Journal Papers and Magazines

[J36] Payel Das, Tom Sercu, Kahini Wadhawan, Inkit Padhi, Sebastian Gehrmann, Flaviu Cipcigan, Vijil Chenthamarakshan, Hendrik Strobelt, Cicero dos Santos, Pin-Yu Chen, Yi Yan Yang, Jeremy Tan, James Hedrick, Jason Crain, and Aleksandra Mojsilovic, “Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics,” Nature Biomedical Engineering, 2021 <AMP_code>

[J35] Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura, Gaoyuan Zhang, Alfred Hero, and Pramod K. Varshney, “A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning,” IEEE Signal Processing Magazine, 2020

[J34] Shuai Zhang, Meng Wang, Jinjun Xiong, Sijia Liu, and Pin-Yu Chen, “Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case,” IEEE Transactions on Neural Networks and Learning Systems, 2020

[J33] Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, and Yunfeng Zhang, AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models,” Journal of Machine Learning Research, 2020 (alphabetical order)

[J32] Samuel Yen-Chi Chen, Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Xiaoli Ma, and Hsi-Sheng Goan, “Variational Quantum Circuits for Deep Reinforcement Learning,” IEEE Access, 2020 <QuantumDRL_code>

[J31] Zhao Qin*, Lingfei Wu*, Hui Sun*, Siyu Huo, Tengfei Ma, Eugene Lim, Pin-Yu Chen, Benedetto Marelli, and Markus Buehler, “Artificial intelligence method to design and fold alpha-helix structural proteins from the primary amino acid sequence,” Extreme Mechanics Letters, 2020 (*equal contribution) <MNNN_code> <MIT_News_SARS-CoV-2>

[J30] Zhining Liu, Weiyi Liu, Pin-Yu Chen, Chenyi Zhuang and Chengyun Song, “hpGAT: High-order Proximity Informed Graph Attention Network,” IEEE Access, 2019

[J29] Chun-Chen Tu, Pin-Yu Chen, and Naisyin Wang, “Improving Prediction Efficacy through Abnormality Detection and Data Preprocessing,” IEEE Access, 2019

[J28] Vachik S. Dave, Baichuan Zhang, Pin-Yu Chen, Mohammad Al Hasan, “Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding,” Data Science and Engineering, 2019 <Neural-Brane_code>

[J27] Weiyi Liu, Zhining Liu, Fucai Yu, Pin-Yu Chen, Toyotaro Suzumura, Guangmin Hu, “A Scalable Attribute-aware Network Embedding System,” Neurocomputing, 2019

[J26] Weiyi Liu, Hal Cooper, Min-Hwan Oh, Pin-Yu Chen, Sailung Yeung, Fucai Yu, Toyotaro Suzumura, Guangmin Hu, “Learning Graph Topological Features via GAN,” IEEE Access, 2019

[J25] Sijia Liu, Haiming Chen, Scott Ronquist, Laura Seaman, Nicholas Ceglia, Walter Meixner, Pin-Yu Chen, Gerald Higgins, Pierre Baldi, Steve Smale, Alfred Hero, Lindsey Muir, Indika Rajapakse, “Genome Architecture Mediates Transcriptional Control of Human Myogenic Reprogramming,” iScience, 2018

[J24] Pin-Yu Chen, Chun-Chen Tu, Paishun Ting, Ya-Yun Luo, Danai Koutra, and Alfred Hero, “Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach,” IEEE Transactions on Signal and Information Processing over Networks, 2018

[J23] Pin-Yu Chen, Meng-Hsuan Sung, and Shin-Ming Cheng, “Analysis of Data Dissemination and Control in Social Internet of Vehicles,” IEEE Internet of Things Journal, vol. 5, no. 4, pp. 2467-2477, Aug. 2018

[J22] Pin-Yu Chen and Alfred Hero, “Phase Transitions and a Model Order Selection Algorithm for Spectral Graph Clustering,” IEEE Transactions on Signal Processing, vol. 66, no. 13, pp. 3407-3420, Jul. 2018 <AMOS code> <slides>

[J21] Sijia Liu, Pin-Yu Chen, and Alfred Hero, “Accelerated Distributed Dual Averaging over Evolving Networks of Growing Connectivity,” IEEE Transactions on Signal Processing, vol. 66, no. 7, pp. 1845-1859, Apr. 2018

