Publication

Conference



[ICC ‘22] Wideband Spectrum Sensing based on Collaborative Multi-Task Learning
W. Zhang, Y. Wang, F. Yu, Z. Qin, X. Chen, and Z. Tian.
The International Conference on Communication, Nov. 2020.

[ICCASP ‘22] Deep Kernel Learning Network with Multiple Learning Paths
P. Xu, Y. Wang, X. Chen, and Z. Tian.
The International Conference on Acoustics, Speech, & Signal Processing, Oct. 2022.

[MLSys ‘22] QuadraLib: A Performant Quadratic Neural Network Library for Architecture Optimization and Design Exploration
Z. Xu, J. Xiong, F. Yu, and X. Chen.
The 5th Conference on Machine Learning and Systems, Aug. 2022.

[MLSys-CI ‘22] A Survey of Multi-Tenant Deep Learning Inference on GPU
Y. Yu, D. Wang, L. Shangguan, M. Zhang, C. Liu, T. Soyata, and X. Chen.
The 5th Conference on Machine Learning and Systems, Workshop on Cloud Intelligence / AIOps, Aug. 2022.

[WebConf-EMDC ‘22] Powering Multi-Task Federated Learning with Competitive GPU Resource Sharing
Y. Yu, F. Yu, Z. Xu, D. Wang, M. Zhang, A. Li, S. Bray, C. Liu, and X. Chen.
The 5th ACM Web Conference, Workshop on Efficiency of Modern Data Centers, Jun. 2022.

[WACV ‘22] SFalCon: Fine-grained Feature Map Sparsity Computing with Decomposed Convolutions for Inference Optimization
Z. Xu, F. Yu, C. Liu, H. Wang, and X. Chen.
The Winter Conference on Applications of Computer Vision, Jan. 2022.

[WACV ‘22] SC-UDA: Style and Content Gap Aware Unsupervised Domain Adaptation for Object Detection
F. Yu, D. Wang, Y. Chen, N. Karianakis, T. Shen, P Yu, D. Lymberopoulos, S. Lu, W. Shi, and X. Chen.
The Winter Conference on Applications of Computer Vision, Jan. 2022.

[ICCAD ‘21] Automated Runtime-Aware Scheduling for Multi-Tenant DNN Inference on GPU
F. Yu, S. Bray, D. Wang, L. Shangguan, X. Tang, C. Liu, and X. Chen.
The 40th International Conference on Computer-Aided Design, Nov. 2021.

[DAC ‘21] Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration
Z. Xu, F. Yu, J. Xiong, and X. Chen.
The 58th Design Automation Conference, Dec. 2021.

[KDD ‘21] Fed2: Feature-Aligned Federated Learning
F. Yu, W. Zhang, Z. Qin, Z. Xu, D. Wang, C. Liu, Z. Tian, and X. Chen.
The 30th ACM SigKDD Conference on Knowledge Discovery and Data Mining, Aug. 2021.

[IBM-AICS ‘20] Exploring the Design Space of Efficient Deep Neural Networks
Z. Xu, J. Xiong, F. Yu, and X. Chen.
The 3rd IBM IEEE CAS/EDS AI Compute Symposium, Nov. 2020.

[SEC ‘20] Exploring the Design Space of Efficient Deep Neural Networks
F. Yu, D. Stamoulis, D. Wang, D. Lymberopoulos, and X. Chen.
The 5th ACM/IEEE Symposium on Edge Computing, No. 10, Nov. 2020.

[SEC ‘20] Exploring Decentralized Collaboration in Heterogeneous Edge Training
X. Chen and Z. Qin.
The 5th ACM/IEEE Symposium on Edge Computing, No. 18, Nov. 2020.

[ECCV ‘20] An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
X. Ma, W. Niu, T. Zhang, S. Liu, S. Lin, H. Li, X. Chen, J. Tang, K. Ma, B. Ren, and Y. Wang.
The 16th European Conference on Computer Vision, Aug. 2020.

