variable models or mixture…
Tractability from overparametrization: The example of the negative perceptron
Andrea Montanari, Yiqiao Zhong, Kangjie Zhou
In the negative perceptron problem we are given data points , where is a -dimensional vector and is a binary l…