[J20] Pin-Yu Chen, Baichuan Zhang, and Mohammad Al Hasan, “Incremental Eigenpair Computation for Graph Laplacian Matrices: Theory and Applications,” Social Network Analysis and Mining, vol. 8, no. 1, Jan. 2018

[J19] P.-Y. Chen, S.-M. Cheng, and H.-Y. Hsu, “Analysis of Information Delivery Dynamics in Cognitive Sensor Networks Using Epidemic Models,” IEEE Internet of Things Journal (special issue on Cognitive Internet of Things), vol. 5, no. 4, pp. 2333-2342, Aug. 2018

[J18] P.-Y. Chen and A. O. Hero, “Multilayer Spectral Graph Clustering via Convex Layer Aggregation: Theory and Algorithms,” IEEE Transactions on Signal and Information Processing over Networks (joint special issue on graph signal processing for J-STSP and T-SIPN), vol. 3, no. 3, pp. 553-567, Sep. 2017 <slides> <MIMOSA_code>

[J17] P.-Y. Chen and S. Liu, “Bias-Variance Tradeoff of Graph Laplacian Regularizer,” IEEE Signal Processing Letters, vol. 24, no. 8, pp. 1118-1122, Aug. 2017

[J16] S.-M. Cheng, P.-Y. Chen, C.-C. Lin, and H.-C. Hsiao, “Traffic-aware Patching for Cyber Security in Mobile IoT,” IEEE Communications Magazine, vol. 55, no 7, pp. 29-35, Jul. 2017 (highlighted by IEEE Xplore Spotlight, Dec. 2017)

[J15] P.-Y. Chen, C.-C. Lin, S.-M. Cheng, C.-Y. Huang, and H.-C. Hsiao, “Decapitation via Digital Epidemics: A Bio-Inspired Transmissive Attack,” IEEE Communications Magazine, vol. 54, no. 6, pp. 75-81, Jun. 2016

[J14] P.-Y. Chen and A. O. Hero, “Deep Community Detection,” IEEE Transactions on Signal Processing, vol. 63, no. 21, pp. 5706-5719, Nov. 2015 <DCD_code>

[J13] P.-Y. Chen, S.-M. Cheng, P.-S. Ting, C.-W. Lien, and F.-J Chu, “When Crowdsourcing Meets Mobile Sensing: A Social Network Perspective,” IEEE Communications Magazine, vol. 53, no. 10, pp. 157-163, Oct. 2015

[J12] P.-Y. Chen and A. O. Hero, “Phase Transitions in Spectral Community Detection,” IEEE Transactions on Signal Processing, vol. 63, no. 16, pp. 4339-4347, Aug. 2015

[J11] P.-Y. Chen and A. O. Hero, “Universal Phase Transition in Community Detectability under a Stochastic Block Model,” Physical Review E, vol. 91, no. 3, pp. 032804, Mar. 2015

[J10] P.-Y. Chen and S.-M. Cheng, “Sequential Defense against Random and Intentional Attacks in Complex Networks,” Physical Review E, vol. 91, no. 2, pp. 022805, Feb. 2015

[J9] P.-Y. Chen and A. O. Hero, “Assessing and Safeguarding Network Resilience to Centrality Attacks,” IEEE Communications Magazine, vol. 52, no. 11, pp. 138-143, Nov. 2014 [Supplementary File] [Correction: For ego centrality, I means the matrix of ones]

[J8] P.-Y. Chen, S.-M. Cheng, and K.-C. Chen, “Information Fusion to Defend Intentional Attack in Internet of Things,” IEEE Internet of Things Journal, vol. 1, no. 4, pp. 337-348, Aug. 2014

[J7] P.-Y. Chen, S.-M. Cheng, and K.-C. Chen, “Optimal Control of Epidemic Information Dissemination over Networks,” IEEE Transactions on Cybernetics, vol. 44, no. 12, pp. 2316-2328, Dec. 2014

[J6] S.-M. Cheng, V. Karyotis, P.-Y. Chen, K.-C. Chen, and S. Papavassiliou, “Diffusion Models for Information Dissemination Dynamics in Wireless Complex Networks,” Journal of Complex Systems, 2013

[J5] P.-Y. Chen, S.-M. Cheng, and K.-C. Chen, “Smart Attacks in Smart Grid Communication Networks,” IEEE Communications Magazine, vol. 50, no. 8, pp. 24–29, Aug. 2012 (highlighted by IEEE COMSOC Technology News, Sep. 2012)

