2 citations · 4 across the 5 of their papers we have counts for
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cs.LG2021★ 1 cited
Labels, Information, and Computation: Efficient Learning Using Sufficient Labels
Shiyu Duan, Spencer Chang, Jose C. Principe
In supervised learning, obtaining a large set of fully-labeled training data is expensive. We show that we do not always need full label information on every single training exampl…
cs.LG2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods
Shiyu Duan, Jose C. Principe
This tutorial paper surveys provably optimal alternatives to end-to-end backpropagation (E2EBP) -- the de facto standard for training deep architectures. Modular training refers to…
cs.LG2018★ 2 cited
On Kernel Method-Based Connectionist Models and Supervised Deep Learning Without Backpropagation
Shiyu Duan, Shujian Yu, Yunmei Chen +1
We propose a novel family of connectionist models based on kernel machines and consider the problem of learning layer-by-layer a compositional hypothesis class, i.e., a feedforward…