[CVPR-V4AS ‘20] Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
F. Yu, D. Wang, Y. Chen, N. Karianakis, P. Yu, D. Lymberopoulos, and X. Chen.
The 33rd IEEE Conference on Computer Vision and Pattern Recognition, Workshop on Vision for all Seasons: Adverse Weather and Lighting Conditions, Jun. 2020.

[DATE ‘20] [Best Paper Award Nomination] AntiDOte: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency
F. Yu, C. Liu, D. Wang, Y. Wang, and X. Chen.
The 23rd International Conference on Design Automation and Test in Europe, Page: 951-956, Mar. 2020.

[DATE ‘20] LanCe: A Comprehensive and Lightweight CNN Defense Methodology against Physical Adversarial Attacks on Embedded Multimedia Applications
F. Yu, Z. Qin, D. Wang, P. Xu, C. Liu, Z. Tian, and X. Chen.
The 23rd International Conference on Design Automation and Test in Europe, Page: 1097-1102, Mar. 2020.

[DATE ‘20] LanCe: A Comprehensive and Lightweight CNN Defense Methodology against Physical Adversarial Attacks on Embedded Multimedia Applications
F. Yu, Z. Qin, D. Wang, P. Xu, C. Liu, Z. Tian, and X. Chen.
The 23rd International Conference on Design Automation and Test in Europe, Page: 1097-1102, Mar. 2020.

[ASP-DAC ‘20] Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra-Efficient DNN Implementation
X. Ma, G. Yuan, S. Lin, C. Ding, F. Yu, T. Liu, W. Wen, X. Chen, and Y. Wang.
The 25th Asia and South Pacific Design Automation Conference, Page: 301-306, Jan. 2020.

[SEC ‘19] Task-Adaptive Incremental Learning for Intelligent Edge Devices
Z. Qin, F. Yu, and X. Chen.
The 4th ACM/IEEE Symposium on Edge Computing, No. 22, Nov. 2019.

[CIKM ‘19] Multi-stage Deep Classifier Cascades for Open World Recognition
X. Guo, A. Alipour-Fanid, L. Wu, H. Purohit, X. Chen, K. Zeng, and Liang Zhao.
The 28th ACM International Conference on Information and Knowledge Management, Page: 179-188, Nov. 2019.

[BMVC ‘19] Functionality-Oriented Convolutional Filter Pruning
Z. Qin, F. Yu, C. Liu, and X. Chen.
The 30th British Machine Vision Conference, No. 92, Sep. 2019.

[IJCAI ‘19] Interpreting and Evaluating Neural Network Robustness
F. Yu, Z. Qin, C. Liu, and X. Chen.
The 28th International Joint Conference on Artificial Intelligence, Page: 4199-4205, Aug. 2019.

[KDD ‘19] Deep Learning Alternating Direction Method of Multipliers
J. Wang, F. Yu, X. Chen, and L. Zhao.
The 28th International Joint Conference on Artificial Intelligence, Page: 111-119, Aug. 2019.

[KDD-AIoT ‘19] DoPa: A Fast and Comprehensive CNN Defense Methodology against Physical Adversarial Attacks
Z. Xu, F. Yu, and X. Chen.
The 25th ACM SigKDD Conference on Knowledge Discovery and Data Mining, Workshop on Artificial Intelligence of Things, No. 3, Aug. 2019.

[DAC ‘19] ReForm: Static and Dynamic Resource-Aware DNN Reconfiguration Framework for Mobile Devices
Z. Xu, F. Yu, C. Liu, and X. Chen.
The 56th Design Automation Conference, Page: 183:1-183:6, Jun. 2019.

[DAC ‘19] MASKER: Adaptive Mobile Security Enhancement against Automatic Speech Recognition in Eavesdropping
F. Yu, Z. Xu, C. Liu, and X. Chen.
The 56th Design Automation Conference, Page: 163:1-163:6, Jun. 2019.

[ASP-DAC ‘19] HAMPER: High-Performance Adaptive Mobile Security Enhancement against Malicious Speech and Image Recognition
Z. Xu, F. Yu, C. Liu, and X. Chen.
The 24th Asia and South Pacific Design Automation Conference, Page: 512-517, Jan. 2019.

