A Domain-Specific System-On-Chip Design for Energy Efficient Wearable Edge AI Applications ISLPED ’22, August 1–3, 2022, Boston, MA, USA Yigit Tuncel, Anish Krishnakumar, Aishwarya L. Chithra, Younghyun Kim, and Umit Ogras
Latent Weight-based Pruning for Small Binary Neural Networks ASPDAC ’23, January 16–19, 2023, Tokyo, Japan Tianen Chen, Noah Anderson, and Younghyun Kim
On-Device Training Under 256KB Memory
Ji Lin1∗ Ligeng Zhu1∗ Wei-Ming Chen1 Wei-Chen Wang1 Chuang Gan2 Song Han1
1MIT 2MIT-IBM Watson AI Lab
https://tinyml.mit.edu/on-device-training
36th Conference on Neural Information Processing Systems (NeurIPS 2022).
SHEPHERD: Serving DNNs in the Wild
Hong Zhang University of Waterloo Yupeng Tang Yale University
Anurag Khandelwal Yale University Ion Stoica UC Berkeley
NSDI23
Yanpeng Yu, Seung-seob Lee, Anurag Khandelwal, and Lin Zhong, "GCS: Generalized cache coherence for efficient synchronization," arXiv, January 2023. (under view by SOSP)
R. Petri, G. L. Zhang, Y. Chen, U. Schlichtmann, and B. Li, "PowerPruning: Selecting Weights and Activations for Power-Efficient Neural Network Acceleration," 60th ACM/IEEE Design Automation Conference (DAC), accepted, to appear 2023.
"Adaptive Graph Spatial-Temporal Transformer Network for Traffic Forecasting", CIKM 2022.
"Low-cost soil carbon sensing with smartphones", paper draft in progress (to be submitted).
Z. Wang, D. Kilper, and T. Chen, “Transfer learning-based ROADM EDFA wavelength dependent gain prediction using minimized data collection,” in Proc. IEEE/Optica Optical Fiber Communication Conference (OFC’23), Paper Th2A.1, 2023.
E. Akinrintoyo, Z. Wang, B. Lantz, T. Chen, and D. Kilper, “Reconfigurable topology testbeds: A new approach to optical system experiments,” Optical Fiber Technology, Special Issue on Novel Optical Networking Architectures and Open Interfaces for 5G and Future 6G Networks (OFT) (invited), vol. 76, pp. 103243, Mar. 2023.
D. Hunt, K. Angel, Z. Qi, T. Chen, and M. Pajic, “Black-Box Physical Layer Attacks on Millimeter-Wave Automotive FMCW Radars” under submission, 2023.
‘Transfer Learning for Individual Treatment Effect Estimation’ by Ahmed Aloui, Juncheng Dong, Cat Phuoc Le, and Vahid Tarokh. (submitted to UAI 2023)
‘Individual Tail Treatment Effect Estimation’ by Ahmed Aloui, Ali Hasan, Yuting Ng, Miroslav Pajic, and Vahid Tarokh. (submitted to UAI 2023)
‘Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-Grained Environments’ by Jingyang Zhang, Nathan Inkawhich, Randolph Linderman, Yiran Chen, Hai Li. (Accepted by WACV 2023)
‘Fine-Grain Inference on Out-of-Distribution Data with Hierarchical Classification’ by Randolph Linderman, Jingyang Zhang, Nathan Inkawhich, Hai Li, Yiran Chen. (Submitted to CoLLAs 2023)
Yuchen Yang, Bo Hui, Haolin Yuan, Neil Gong, and Yinzhi Cao. "PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation". In USENIX Security Symposium, 2023.
Jinghuai Zhang, Jinyuan Jia, Hongbin Liu, and Neil Zhenqiang Gong. "PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees". In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
Xiaoyu Cao, Jinyuan Jia, Zaixi Zhang, and Neil Zhenqiang Gong. "FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information". In IEEE Symposium on Security and Privacy, 2023.
Xiaoyu Cao, Zaixi Zhang, Jinyuan Jia, and Neil Zhenqiang Gong. "FLCert: Provably Secure Federated Learning against Poisoning Attacks". IEEE Transactions on Information Forensics and Security (TIFS), 2022.