[J4] W. C. Ao, P.-Y. Chen, and K.-C. Chen, “Rate-Reliability-Delay Trade-off of Multipath Transmission Using Network Coding,” IEEE Transactions on Vehicular Technology, vol.61, no.5, pp.2336-2342, Jun 2012

[J3] P.-Y. Chen, W. C. Ao, and K.-C. Chen, “Rate-Delay Enhanced Multipath Transmission Schem via Network Coding in Multihop Networks,” IEEE Communications Letters, vol.16, no.3, pp.281-283, March 2012

[J2] S.-M. Cheng, P.-Y. Chen, and K.-C. Chen, “Ecology of Cognitive Radio Ad Hoc Networks,” IEEE Communications Letters, vol.15, no.7, pp.764-766, July 2011

[J1] S.-M. Cheng, W. C. Ao, P.-Y. Chen, and K.-C. Chen, “On Modeling Malware Propagation in Generalized Social Networks,” IEEE Communications Letters, vol.15, no.1, pp.25-27, Jan. 2011

Book Chapters

[B6] Pin-Yu Chen, Sutanay Choudhury, Luke Rodriguez, Alfred Hero, and Indrajit Ray, “Toward Cyber-Resiliency Metrics for Action Recommendations Against Lateral Movement Attacks,” book chapter in Industrial Control Systems Security and Resiliency, Springer, 2019 <Link> <Technical_Report>

[B5] P.-Y. Chen, “Attack, Defense, and Network Robustness of Internet of Things,” book chapter in Security and Privacy in Internet of Things (IoTs): Models, Algorithms, and Implementations, CRC Press, 2016 <Amazon link>

[B4] S.-M. Cheng, P.-Y. Chen, and K.-C. Chen, “Malware Propagation and Control in Internet of Things,” book chapter in Security and Privacy in Internet of Things (IoTs): Models, Algorithms, and Implementations, CRC Press, 2016 <Amazon link>

[B3] P.-Y. Chen, S.-M. Cheng, W. C. Ao, H.-Y. Hsu, and K.-C. Chen, “Delay Models for Epidemic-like Routing in Multihop Secondary Networks,” book chapter in Introduction to Cognitive Radio Networks and Applications, CRC Press, 2016 <Amazon link>

[B2] P.-Y. Chen, “Network Coding at the Source: Exploiting Multipath Transmission for Rate-Delay Adaptation,” book chapter in Network Coding and Data Compression: Theory, Applications, and Challenges, Nova Science Publishers, 2015 <Amazon link>

[B1] P.-Y. Chen, “A Game-theoretic Attack and Defense Model for Smart Grid,” book chapter in Smart Grids: Technologies, Applications and Management Systems, Nova Science Publishers, 2014 <Amazon link>

Conference and Workshop Papers

[C95] Omid Aramoon, Pin-Yu Chen, and Gang Qu, “AID: Attesting the Integrity of Deep Neural Networks,” Design Automation Conference (DAC), 2021

[C94] Yu-Lin Tsai, Chia-Yi Hsu, Chia-Mu Yu, and Pin-Yu Chen, “Non-Singular Adversarial Robustness of Neural Networks,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021

[C93] Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, and Payel Das, “Active Estimation from Multimodal Data,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021

[C92] Chun-Chieh Teng, Pin-Yu Chen, and Wei-Chen Chiu, “Domain Adaptation for Learning Generator from Paired Few-Shot Data,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021

[C91] Chao-Han Huck Yang, Jun Qi, Samuel Yen-Chi Chen, Pin-Yu Chen, Sabato Marco Siniscalchi, Xiaoli Ma, and Chin-Hui Lee, “Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 <QVFL_code>

[C90] Zichong Li, Pin-Yu Chen*, Sijia Liu*, Songtao Lu*, and Yangyang Xu*, “Rate-improved Inexact Augmented Lagrangian Method for Constrained Nonconvex Optimization,” Artificial Intelligence and Statistics (AISTATS), 2021 (*alphabetical order)

[C89] Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei (Lily) Weng, Sijia Liu, Pin-Yu Chen, and Luca Daniel, “Hidden Cost of Randomized Smoothing,” Artificial Intelligence and Statistics (AISTATS), 2021

[C88] Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei (Lily) Weng, Chuang Gan, and Meng Wang, “On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning,” International Conference on Learning Representations (ICLR), 2021