[ASP-DAC ‘19] REIN: A Robust Training Method for Enhancing Generalization Ability of Neural Networks in Autonomous Driving Systems
F. Yu, C. Liu, and X. Chen.
The 24th Asia and South Pacific Design Automation Conference, Page: 456-461, Jan. 2019.

[ASP-DAC ‘19] CAPTOR: A Class Adaptive Filter Pruning Framework for Convolutional Neural Networks in Mobile Applications
Z. Qin, F. Yu, C. Liu, and X. Chen
The 24th Asia and South Pacific Design Automation Conference, Page: 444-449, Jan. 2019.

[NIPS-CDNNIA ‘18] Demystifying Neural Network Filter Pruning
Z. Qin, F. Yu, C. Liu, and X. Chen.
The 32nd Conference on Neural Information Processing Systems, Workshop on Compact Deep Neural Networks with Industrial Applications, No.34, Dec. 2018.

[NIPS-CDNNIA ‘18] Distilling Critical Paths in Convolutional Neural Networks
F. Yu, Z. Qin, and X. Chen.
The 32nd Conference on Neural Information Processing Systems, Workshop on Compact Deep Neural Networks with Industrial Applications, No.34, Dec. 2018.

[SEC ‘18] Z Adge: An ADMM-Based Audio Adversarial Example Generation Method
. Qin, F. Yu, C. Liu, Y. Wang, and X. Chen.
The 3th ACM/IEEE Symposium on Edge Computing, Oct. 2018.

[GlobalSIP ‘18] A Hybrid Neural Network Framework and Application to Radar Automatic Target Recognition
Z. Zhang, X. Chen, Z. Tian.
The 6th IEEE Global Conference on Signal and Information Processing, Nov. 2018.

[ISLPED ‘18] DiReCt: Resource-Aware Dynamic Model Reconfiguration for Convolutional Neural Network in Mobile Systems
Z. Xu, Z. Qin, F. Yu, C. Liu, and X. Chen.
The 23rd ACM/IEEE International Symposium on Low Power Electronics and Design, No. 37, Page: 1-6, Jul. 2018.

[ISVLSI ‘18] ReRise: An Adversarial Example Restoration System for Neuromorphic Computing Security
C. Liu, Q. Dong, F. Liu, F. Yu, and X. Chen.
The 17th IEEE Computer Society Annual Symposium on VLSI, Page: 470-475, Jul. 2018.

[DAC-WIP ‘18] DiReCt: Performance-Aware Dynamic Model Reconfiguration for Convolutional Neural Network in Mobile Systems
F. Yu, Q. Dong, and X. Chen.
The 55th Design Automation Conference, WIP, Jun. 2018.

[DAC-WIP ‘18] ASP: A Fast Adversarial Attack Example Generation Framework based on Adversarial Saliency Prediction
Z. Xu, F. Yu, and X. Chen.
The 55th Design Automation Conference, WIP, Jun. 2018.

[ICCAD ‘17] VoCaM: Visualization Oriented Convolutional Neural Network Acceleration on Mobile Systems
Z. Qin, Z. Xu, Q. Dong, Y. Chen, and Xiang Chen.
The 36th International Conference on Computer-Aided Design, Page: 835-840, Nov. 2017.

[ICCAD ‘17] AdaLearner: An Adaptive Distributed Mobile Learning System for Neural Networks
J. Mao, Z. Qin, Z. Xu, K. Nixon, X. Chen, H. Li, and Y. Chen.
The 36th International Conference on Computer-Aided Design, Page: 291-296, Nov. 2017.

[ICCAD ‘17] MeDNN: A Distributed Mobile System with Enhanced Partition and Deployment for Large-Scale DNNs
J. Mao, Z. Yang, W. Wen, C. Wu, L. Song, K. Nixon, X. Chen, H. Li, and Y. Chen.
The 36th International Conference on Computer-Aided Design, Page: 751-756, Nov. 2017.

[SoCC ‘17] MobiCore: An Adaptive Hybrid Approach for Power-Efficient CPU Management on Android Devices。
L. Broyde, K. Nixon, X. Chen, and H. Li.
The 30th IEEE International System-On-Chip Conference, Page: 221-226, Sep. 2017.