Haolin Yuan, Bo Hui, Yuchen Yang, Philippe Burlina, Neil Zhenqiang Gong, and Yinzhi Cao. "Addressing Heterogeneity in Federated Learning via Distributional Transformation". In European Conference on Computer Vision (ECCV), 2022.
Sun, Jingwei, et al. "Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties." Submitted to ICCV2023.
J. Centers and J. Krolik, "VIBRATIONAL RADAR BACKSCATTER COMMUNICATIONS THEORY AND BOUND," IEEE Transactions on Radar Systems, accepted and in press, to appear 2023.
J. Centers and J. Krolik, "MULTI-USER METHODS FOR VIBRATIONAL RADAR BACKSCATTER COMMUNICATIONS," 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing, to appear, June 2023
J. Centers and J. Krolik, "VIBRATIONAL RADAR BACKSCATTER COMMUNICATION USING RESONANT TRANSPONDING SURFACES," 2022 IEEE 12th Sensor Array and Multichannel Sig. Proc. Workshop, pp. 71-75, 2022.
"Adaptive Graph Spatial-Temporal Transformer Network for Traffic Forecasting", CIKM 2022.
"Low-cost soil carbon sensing with smartphones", paper draft in progress (to be submitted).
“Prefetching Using Principles of Hippocampal-Neocortical Interaction”, Michael Wu, Ketaki Joshi, Andrew Sheinberg, Guilherme Cox, Anurag Khandelwal, Raghavendra Pothukuchi, Abhishek Bhattacharjee, HotOS ’23.
[GHH21] Peizhen Guo, Bo Hu, and Wenjun Hu. Mistify: Automating DNN model porting for on- device inference at the edge. In Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation, April 2021.
[GHH22] Peizhen Guo, Bo Hu, and Wenjun Hu. Sommelier: Curating DNN models for the masses. In SIGMOD ’22: Proceedings of the 2022 International Conference on Management of Data, pages 1876–1890, June 2022.
[HGH22] Bo Hu, Peizhen Guo, and Wenjun Hu. Video-zilla: An indexing layer for large-scale video analytics. In SIGMOD ’22: Proceedings of the 2022 International Conference on Management of Data, pages 1905–1919, June 2022.
Adaptive uplink data compression in spectrum crowdsensing systems
Y Zeng, R Calvo-Palomino, D Giustiniano, G Bovet, S Banerjee
IEEE/ACM Transactions on Networking
1 2023
Online Federated Learning based Object Detection across Autonomous Vehicles in a Virtual World
S Dai, SMI Alam, R Balakrishnan, K Lee, S Banerjee, N Himayat
2023 IEEE 20th Consumer Communications & Networking Conference (CCNC), 919-920
2023
{OpenLoRa}: Validating {LoRa} Implementations through an Extensible and Open-sourced Framework
M Mishra, D Koch, MO Shahid, B Krishnaswamy, K Chintalapudi, ...
20th USENIX Symposium on Networked Systems Design and Implementation (NSDI ...
2023
μCity: a miniatured autonomous vehicle testbed
J Tabor, S Dai, V Sreenivasan, S Banerjee
Proceedings of the 17th ACM Workshop on Mobility in the Evolving Internet ...
2022
Network-side digital contact tracing on a large university campus
ML Malloy, L Hartung, S Wangen, S Banerjee
Proceedings of the 28th Annual International Conference on Mobile Computing ...
