17 citations · 35 across the 6 of their papers we have counts for
6 papers
Interpretable Feature Engineering for Time Series Predictors using Attention Networks
Tianjie Wang, Jie Chen, Joel Vaughan +1
Regression problems with time-series predictors are common in banking and many other areas of application. In this paper, we use multi-head attention networks to develop interpreta…
A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation
Min Zhao, Jie Chen, Zhe He
Spectral unmixing is an important and challenging problem in hyperspectral data processing. This topic has been extensively studied and a variety of unmixing algorithms have been p…
Deep Extractor Network for Target Speaker Recovery From Single Channel Speech Mixtures
Jun Wang, Jie Chen, Dan Su +4
Speaker-aware source separation methods are promising workarounds for major difficulties such as arbitrary source permutation and unknown number of sources. However, it remains cha…
Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications
Sijia Liu, Jie Chen, Pin-Yu Chen +1
In this paper, we design and analyze a new zeroth-order online algorithm, namely, the zeroth-order online alternating direction method of multipliers (ZOO-ADMM), which enjoys dual…
On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps
Jie Chen, Dehua Cheng, Yan Liu
Positive-definite kernel functions are fundamental elements of kernel methods and Gaussian processes. A well-known construction of such functions comes from Bochner's characterizat…
Hierarchically Compositional Kernels for Scalable Nonparametric Learning
Jie Chen, Haim Avron, Vikas Sindhwani
We propose a novel class of kernels to alleviate the high computational cost of large-scale nonparametric learning with kernel methods. The proposed kernel is defined based on a hi…