165 citations · 224 across the 25 of their papers we have counts for
9 papers · 1 filter
Learning-Assisted Algorithm Unrolling for Online Optimization with Budget Constraints
Jianyi Yang, Shaolei Ren
Online optimization with multiple budget constraints is challenging since the online decisions over a short time horizon are coupled together by strict inventory constraints. The e…
Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning
Yejia Liu, Wang Zhu, Shaolei Ren
Continual learning faces a crucial challenge of catastrophic forgetting. To address this challenge, experience replay (ER) that maintains a tiny subset of samples from previous tas…
ObfuNAS: A Neural Architecture Search-based DNN Obfuscation Approach
Tong Zhou, Shaolei Ren, Xiaolin Xu
Malicious architecture extraction has been emerging as a crucial concern for deep neural network (DNN) security. As a defense, architecture obfuscation is proposed to remap the vic…
Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity
Jianyi Yang, Shaolei Ren
By integrating domain knowledge with labeled samples, informed machine learning has been emerging to improve the learning performance for a wide range of applications. Nonetheless,…
Expert-Calibrated Learning for Online Optimization with Switching Costs
Pengfei Li, Jianyi Yang, Shaolei Ren
We study online convex optimization with switching costs, a practically important but also extremely challenging problem due to the lack of complete offline information. By tapping…
LeHDC: Learning-Based Hyperdimensional Computing Classifier
Shijin Duan, Yejia Liu, Shaolei Ren +1
Thanks to the tiny storage and efficient execution, hyperdimensional Computing (HDC) is emerging as a lightweight learning framework on resource-constrained hardware. Nonetheless,…
A Brain-Inspired Low-Dimensional Computing Classifier for Inference on Tiny Devices
Shijin Duan, Xiaolin Xu, Shaolei Ren
By mimicking brain-like cognition and exploiting parallelism, hyperdimensional computing (HDC) classifiers have been emerging as a lightweight framework to achieve efficient on-dev…
A Semi-Decoupled Approach to Fast and Optimal Hardware-Software Co-Design of Neural Accelerators
Bingqian Lu, Zheyu Yan, Yiyu Shi +1
In view of the performance limitations of fully-decoupled designs for neural architectures and accelerators, hardware-software co-design has been emerging to fully reap the benefit…
HDLock: Exploiting Privileged Encoding to Protect Hyperdimensional Computing Models against IP Stealing
Shijin Duan, Shaolei Ren, Xiaolin Xu
Hyperdimensional Computing (HDC) is facing infringement issues due to straightforward computations. This work, for the first time, raises a critical vulnerability of HDC, an attack…