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2020 – today
- 2024
[j19]Peng Ye, Yuanfang Chen
, Sihang Ma, Feng Xue, Noël Crespi, Xiaohan Chen, Xing Fang:
Security in Transformer Visual Trackers: A Case Study on the Adversarial Robustness of Two Models. Sensors 24(14): 4761 (2024)- [j18]Tao Wen, Xiaohan Chen, Dingcheng Zhang, Clive Roberts, Baigen Cai:
A Sequential and Asynchronous Federated Learning Framework for Railway Point Machine Fault Diagnosis With Imperfect Data Transmission. IEEE Trans. Ind. Informatics 20(6): 8828-8837 (2024) - [j17]Xiaohan Zhang, Peng Liu, Bohao Lu, Yang Wang, Xiaohan Chen, Yanxin Zhang, Zhi Wang:
MTSFBet: A Hand-Gesture-Recognition-Based Identity Authentication Approach for Passive Keyless Entry Against Relay Attack. IEEE Trans. Mob. Comput. 23(2): 1902-1913 (2024) - [i26]Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin:
Rethinking the Capacity of Graph Neural Networks for Branching Strategy. CoRR abs/2402.07099 (2024) - [i25]Xiaohan Chen, Jialin Liu, Wotao Yin:
Learning to optimize: A tutorial for continuous and mixed-integer optimization. CoRR abs/2405.15251 (2024) - [i24]Ziang Chen, Xiaohan Chen, Jialin Liu, Xinshang Wang, Wotao Yin:
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs. CoRR abs/2406.05938 (2024) - 2023
- [j16]Gongchen Zhang, Chenyu Zhu, Xiaohan Chen, Jifang Yan, Dongyu Xue, Zixuan Wei, Guohui Chuai, Qi Liu:
Systematic Exploration of Optimized Base Editing gRNA Design and Pleiotropic Effects with BExplorer. Genom. Proteom. Bioinform. 21(6): 1237-1245 (2023) - [j15]Xiaohan Chen, Rui Yang, Yihao Xue, Chao Yang, Baoye Song, Maiying Zhong:
A novel momentum prototypical neural network to cross-domain fault diagnosis for rotating machinery subject to cold-start. Neurocomputing 555: 126656 (2023) - [j14]Yihui Li, Jiajun Wu, Xiaohan Chen, Yisheng Guan, Haifei Zhu:
TMG: A topology-based motion generalization method with spatial relationship preservation. Robotics Auton. Syst. 166: 104445 (2023) - [j13]Xiaohan Chen, Rui Yang, Yihao Xue, Mengjie Huang, Roberto Ferrero, Zidong Wang:
Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016. IEEE Trans. Instrum. Meas. 72: 1-21 (2023) - [j12]Yihao Xue, Rui Yang, Xiaohan Chen, Zhongbei Tian, Zidong Wang:
A Novel Local Binary Temporal Convolutional Neural Network for Bearing Fault Diagnosis. IEEE Trans. Instrum. Meas. 72: 1-13 (2023) - [j11]Qiming Wu, Xiaohan Chen, Yifan Jiang, Zhangyang Wang:
Chasing Better Deep Image Priors between Over- and Under-parameterization. Trans. Mach. Learn. Res. 2023 (2023) - [j10]Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang:
SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7099-7113 (2023) - [c43]Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
Safeguarded Learned Convex Optimization. AAAI 2023: 7848-7855 - [c42]Ruisi Cai, Xiaohan Chen, Shiwei Liu, Jayanth Srinivasa, Myungjin Lee, Ramana Kompella, Zhangyang Wang:
Many-Task Federated Learning: A New Problem Setting and A Simple Baseline. CVPR Workshops 2023: 5037-5045 - [c41]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang:
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR 2023 - [c40]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai:
Towards Constituting Mathematical Structures for Learning to Optimize. ICML 2023: 21426-21449 - [c39]Senyu Mo, Yisheng Guan, Yihui Li, Xiaohan Chen:
A Framework for Online and Offline Programming of Multi-Robot Cooperative Motion Planning. ICMRE 2023: 72-77 - [c38]Qihang Liu, Yuhang Liu, Xiaohan Chen, Zixin Wang, Jiangchen Li:
A new dynamic planning for airport surface based on an improved artificial potential field algorithm in a connected aircraft environment. IoTAAI 2023: 476-482 - [c37]Lei Tan, Xiaohan Chen, Xiaoxi Hu, Tao Tang:
DMDSNet: A Computer Vision-based Dual Multi-task Model for Tunnel Bolt Detection and Corrosion Segmentation. ITSC 2023: 4827-4833 - [c36]Jiajun Wu, Yihui Li, Xiaohan Chen, Yisheng Guan, Weichun Xie, Junyu Xie:
Robot Orientation Learning Based on Interaction Primitives for Human-Robot Collaboration. RCAR 2023: 701-706 - [i23]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai:
Towards Constituting Mathematical Structures for Learning to Optimize. CoRR abs/2305.18577 (2023) - [i22]Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin:
DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. CoRR abs/2310.13261 (2023) - 2022
- [j9]Xiaowen Wang, Hongming Zhu, Yizhi Jiang, Yulong Li, Chen Tang, Xiaohan Chen, Yunjie Li, Qi Liu, Qin Liu:
PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network. Briefings Bioinform. 23(2) (2022) - [j8]Zhiting Wei, Sheng Zhu, Xiaohan Chen, Chen-Yu Zhu, Bin Duan, Qi Liu:
DrSim: Similarity Learning for Transcriptional Phenotypic Drug Discovery. Genom. Proteom. Bioinform. 20(5): 1028-1036 (2022) - [j7]Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin:
