105 citations · 195 across the 28 of their papers we have counts for
5 papers · 1 filter
Deep Layer-wise Networks Have Closed-Form Weights
Chieh Wu, Aria Masoomi, Arthur Gretton +1
There is currently a debate within the neuroscience community over the likelihood of the brain performing backpropagation (BP). To better mimic the brain, training a network \texti…
On the Sample Complexity of Rank Regression from Pairwise Comparisons
Berkan Kadioglu, Peng Tian, Jennifer Dy +2
We consider a rank regression setting, in which a dataset of samples with features in is ranked by an oracle via pairwise comparisons. Specifically, there ex…
Deep Layer-wise Networks Have Closed-Form Weights
Chieh Wu, Aria Masoomi, Arthur Gretton +1
There is currently a debate within the neuroscience community over the likelihood of the brain performing backpropagation (BP). To better mimic the brain, training a network $\text…
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…
Structured Disentangled Representations
Babak Esmaeili, Hao Wu, Sarthak Jain +6
Deep latent-variable models learn representations of high-dimensional data in an unsupervised manner. A number of recent efforts have focused on learning representations that disen…