43 citations · 86 across the 19 of their papers we have counts for
19 papers
Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement
Yang Bai, Lixing Chen, Shaolei Ren +1
The rapid uptake of intelligent applications is pushing deep learning (DL) capabilities to Internet-of-Things (IoT). Despite the emergence of new tools for embedding deep neural ne…
Robust Bandit Learning with Imperfect Context
Jianyi Yang, Shaolei Ren
A standard assumption in contextual multi-arm bandit is that the true context is perfectly known before arm selection. Nonetheless, in many practical applications (e.g., cloud reso…
Distributed Thompson Sampling
Jing Dong, Tan Li, Shaolei Ren +1
We study a cooperative multi-agent multi-armed bandits with M agents and K arms. The goal of the agents is to minimized the cumulative regret. We adapt a traditional Thompson Sampl…
A Quantitative Perspective on Values of Domain Knowledge for Machine Learning
Jianyi Yang, Shaolei Ren
With the exploding popularity of machine learning, domain knowledge in various forms has been playing a crucial role in improving the learning performance, especially when training…
Scaling Up Deep Neural Network Optimization for Edge Inference
Bingqian Lu, Jianyi Yang, Shaolei Ren
Deep neural networks (DNNs) have been increasingly deployed on and integrated with edge devices, such as mobile phones, drones, robots and wearables. To run DNN inference directly…
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring
Zhihui Shao, Jianyi Yang, Shaolei Ren
Inference accuracy of deep neural networks (DNNs) is a crucial performance metric, but can vary greatly in practice subject to actual test datasets and is typically unknown due to…
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets
Zhihui Shao, Jianyi Yang, Shaolei Ren
To increase the trustworthiness of deep neural network (DNN) classifiers, an accurate prediction confidence that represents the true likelihood of correctness is crucial. Towards t…
Adversarial Attacks on Brain-Inspired Hyperdimensional Computing-Based Classifiers
Fangfang Yang, Shaolei Ren
Being an emerging class of in-memory computing architecture, brain-inspired hyperdimensional computing (HDC) mimics brain cognition and leverages random hypervectors (i.e., vectors…
A Note on Latency Variability of Deep Neural Networks for Mobile Inference
Luting Yang, Bingqian Lu, Shaolei Ren
Running deep neural network (DNN) inference on mobile devices, i.e., mobile inference, has become a growing trend, making inference less dependent on network connections and keepin…
Your Noise, My Signal: Exploiting Switching Noise for Stealthy Data Exfiltration from Desktop Computers
Zhihui Shao, Mohammad A. Islam, Shaolei Ren
Attacks based on power analysis have been long existing and studied, with some recent works focused on data exfiltration from victim systems without using conventional communicatio…
Spatio-temporal Edge Service Placement: A Bandit Learning Approach
Lixing Chen, Jie Xu, Shaolei Ren +1
Shared edge computing platforms deployed at the radio access network are expected to significantly improve quality of service delivered by Application Service Providers (ASPs) in a…
Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing
Jie Xu, Lixing Chen, Shaolei Ren
Mobile edge computing (a.k.a. fog computing) has recently emerged to enable in-situ processing of delay-sensitive applications at the edge of mobile networks. Providing grid power…
Online Learning for Offloading and Autoscaling in Renewable-Powered Mobile Edge Computing
Jie Xu, Shaolei Ren
Mobile edge computing (a.k.a. fog computing) has recently emerged to enable \emph{in-situ} processing of delay-sensitive applications at the edge of mobile networks. Providing grid…
Extending Demand Response to Tenants in Cloud Data Centers via Non-intrusive Workload Flexibility Pricing
Yong Zhan, Mahdi Ghamkhari, Du Xu +2
Participating in demand response programs is a promising tool for reducing energy costs in data centers by modulating energy consumption. Towards this end, data centers can employ…
Energy-Efficient Flow Scheduling and Routing with Hard Deadlines in Data Center Networks
Lin Wang, Fa Zhang, Kai Zheng +3
The power consumption of enormous network devices in data centers has emerged as a big concern to data center operators. Despite many traffic-engineering-based solutions, very litt…
Entry and Spectrum Sharing Scheme Selection in Femtocell Markets
Shaolei Ren, Jaeok Park, Mihaela van der Schaar
Focusing on a femtocell communications market, we study the entrant network service provider's (NSP's) long-term decision: whether to enter the market and which spectrum sharing te…
Business Mode Selection in Digital Content Markets
Shaolei Ren, Jaeok Park, Mihaela van der Schaar
In this paper, we consider a two-sided digital content market, and study which of the two business modes, i.e., Business-to-Customer (B2C) and Customer-to-Customer (C2C), should be…
User Subscription, Revenue Maximization, and Competition in Communications Markets
Shaolei Ren, Jaeok Park, Mihaela van der Schaar
An updated version of this paper (but with a different title) can be found at arXiv:1204.4262
Distributed Power Allocation in Multi-User Multi-Channel Relay Networks
Shaolei Ren, Mihaela van der Schaar
This paper has been withdrawn by the authors as they feel it inappropriate to publish this paper for the time being.