[DATE ‘17] [Best Paper Award] MoDNN: Local Distributed Mobile Computing System for Deep Neural Network
J. Mao, X. Chen, K. Nixon, C. Krieger, and Y. Chen.
The 20th International Conference on Design Automation and Test in Europe, Page: 1396-1401, Mar. 2017.

[ICCAD ‘16] [Best Paper Nomination] Scope – Quality Retaining Display Rendering Workload Scaling based on User-Smartphone Distance
K. Nixon, X. Chen, and Y. Chen.
The 35th International Conference on Computer-Aided Design, Page: 1-6, Nov. 2016.

[SoCC ‘16] Practical Power Consumption Analysis with Current Smartphones
X. Chen, K. Nixon, and Y. Chen.
The 29th IEEE International System-on-Chip Conference, Page: 333-337, Oct. 2016.

[DAC ‘16] MORPh: Mobile OLED-friendly Recording and Playback System for Low Power Video Streaming
X. Chen, J. Mao, J. Gao, K. Nixon, and Y. Chen.
The 53rd Design Automation Conference, Page: 1-6, Jun. 2016.

[ASP-DAC ‘16] Footfall: GPS Polling Scheduler for Power Saving on Wearable Devices
K. Nixon, X. Chen, and Y. Chen.
The 21st Asia and South Pacific Design Automation Conference, Page: 563-568, Jan. 2016.

[ASP-DAC ‘16] SlowMo: Enhancing Mobile Gesture-Based Authentication Schemes via Sampling Rate Optimization
K. Nixon, X. Chen, and Y. Chen.
The 21st Asia and South Pacific Design Automation Conference, Page: 462-467, Jan. 2016.

[DAC ‘15] DaTuM: Dynamic Tone Mapping Technique for OLED Display Power Saving based on Video Classification
X. Chen, C. J. Xue, and Y. Chen.
The 52nd Design Automation Conference, Page: 8-12, Jun. 2015.

[USENIX HotPower ‘14] FingerShadow: An OLED Power Optimization based on Smartphone Touch Interactions
X. Chen, K. W. Nixon, H. Zhou, Y. Liu, and Y. Chen.
The 6th International Workshop on Power-Aware Computing and System, No. 6, Oct. 2014.

[USENIX HotPower ‘14] Mobile GPU Power Consumption Reduction via Dynamic Resolution and Frame Rate Scaling
K. W. Nixon, X. Chen, H. Zhou, Y. Liu, and Y. Chen.
The 6th International Workshop on Power-Aware Computing and System, No. 5, Oct. 2014.

[DAC ‘14] Demystify Smartphone Power Consumption: The Evolution of Smartphone Communication Modules
X. Chen, M. Dong, C. Zhang, and Y. Chen.
The 51st Design Automation Conference, Page: 1-5, Jun. 2014.

[CODES+ISSS ‘13] Online OLED Dynamic Voltage Scaling for Video Streaming Applications on Mobile Devices
M. Zhao, X. Chen, Y. Chen, and C. J. Xue.
International Conference on Hardware/Software Codesign and System Synthesis, Page: 1-10, Oct. 2013.

[RTSS ‘13] Online OLED Dynamic Voltage Scaling for Video Streaming Applications on Mobile Devices
M. Zhao, X. Chen, Y. Chen, and C. J. Xue.
IEEE Real-Time Systems Symposium, Volume 10, Issue 2, Page: 18, Jul. 2013.

[DAC-WIP ‘13] Dynamic Tone Mapping on OLED Display Based on Video Classification
X. Chen, Z. Ma, F. C. A. Fernandes, C. J. Xue, and Y. Chen.
The 50th Design Automation Conference, Work-in-Progress Workshop, Jun. 2013.

[DAC-WIP ‘13] P-Spectrum: A Personalized Smartphone Power Management Technique based on Real-time Battery and User Behavior Monitoring
X. Chen, and H. Li.
The 50th Design Automation Conference, Work-in-Progress Workshop, Jun. 2013.

