273 citations · 1.6k across the 53 of their papers we have counts for
4 papers · 1 filter
Why are deep nets reversible: A simple theory, with implications for training
Sanjeev Arora, Yingyu Liang, Tengyu Ma
Generative models for deep learning are promising both to improve understanding of the model, and yield training methods requiring fewer labeled samples. Recent works use generativ…
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients
Bo Xie, Yingyu Liang, Le Song
Nonlinear component analysis such as kernel Principle Component Analysis (KPCA) and kernel Canonical Correlation Analysis (KCCA) are widely used in machine learning, statistics and…
Communication Efficient Distributed Kernel Principal Component Analysis
Maria-Florina Balcan, Yingyu Liang, Le Song +2
Kernel Principal Component Analysis (KPCA) is a key machine learning algorithm for extracting nonlinear features from data. In the presence of a large volume of high dimensional da…
A Latent Variable Model Approach to PMI-based Word Embeddings
Sanjeev Arora, Yuanzhi Li, Yingyu Liang +2
Semantic word embeddings represent the meaning of a word via a vector, and are created by diverse methods. Many use nonlinear operations on co-occurrence statistics, and have hand-…