Learning to Optimize: A Primer and A Benchmark. J. Mach. Learn. Res. 23: 189:1-189:59 (2022) - [c35]Sameer Bibikar, Haris Vikalo, Zhangyang Wang, Xiaohan Chen:
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better. AAAI 2022: 6080-6088 - [c34]Allen-Jasmin Farcas, Xiaohan Chen, Zhangyang Wang, Radu Marculescu:
Model elasticity for hardware heterogeneity in federated learning systems. FedEdge@MobiCom 2022: 19-24 - [c33]Xiaohan Chen, Jason Zhang, Zhangyang Wang:
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently. ICLR 2022 - [c32]Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. ICLR 2022 - [c31]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy:
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. ICLR 2022 - [c30]Ruisi Cai, Zhenyu Zhang, Tianlong Chen, Xiaohan Chen, Zhangyang Wang:
Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets. NeurIPS 2022 - [c29]Xiaohan Chen, Yihui Li, Yisheng Guan, Wenjing Shi, Jiajun Wu:
Probabilistic Fusion in Task Space and Joint Space for Human-Robot Interaction. ROBIO 2022: 415-420 - [c28]Wenjing Shi, Yihui Li, Yisheng Guan, Xiaohan Chen, Shengtian Yang, Senyu Mo:
Optimized Fingering Planning for Automatic Piano Playing Using Dual-arm Robot System. ROBIO 2022: 933-938 - [i21]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy:
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR abs/2202.02643 (2022) - [i20]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang:
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. CoRR abs/2207.03620 (2022) - 2021
- [j6]Xiaohan Chen, Bei-ke Zhang, Dong Gao:
Bearing fault diagnosis base on multi-scale CNN and LSTM model. J. Intell. Manuf. 32(4): 971-987 (2021) - [c27]Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Zhangyang Wang, Jingjing Liu:
EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets. ACL/IJCNLP (1) 2021: 2195-2207 - [c26]Lida Zhang, Xiaohan Chen, Tianlong Chen, Zhangyang Wang, Bobak J. Mortazavi:
DynEHR: Dynamic adaptation of models with data heterogeneity in electronic health records. BHI 2021: 1-4 - [c25]Xiaohan Chen, Rui Yang, Huiqing Wen, Steven Guan:
Transfer Learning with Unsupervised Domain Adaptation Method for Bearing Fault Diagnosis. CAA SAFEPROCESS 2021: 1-6 - [c24]Tianjian Meng, Xiaohan Chen, Yifan Jiang, Zhangyang Wang:
A Design Space Study for LISTA and Beyond. ICLR 2021 - [c23]Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang:
Learning A Minimax Optimizer: A Pilot Study. ICLR 2021 - [c22]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS 2021: 9908-9922 - [c21]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Hyperparameter Tuning is All You Need for LISTA. NeurIPS 2021: 11678-11689 - [c20]Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang:
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? NeurIPS 2021: 12749-12760 - [c19]Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu, Zhangyang Wang:
The Elastic Lottery Ticket Hypothesis. NeurIPS 2021: 26609-26621 - [i19]Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Zhangyang Wang, Jingjing Liu:
EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets. CoRR abs/2101.00063 (2021) - [i18]Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang:
SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training. CoRR abs/2101.01163 (2021) - [i17]Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin:
Learning to Optimize: A Primer and A Benchmark. CoRR abs/2103.12828 (2021) - [i16]Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu, Zhangyang Wang:
The Elastic Lottery Ticket Hypothesis. CoRR abs/2103.16547 (2021) - [i15]Tianjian Meng, Xiaohan Chen, Yifan Jiang, Zhangyang Wang:
A Design Space Study for LISTA and Beyond. CoRR abs/2104.04110 (2021) - [i14]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. CoRR abs/2106.10404 (2021) - [i13]Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. CoRR abs/2106.14568 (2021) - [i12]Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang:
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? CoRR abs/2107.00166 (2021) - [i11]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Hyperparameter Tuning is All You Need for LISTA. CoRR abs/2110.15900 (2021) - [i10]Sameer Bibikar, Haris Vikalo, Zhangyang Wang, Xiaohan Chen:
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better. CoRR abs/2112.09824 (2021) - 2020
- [c18]Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi:
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. AISTATS 2020: 3894-3904 - [c17]Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin:
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. ICLR 2020 - [c16]Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin:
SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. ISCA 2020: 954-967 - [c15]Xiaohan Chen, Zhangyang Wang, Siyu Tang, Krikamol Muandet:
MATE: Plugging in Model Awareness to Task Embedding for Meta Learning. NeurIPS 2020 - [c14]Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin:
ShiftAddNet: A Hardware-Inspired Deep Network. NeurIPS 2020 - [i9]Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi:
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. CoRR abs/2003.01753 (2020) - [i8]Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
Safeguarded Learned Convex Optimization. CoRR abs/2003.01880 (2020) - [i7]Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin:
SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. CoRR abs/2005.03403 (2020) - [i6]Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin:
ShiftAddNet: A Hardware-Inspired Deep Network. CoRR abs/2010.12785 (2020)
2010 – 2019
- 2019
- [c13]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA. ICLR (Poster) 2019 - [c12]Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. ICML 2019: 5546-5557 - [c11]Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang:
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings. NeurIPS 2019: 5139-5151 - [i5]Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. CoRR abs/1905.05406 (2019) - [i4]Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk:
Drawing early-bird tickets: Towards more efficient training of deep networks. CoRR abs/1909.11957 (2019) - [i3]Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang:
E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving. CoRR abs/1910.13349 (2019) - 2018
- [c10]Xiaohan Chen:
Unsupervised Speech Denoising Method Based on Deep Neural Network. ISCID (2) 2018: 254-258 - [c9]Nitin Bansal, Xiaohan Chen, Zhangyang Wang:
Can We Gain More from Orthogonality Regularizations in Training Deep Networks? NeurIPS 2018: 4266-4276 - [c8]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds. NeurIPS 2018: 9079-9089 - [i2]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds. CoRR abs/1808.10038 (2018) - [i1]Nitin Bansal, Xiaohan Chen, Zhangyang Wang:
Can We Gain More from Orthogonality Regularizations in Training Deep CNNs? CoRR abs/1810.09102 (2018) - 2015
- [c7]Xiaohan Chen, Gim Song Soh, Shaohui Foong, Kevin Otto:
Pose estimation of robotic end-effectors under low speed motion using EKF with inertial and SE(3) measurements. AIM 2015: 1585-1590 - 2014
- [j5]Xiaohan Chen, Yingmin Jia, Fumitoshi Matsuno:
Tracking Control for Differential-Drive Mobile Robots With Diamond-Shaped Input Constraints. IEEE Trans. Control. Syst. Technol. 22(5): 1999-2006 (2014) - [c6]Xiaohan Chen, Yingmin Jia, Fumitoshi Matsuno:
Tracking control of nonholonomic mobile robots with velocity and acceleration constraints. ACC 2014: 880-884 - 2011
- [c5]Xiaohan Chen, Yingmin Jia, Junping Du, Fashan Yu:
Column formation control of multi-robot systems with input constraints. CDC/ECC 2011: 2732-2737 - 2010
- [j4]Chen Wang, Yibo Zhang, Xiaohan Chen, Zhiyu Liu, Lei Shi, Guang Chen, F. Qiu, Chun Ying, Wei Lu:
A behavior-based SMS antispam system. IBM J. Res. Dev. 54(6): 3 (2010) - [j3]Xiaohan Chen, Natalia A. Schmid:
Automatic target recognition performance losses in the presence of atmospheric and camera effects. J. Electronic Imaging 19(2): 023016 (2010)
2000 – 2009
- 2009
- [j2]Xiaohan Chen, Natalia A. Schmid:
Empirical Capacity of a Recognition Channel for Single- and Multipose Object Recognition Under the Constraint of PCA Encoding. IEEE Trans. Image Process. 18(3): 636-651 (2009) - 2008
- [c4]Xiaohan Chen, Natalia A. Schmid:
On empirical capacity, random coding bound, and probability of outage of an object recognition system under constraint of PCA-encoding. CISS 2008: 967-971 - 2007
- [j1]Jinyu Zuo, Natalia A. Schmid, Xiaohan Chen:
On Generation and Analysis of Synthetic Iris Images. IEEE Trans. Inf. Forensics Secur. 2(1): 77-90 (2007) - [c3]Xiaohan Chen, Natalia A. Schmid:
On Capacity of Automatic Target Recognition Systems Under the Constraint of PCA-Encoding. CISS 2007: 530-534 - 2006
- [c2]Jinyu Zuo, Natalia A. Schmid, Xiaohan Chen:
On Performance Comparison of Real and Synthetic Iris Images. ICIP 2006: 305-308 - [c1]Xiaohan Chen, Natalia A. Schmid:
A Joint Shape-Intensity Estimation in Computerized Tomography in the Presence of High-Density Objects. ICIP 2006: 901-904
Coauthor Index
[j11] [j10] [c43] [c42] [c41] [c40] [i23] [j7] [c35] [c34] [c33] [c32] [c31] [c30] [i21] [i20] [c27] [c26] [c24] [c23] [c22] [c21] [c20] [c19] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [i11] [i10] [c18] [c17] [c16] [c15] [c14] [i9] [i8] [i7] [i6] [c13] [c12] [c11] [i5] [i4] [i3] [c9] [c8] [i2] [i1]
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