[DAC-WIP ‘13] The Invisible Shield: User Classification and Authentication for Mobile Device based on Gesture Recognition
K. Nixon, X. Chen, Z. Mao, K. Li, and Y. Chen.
The 50th Design Automation Conference, Work-in-Progress Workshop, Jun. 2013.

[HotMobile ‘13] How is Energy Consumed in Smartphone Display Applications?
X. Chen, Y. Chen, Zhan Ma, and Felix C. A. Fernandes.
The 16th International Workshop on Mobile Computing Systems and Applications, No. 3, Feb. 2013.

[ASP-DAC ‘13] Mobile User Classification and Authorization based on Gesture Usage Recognition
K. Nixon, X. Chen Z. H. Mao, Y. Chen, and K. Li.
The 18th Asia and South Pacific Design Automation Conference, Page: 384-389, Jan. 2013.

[ICCAD ‘12] Mobile Devices User – The Subscriber and also the Publisher of Real-Time OLED Display Power Management Plan
X. Chen, C. J. Xue, and Y. Chen.
The 31st International Conference on Computer-Aided Design, Page: 687-690, Nov. 2012.

[ICCAD ‘12] Active Compensation Technique for the Thin-Film Transistor Variations and OLED Aging of Mobile Device Displays
X. Chen, B. Liu, M. Zhao, C. J. Xue, X. Guo, and Y. Chen.
The 31st International Conference on Computer-Aided Design, Page: 516-522, Nov. 2012.

[DAC ‘12] Quality-retaining OLED Dynamic Voltage Scaling for Video Streaming Applications on Mobile Devices
X. Chen, M. Zhao, J. Zeng, J. Xue, and Y. Chen.
The 49th Design Automation Conference, Page: 1000-1005, Jun. 2012.

[ASP-DAC ‘12] Fine-grained Dynamic Voltage Scaling on OLED Display
X. Chen, J. Zeng, Y. Chen, and H. Li.
The 17th Asia and South Pacific Design Automation Conference, Page: 807-812, Jan. 2012.

[CICC ‘11] A 1.0V 45nm Nonvolatile Magnetic Latch Design and Its Robustness Analysis
P. Wang, X. Chen, Y. Chen, H. Li, S. Kang, X. Zhu, and W. Wu.
IEEE Custom Integrated Circuits Conference, Page: 1-4, Sep. 2011.


Journal



[IEEE-TC ‘22] HeliosX: Heterogeneity-Aware Federated Learning for Dynamic Edge Collaboration Management
Z. Xu, F. Yu, J. Xiong, and X. Chen.
IEEE Transactions on Computers, in press.

[IEEE-TC ‘22] Fed2X: Feature-Aligned Large-Scale Federated Learning Systems
F. Yu, W. Zhang, Z. Qin, Z. Xu, D. Wang, C. Liu, Z. Tian, and X. Chen.
IEEE Transactions on Computers, in press.

[IEEE-TC ‘22] FalConX: Fine-grained Feature Map Sparsity Computing with Decomposed Convolutions
Z. Xu, F. Yu, C. Liu, and X. Chen.
IEEE Transactions on Computers, in press.

[ACM-TECS ‘22] LanCeX: A Versatile and Lightweight Defense Method against Condensed Adversarial Attacks
Z. Xu, F. Yu, and X. Chen.
ACM Transactions on Embedded Computing Systems, Aug. 2022.

[IEEE-TCAD ‘22] AntiDoteX: Attention- based Neural Network Runtime Efficiency Dynamic Optimization
F. Yu, C. Liu, D. Wang, Y. Wang and X. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Jan. 2022.

[JMLR ‘21] COKE: Communication-Censored Decentralized Kernel Learning
P. Xu, Y. Wang, X. Chen, and Z. Tian.
Journal of Machine Learning Research, Oct. 2021.

[IEEE-TCAD ‘21] CaptorX: A Class- Adaptive Convolutional Neural Network Reconfiguration Framework
Z. Qin, F. Yu, Z. Xu, C. Liu, and X. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Feb. 2021.

