11 citations · 31 across the 10 of their papers we have counts for
10 papers
ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection
Huiping Zhuang, Zhenyu Weng, Hongxin Wei +3
Class-incremental learning (CIL) learns a classification model with training data of different classes arising progressively. Existing CIL either suffers from serious accuracy loss…
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…
Analytic Learning of Convolutional Neural Network For Pattern Recognition
Huiping Zhuang, Zhiping Lin, Yimin Yang +1
Training convolutional neural networks (CNNs) with back-propagation (BP) is time-consuming and resource-intensive particularly in view of the need to visit the dataset multiple tim…
An Analytic Layer-wise Deep Learning Framework with Applications to Robotics
Huu-Thiet Nguyen, Chien Chern Cheah, Kar-Ann Toh
Deep learning (DL) has achieved great success in many applications, but it has been less well analyzed from the theoretical perspective. The unexplainable success of black-box DL m…
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…
Stretchy Polynomial Regression
Kar-Ann Toh
This article proposes a novel solution for stretchy polynomial regression learning. The solution comes in primal and dual closed-forms similar to that of ridge regression. Essentia…