105 citations · 195 across the 28 of their papers we have counts for
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stat.ML2019
Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion
Chieh Wu, Jared Miller, Yale Chang +2
The Hilbert Schmidt Independence Criterion (HSIC) is a kernel dependence measure that has applications in various aspects of machine learning. Conveniently, the objectives of diffe…
cs.LG2019
Deep Kernel Learning for Clustering
Chieh Wu, Zulqarnain Khan, Yale Chang +2
We propose a deep learning approach for discovering kernels tailored to identifying clusters over sample data. Our neural network produces sample embeddings that are motivated by--…
cs.LG2019★ 4 cited
Neural Topographic Factor Analysis for fMRI Data
Eli Sennesh, Zulqarnain Khan, Yiyu Wang +4
Neuroimaging studies produce gigabytes of spatio-temporal data for a small number of participants and stimuli. Rarely do researchers attempt to model and examine how individual par…