[IEEE-TCAD ‘20] DiViSi: Quality-retaining Dynamic Driver Voltage Scaling for Organic Light Emitting Diode Displays
X. Chen, W. Zhang, C. J. Xue, H. Li, and Y. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Nov. 2020.

[IEEE-TCAD ‘20] REIN the RobuTS: Robust DNN-based Image Recognition in Autonomous Driving Systems
F. Yu, Z. Qin, C. Liu, D. Wang, and X. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Oct. 2020.

[IEEE-TCAD ‘20] DiReCtX: Dynamic Resource-Aware CNN Reconfiguration Framework for Real-Time Mobile Application
Z. Xu, F. Yu, C. Liu, and X. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, May 2020.

[AMC-MFC ‘20] How Convolutional Neural Networks See the World — A Survey of Convolutional Neural Network Visualization Methods
Z. Xu, F. Yu, C. Liu, and X. Chen.
Advances in Mathematics of Communications Journal on Mathematical Foundations of Computing, Vol. 1, Iss. 2, No. 149, pp. 149∼180, May 2018.

[ACM-ETCS ‘20] Non-volatile Memories as the Data Storage System for Implantable ECG Recorder
Z. Sun, X. Chen, Y. Zhang, H. Li, and Y. Chen.
ACM Journal on Emerging Technologies in Computing Systems, Vol. 8, Iss. 2, No. 13, pp. 1∼16, Jun. 2012.


Arxiv



[arXiv:2111.14247] A Survey of Large-Scale Deep Learning Serving System Optimization: Challenges and
Opportunities

F. Yu, D. Wang, L. Shangguan, M. Zhang, X. Tang, C. Liu, and X. Chen. Nov. 2021.

[arXiv:2011.03897] Towards Latency-Aware DNN Optimization with GPU Runtime Analysis and Tail Effect Elimination
C. Liu, Q. Dong, F. Liu, F. Yu, and X. Chen. Nov. 2020.

[arXiv:2008.06767] Heterogeneous Federated Learning
F. Yu, W. Zhang, Z. Qin, Z. Xu, D. Wang, C. Liu, Z. Tian, and X. Chen. Aug. 2020.

[arXiv:2001.10133] COKE: Communication-Censored Kernel Learning for Decentralized Non-parametric Learning
P. Xu, Y. Wang, X. Chen, and Z. Tian. Jan. 2020.

[arXiv:1910.03122] Task-Adaptive Incremental Learning for Intelligent Edge Devices
Z. Qin, F. Yu, and X. Chen. Oct. 2019.

[arXiv:1811.04187] The Global Convergence of the Alternating Minimization Algorithm for Deep Neural Network Problems
J. Wang, Y. Fu, X. Chen, and L. Zhao. Nov. 2018.

[arXiv:1810.07378] Progressive Weight Pruning of Deep Neural Networks using ADMM
S. Ye, T. Zhang, K. Zhang, J. Li, K. Xu, Y. Yang, F. Yu, J. Tang, M. Faradad, S. Liu, X. Chen, X. Lin, and Y. Wang. Oct. 2018.

[arXiv:1810.07322] Functionality-Oriented Convolutional Filter Pruning
Q. Zhu, F. Yu, C. Liu, L. Zhao, and X. Chen. Oct. 2018.

[arXiv:1810.00144] Interpreting Adversarial Robustness: A View from Decision Surface in Input Space
F. Yu, C. Liu, Y. Wang, L. Zhao, and X. Chen. Oct. 2018.

[arXiv:1809.10795] A Hybrid Neural Network Framework and Application to Radar Automatic Target Recognition
Z. Zhang, X. Chen, and Z. Tian. Sep. 2018.

[arXiv:1809.01697] HASP: A High-Performance Adaptive Mobile Security Enhancement Against Malicious Speech Recognition
Z. Xu, F. Yu, C. Liu, and X. Chen. Sep. 2018.

[arXiv:1805.09370] Towards Robust Training of Neural Networks by Regularizing Adversarial Gradients
F. Yu, Z. Xu, Y. Wang, C. Liu, and X. Chen. Sep. 2018.