activity
20172023
most citedA Selective Overview of Deep Learning

41 citations · 42 across the 2 of their papers we have counts for

collaborators

9 papers

stat.ML2023★ 1 cited

Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage

Yu Gui, Cong Ma, Yiqiao Zhong

We investigate the role of projection heads, also known as projectors, within the encoder-projector framework (e.g., SimCLR) used in contrastive learning. We aim to demystify the o…

cs.LG2021

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…

stat.ML2020

The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training

Andrea Montanari, Yiqiao Zhong

Modern neural networks are often operated in a strongly overparametrized regime: they comprise so many parameters that they can interpolate the training set, even if actual labels…

stat.ML2019★ 41 cited

A Selective Overview of Deep Learning

Jianqing Fan, Cong Ma, Yiqiao Zhong

Deep learning has arguably achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex depende…

stat.ME2018

Robust high dimensional factor models with applications to statistical machine learning

Jianqing Fan, Kaizheng Wang, Yiqiao Zhong +1

Factor models are a class of powerful statistical models that have been widely used to deal with dependent measurements that arise frequently from various applications from genomic…

stat.ME2018

Optimal Subspace Estimation Using Overidentifying Vectors via Generalized Method of Moments

Jianqing Fan, Yiqiao Zhong

Many statistical models seek relationship between variables via subspaces of reduced dimensions. For instance, in factor models, variables are roughly distributed around a low dime…