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Deterministic Bridge Regression for Compressive Classification
Kar-Ann Toh, Giuseppe Molteni, Zhiping Lin
Pattern classification with compact representation is an important component in machine intelligence. In this work, an analytic bridge solution is proposed for compressive classifi…
Accumulated Decoupled Learning: Mitigating Gradient Staleness in Inter-Layer Model Parallelization
Huiping Zhuang, Zhiping Lin, Kar-Ann Toh
Decoupled learning is a branch of model parallelism which parallelizes the training of a network by splitting it depth-wise into multiple modules. Techniques from decoupled learnin…
Analytic Network Learning
Kar-Ann Toh
Based on the property that solving the system of linear matrix equations via the column space and the row space projections boils down to an approximation in the least squares erro…
Gradient-Free Learning Based on the Kernel and the Range Space
Kar-Ann Toh, Zhiping Lin, Zhengguo Li +2
In this article, we show that solving the system of linear equations by manipulating the kernel and the range space is equivalent to solving the problem of least squares error appr…
Learning from the Kernel and the Range Space
Kar-Ann Toh
In this article, a novel approach to learning a complex function which can be written as the system of linear equations is introduced. This learning is grounded upon the observatio…
Deterministic Stretchy Regression
Kar-Ann Toh, Lei Sun, Zhiping Lin
An extension of the regularized least-squares in which the estimation parameters are stretchable is introduced and studied in this paper. The solution of this ridge regression with…