2 2022
A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification
Ge Gao1 , Qitong Gao2 , Xi Yang1 , Miroslav Pajic2 and Min Chi1
1Department of Computer Science, North Carolina State University, USA
2Department of Electrical and Computer Engineering, Duke University, USA
{ggao5, yxi2, mchi}@ncsu.edu, {qitong.gao, miroslav.pajic}@duke.edu
VARIATIONAL LATENT BRANCHING MODEL FOR OFF-POLICY EVALUATION
Qitong Gao∗ Ge Gao† Min Chi† Miroslav Pajic∗
Security Analysis of Camera-LiDAR Fusion Against Black-Box Attacks on Autonomous Vehicles
R. Spencer Hallyburton Duke University Yupei Liu Duke University Yulong Cao University of Michigan Z. Morley Mao University of Michigan Miroslav Pajic Duke University
Learning-Based Vulnerability Analysis of Cyber-Physical Systems
Amir Khazraei Duke University Spencer Hallyburton Duke University Qitong Gao Duke University Yu Wang University of Florida Miroslav Pajic Duke University
GRADIENT IMPORTANCE LEARNING FOR INCOMPLETE OBSERVATIONS
Qitong Gao Dong Wang Joshua D. Amason Siyang Yuan Chenyang Tao
Ricardo Henao Majda Hadziahmetovic Lawrence Carin,† Miroslav Pajic
AVstack: An Open-Source, Reconfigurable Platform for Autonomous Vehicle Development
R. Spencer Hallyburton Shucheng Zhang Miroslav Pajic
Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease Treatment
Qitong Gao Stephen L. Schmidt Afsana Chowdhury Guangyu Feng Jennifer J. Peters Katherine Genty Warren M. Grill Dennis A. Turner Miroslav Pajic
Resiliency of Nonlinear Control Systems to Stealthy Sensor Attacks
Amir Khazraei and Miroslav Pajic
Resiliency of Perception-Based Controllers Against Attacks
Amir Khazraei Henry Pfister Miroslav Pajic
Optimal Myopic Attacks on Nonlinear Estimation
R. Spencer Hallyburton, Amir Khazraei, and Miroslav Pajic
A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification
Ge Gao1 , Qitong Gao2 , Xi Yang1 , Miroslav Pajic2 and Min Chi1
Learning Monotone Dynamics by Neural Networks
Yu Wang, Qitong Gao, and Miroslav Pajic
Individual Tail Treatment Effect Estimation
Ahmed Aloui1 Ali Hasan2 Yuting Ng1 Miroslav Pajic1 Vahid Tarokh1
Transfer Learning for Individual Treatment Effect Estimation
Ahmed Aloui1 Juncheng Dong1 Cat P. Le1 Vahid Tarokh1
Softly, Deftly, Scrolls Unfurl Their Splendor: Rolling Flexible Surfaces for Wideband Wireless
Ruichun Ma R. Ivan Zelaya Wenjun Hu
FLCert: Provably Secure Federated Learning against Poisoning Attacks
Xiaoyu Cao, Zaixi Zhang, Jinyuan Jia, and Neil Zhenqiang Gong, Member, IEEE
PRIVATEFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation
Yuchen Yang, Bo Hui, Haolin Yuan, Neil Gong, and Yinzhi Cao
PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees
Jinghuai Zhang Jinyuan Jia Hongbin Liu Neil Zhenqiang Gong
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information
Xiaoyu Cao∗ Jinyuan Jia∗ Zaixi Zhang+ Neil Zhenqiang Gong∗
∗Duke University +University of Science and Technology of China
Addressing Heterogeneity in Federated Learning via Distributional Transformation
Haolin Yuan1, Bo Hui1, Yuchen Yang1, Philippe Burlina1;2,
Neil Zhenqiang Gong3, and Yinzhi Cao1
You Can’t See Me: Physical Removal Attacks on LiDAR-based Autonomous Vehicles Driving Frameworks
Yulong Cao
University of Michigan
S. Hrushikesh Bhupathiraju
University of Florida
Pirouz Naghavi
University of Florida
Takeshi Sugawara
The University of Electro-Communications
Z. Morley Mao
University of Michigan
Sara Rampazzi
University of Florida
Vivisecting Mobility Management in 5G Cellular Networks
Ahmad Hassan†, Arvind Narayanan†, Anlan Zhang†, Wei Ye†, Ruiyang Zhu‡, Shuowei Jin‡,
Jason Carpenter†, Z. Morley Mao‡, Feng Qian†, Zhi-Li Zhang†
A Spectral View of Randomized Smoothing under Common Corruptions: Benchmarking and
