1k citations · 2.3k across the 48 of their papers we have counts for
49 papers
Knowledge-Aware Modeling with Frequency Adaptive Learning for Battery Health Prognostics
Vijay Babu Pamshetti, Wei Zhang, Sumei Sun +3
Battery health prognostics are critical for ensuring safety, efficiency, and sustainability in modern energy systems. However, it has been challenging to achieve accurate and robus…
Towards a Systematic Survey for Carbon Neutral Data Centers
Zhiwei Cao, Xin Zhou, Han Hu +2
Data centers are carbon-intensive enterprises due to their massive energy consumption, and it is estimated that data center industry will account for 8\% of global carbon emissions…
ModelCI-e: Enabling Continual Learning in Deep Learning Serving Systems
Yizheng Huang, Huaizheng Zhang, Yonggang Wen +2
MLOps is about taking experimental ML models to production, i.e., serving the models to actual users. Unfortunately, existing ML serving systems do not adequately handle the dynami…
Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning
Weiming Zhuang, Xin Gan, Yonggang Wen +3
Unsupervised domain adaptation has been widely adopted to generalize models for unlabeled data in a target domain, given labeled data in a source domain, whose data distributions d…
ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale
Yuanming Li, Huaizheng Zhang, Shanshan Jiang +3
AI engineering has emerged as a crucial discipline to democratize deep neural network (DNN) models among software developers with a diverse background. In particular, altering thes…
EasyFL: A Low-code Federated Learning Platform For Dummies
Weiming Zhuang, Xin Gan, Yonggang Wen +1
Academia and industry have developed several platforms to support the popular privacy-preserving distributed learning method -- Federated Learning (FL). However, these platforms ar…
A Serverless Cloud-Fog Platform for DNN-Based Video Analytics with Incremental Learning
Huaizheng Zhang, Meng Shen, Yizheng Huang +4
DNN-based video analytics have empowered many new applications (e.g., automated retail). Meanwhile, the proliferation of fog devices provides developers with more design options to…
On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times
Yao Fu, Yipeng Zhou, Di Wu +3
In spite that Federated Learning (FL) is well known for its privacy protection when training machine learning models among distributed clients collaboratively, recent studies have…
Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control
Duc Van Le, Rongrong Wang, Yingbo Liu +3
Air free-cooled data centers (DCs) have not existed in the tropical zone due to the unique challenges of year-round high ambient temperature and relative humidity (RH). The increas…
Privacy-preserving Collaborative Learning with Automatic Transformation Search
Wei Gao, Shangwei Guo, Tianwei Zhang +3
Collaborative learning has gained great popularity due to its benefit of data privacy protection: participants can jointly train a Deep Learning model without sharing their trainin…
InferBench: Understanding Deep Learning Inference Serving with an Automatic Benchmarking System
Huaizheng Zhang, Yizheng Huang, Yonggang Wen +2
Deep learning (DL) models have become core modules for many applications. However, deploying these models without careful performance benchmarking that considers both hardware and…
Performance Optimization for Federated Person Re-identification via Benchmark Analysis
Weiming Zhuang, Yonggang Wen, Xuesen Zhang +5
Federated learning is a privacy-preserving machine learning technique that learns a shared model across decentralized clients. It can alleviate privacy concerns of personal re-iden…
Distributed Energy Trading and Scheduling among Microgrids via Multiagent Reinforcement Learning
Guanyu Gao, Yonggang Wen, Xiaohu Wu +1
The development of renewable energy generation empowers microgrids to generate electricity to supply itself and to trade the surplus on energy markets. To minimize the overall cost…
Hysia: Serving DNN-Based Video-to-Retail Applications in Cloud
Huaizheng Zhang, Yuanming Li, Qiming Ai +4
Combining \underline{v}ideo streaming and online \underline{r}etailing (V2R) has been a growing trend recently. In this paper, we provide practitioners and researchers in multimedi…
MLModelCI: An Automatic Cloud Platform for Efficient MLaaS
Huaizheng Zhang, Yuanming Li, Yizheng Huang +3
MLModelCI provides multimedia researchers and developers with a one-stop platform for efficient machine learning (ML) services. The system leverages DevOps techniques to optimize,…
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Jie Gui, Zhenan Sun, Yonggang Wen +2
Generative adversarial networks (GANs) are a hot research topic recently. GANs have been widely studied since 2014, and a large number of algorithms have been proposed. However, th…
Look, Read and Feel: Benchmarking Ads Understanding with Multimodal Multitask Learning
Huaizheng Zhang, Yong Luo, Qiming Ai +1
Given the massive market of advertising and the sharply increasing online multimedia content (such as videos), it is now fashionable to promote advertisements (ads) together with t…
Kalibre: Knowledge-based Neural Surrogate Model Calibration for Data Center Digital Twins
Ruihang Wang, Xin Zhou, Linsen Dong +5
Computational fluid dynamics (CFD) model has been widely used for prototyping data centers. Evolving it to high-fidelity {\em digital twin} is desirable for the management and oper…
A Survey of Predictive Maintenance: Systems, Purposes and Approaches
Tianwen Zhu, Yongyi Ran, Xin Zhou +1
This paper highlights the importance of maintenance techniques in the coming industrial revolution, reviews the evolution of maintenance techniques, and presents a comprehensive li…
Soft-ranking Label Encoding for Robust Facial Age Estimation
Xusheng Zeng, Changxing Ding, Yonggang Wen +1
Automatic facial age estimation can be used in a wide range of real-world applications. However, this process is challenging due to the randomness and slowness of the aging process…
Large Margin Multi-modal Multi-task Feature Extraction for Image Classification
Yong Luo, Yonggang Wen, Dacheng Tao +2
The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many…
Heterogeneous Multi-task Metric Learning across Multiple Domains
Yong Luo, Yonggang Wen, Dacheng Tao
Distance metric learning (DML) plays a crucial role in diverse machine learning algorithms and applications. When the labeled information in target domain is limited, transfer metr…
Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain
Yong Luo, Yonggang Wen, Tongliang Liu +1
The goal of transfer learning is to improve the performance of target learning task by leveraging information (or transferring knowledge) from other related tasks. In this paper, w…
Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification
Yong Luo, Dacheng Tao, Chang Xu +3
In computer vision, image datasets used for classification are naturally associated with multiple labels and comprised of multiple views, because each image may contain several obj…