35 citations · 224 across the 26 of their papers we have counts for
4 papers · 1 filter
An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data
Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng
In this paper, we propose an information-theoretic approach to design the functional representations to extract the hidden common structure shared by a set of random variables. The…
On the Sample Complexity of HGR Maximal Correlation Functions for Large Datasets
Shao-Lun Huang, Xiangxiang Xu
The Hirschfeld-Gebelein-Rényi (HGR) maximal correlation and the corresponding functions have been shown useful in many machine learning scenarios. In this paper, we study the sampl…
An Information Theoretic Interpretation to Deep Neural Networks
Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng +1
It is commonly believed that the hidden layers of deep neural networks (DNNs) attempt to extract informative features for learning tasks. In this paper, we formalize this intuition…
On the Capacity of Gaussian Relay Channels
Shao-Lun Huang, Ming-Yang Chen, Kwang-Cheng Chen +1
This paper has been withdrawn due to that the same conclusion has been proposed before.