Improving Certified Robustness
Jiachen Sun1 , Akshay Mehra2, Bhavya Kailkhura3, Pin-Yu Chen4 , Dan
Hendrycks5, Jihun Hamm2, and Z. Morley Mao1
PACT: Scalable, Long-Range Communication for Monitoring and Tracking Systems Using Battery-less Tags
YAMAN SANGAR , University of Wisconsin-Madison, USA
YOGANAND BIRADAVOLU , University of Wisconsin-Madison, USA
KAI PEDERSON , University of Wisconsin-Madison, USA
VAISHNAVI RANGANATHAN , Microsoft Research, USA
BHUVANA KRISHNASWAMY , University of Wisconsin-Madison, USA
OpenLoRa: Validating LoRa Implementations through an Extensible and Open-sourced Framework
Manan Mishra, Daniel Koch, Muhammad Osama Shahid, and Bhuvana
Krishnaswamy, University of Wisconsin-Madison; Krishna Chintalapudi,
Microsoft Research; Suman Banerjee, University of Wisconsin-Madison
https://www.usenix.org/conference/nsdi23/presentation/mishra
Spreading Factor Detection for low-cost Adaptive Data Rate in LoRaWAN Gateways
Daniel Jay Koch
University of Wisconsin-Madison
Muhammad Osama Shahid
University of Wisconsin-Madison
Bhuvana Krishnaswamy
University of Wisconsin-Madison
Incentive Mechanism Design for Unbiased Federated Learning with Randomized
Client Participation
Bing Luo∗, Yutong Feng†, Shiqiang Wang§, Jianwei Huang†‡, Leandros Tassiulas¶
Adaptive Graph Spatial-Temporal Transformer Network for Traffic Flow Forecasting
Aosong Feng
Leandros Tassiulas
AdaptSLAM: Edge-Assisted Adaptive SLAM with Resource Constraints via Uncertainty Minimization
Ying Chen, Hazer Inaltekin†, Maria Gorlatova
Ambient Intelligence for Next-Generation AR
Tim Scargill, Sangjun Eom, Ying Chen, Maria Gorlatova
Transfer Learning-based ROADM EDFA Wavelength Dependent Gain Prediction
Using Minimized Data Collection
ZehaoWang1, Dan Kilper2, and Tingjun Chen1
(INVITED)Reconfigurable topology testbeds: A new approach to optical system experiments
Emmanuel Akinrintoyo a, Zehao Wang b, Bob Lantz c, Tingjun Chen b, Dan Kilper a
A Domain-Specific System-On-Chip Design for Energy Efficient Wearable Edge AI Applications
Yigit Tuncel
Anish Krishnakumar
Aishwarya L. Chithra
Younghyun Kim
Umit Ogras
LatentWeight-based Pruning for Small Binary Neural Networks
Tianen Chen
Noah Anderson
Younghyun Kim
[Ref A] A. Wang, V. V. Ramaswamy and O. Russakovsky. “Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation.” Conference on Fairness, Accountability and Transparency (FAccT), 2022.
[Ref B] N. Meister*, D. Zhao*, A. Wang, V. V. Ramaswamy, R. Fong and O. Russakovsky. Gender artifacts in visual datasets. Under Review; pre-print available at https://arxiv.org/abs/2206.09191.
[RefC] A. Wang and O. Russakovsky. “Overcoming Bias in Pretrained Models by Manipulating the Finetuning Dataset.” Under review; pre-print is available at https://arxiv.org/abs/2303.06167
[RefD] J. Chung, Y. Wu and O. Russakovsky. Enabling Detailed Action Recognition Evaluation Through Video Dataset Augmentation. Neural Information Processing Systems (NeurIPS) Datasets&Benchmarks Track, 2022.
[RefE] V. V. Ramaswamy, S. S. Y. Kim, R. Fong and O. Russakovsky. Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability. Computer Vision and Pattern Recognition (CVPR), 2023.
[RefF] V. V. Ramaswamy, S. S. Y. Kim, R. Fong and O. Russakovsky. UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs. Under review; pre-print is available at https://arxiv.org/abs/2303.15632
[RefG] W. Yang*, B. Zhang* and O. Russakovsky. Rethinking Out-of-Distribution Detection: The Model Perspective. Under review.
[RefH] Z. Deng and O. Russakovsky. Remember the past: Distilling datasets into addressable memories for neural networks. Neural Information Processing Systems (NeurIPS), 2022.
