137 citations · 154 across the 5 of their papers we have counts for
6 papers
Multi-Party Dual Learning
Maoguo Gong, Yuan Gao, Yu Xie +3
The performance of machine learning algorithms heavily relies on the availability of a large amount of training data. However, in reality, data usually reside in distributed partie…
Multi-Space Evolutionary Search for Large-Scale Optimization
Liang Feng, Qingxia Shang, Yaqing Hou +2
In recent years, to improve the evolutionary algorithms used to solve optimization problems involving a large number of decision variables, many attempts have been made to simplify…
Online Deep Clustering for Unsupervised Representation Learning
Xiaohang Zhan, Jiahao Xie, Ziwei Liu +2
Joint clustering and feature learning methods have shown remarkable performance in unsupervised representation learning. However, the training schedule alternating between feature…
Jacobian Adversarially Regularized Networks for Robustness
Alvin Chan, Yi Tay, Yew Soon Ong +1
Adversarial examples are crafted with imperceptible perturbations with the intent to fool neural networks. Against such attacks, adversarial training and its variants stand as the…
Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer
Alvin Chan, Lei Ma, Felix Juefei-Xu +3
Deep neural networks (DNN), while becoming the driving force of many novel technology and achieving tremendous success in many cutting-edge applications, are still vulnerable to ad…
Evolutionary Multitasking for Single-objective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results
Bingshui Da, Yew-Soon Ong, Liang Feng +6
In this report, we suggest nine test problems for multi-task single-objective optimization (MTSOO), each of which consists of two single-objective optimization tasks that need to b…