[C87] Omid Aramoon, Pin-Yu Chen, and Gang Gu, Don't Forget to Sign the Gradients!,” Fourth Conference on Machine Learning and Systems (MLSyS), 2021

[C86] Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, and Payel Das, “Self-Progressing Robust Training,” AAAI Conference on Artificial Intelligence (AAAI), 2021 <SPROUT_code>

[C85] Maurício Gruppi, Sibel Adali, and Pin-Yu Chen, “Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks,” AAAI Conference on Artificial Intelligence (AAAI), 2021

[C84] Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, and Feng Yan, “Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning,” AAAI Conference on Artificial Intelligence (AAAI), 2021

[C83] Akhilan Boopathy, Lily Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, and Luca Daniel, “Fast Training of Provably Robust Neural Networks by SingleProp,” AAAI Conference on Artificial Intelligence (AAAI), 2021

[C82] N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, and Rongjie Lai, Optimizing Mode Connectivity via Neuron Alignment,” Neural Information Processing Systems (NeurIPS), 2020 <Neuron_Alignment_code> <IBM_blog_TND_Align>

[C81] Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei (Lily) Weng, Pin-Yu Chen, Sijia Liu, and Luca Daniel, Higher-Order Certification For Randomized Smoothing,” Neural Information Processing Systems (NeurIPS), 2020 (selected for spotlight presentation, top 3% submission) <IBM_Blog_Certification>

[C80] Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi (Viji) Srinivasan, Wei Zhang, and Kailash Gopalakrishnan, ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training,Neural Information Processing Systems (NeurIPS), 2020 <IBM_blog_ScaleCom>

[C79] Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, and Meng Wang, “Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases,” European Conference on Computer Vision (ECCV), 2020 <TND_code> <IBM_blog_TND_Align>

[C78] Kaidi Xu, Gaoyuan Zhang, Sijia Liu, Quanfu Fan, Mengshu Sun, Hongge Chen, Pin-Yu Chen, Yanzhi Wang, and Xue Lin, “Adversarial T-shirt! Evading Person Detectors in A Physical World,” European Conference on Computer Vision (ECCV), 2020 <Venturebeat_Adv_T-Shirt> <Import_AI_Adv_T-Shirt> <The_Register_Adv_T-Shirt> <NEU_News_Adv_T-Shirt> <Boston Globe_Adv_T-Shirt> <VICE_Adv_T-Shirt> <ODSC_Adv_T-Shirt> <Quartz_Adv_T-Shirt> <WIRED_Adv_T-Shirt> <Comm_ACM_Adv_T-Shirt> <機器之心_Adv_T-Shirt>

[C77] Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho, “Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources,” International Conference on Machine Learning (ICML), 2020 <BAR_code> <TheNextWeb_BAR> <Techtalks_BAR>

[C76] Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, and Jinjun Xiong, “Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case,” International Conference on Machine Learning (ICML), 2020

[C75] Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, and Luca Daniel, “Proper Network Interpretability Helps Adversarial Robustness in Classification,” International Conference on Machine Learning (ICML), 2020

[C74] Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, and Kush R. Varshney, “An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy,” International Conference on Machine Learning (ICML), 2020

[C73] Payel Das*, Brian Quanz*, Pin-Yu Chen, Jaw-wook Ahn, and Dhruv Shah “Toward A Neuro-inspired Creative Decoder,” International Joint Conference on Artificial Intelligence (IJCAI), 2020 (*equal contribution)

[C72] Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, and Jinjun Xiong, “Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent,” Annual Conference on Information Sciences and Systems (CISS), 2020

[C71] Jeet Mohapatra, Tsui-Wei (Lily) Weng, Pin-Yu Chen, Sijia Liu, and Luca Daniel, “Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations,” Conference on Computer Vision and Pattern Recognition (CVPR), 2020 (oral presentation) <Semantify-NN_code> <Semantify-NN_video>

[C70] Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Xiaoli Ma, and Chin-Hui Lee, “Characterizing Adversarial Speech Examples Using Self-Attention U-Net Enhancement,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020

[C69] Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Yi Ouyang, Chin-Hui Lee, and Xiaoli Ma, “Enhanced Adversarial Strategically-Timed Attacks against Deep Reinforcement Learning,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020

[C68] Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, and Xue Lin, “Towards an Efficient and General Framework of Robust Training for Graph Neural Networks,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020

[C67] Xiao Wang, Siyue Wang, Pin-Yu Chen, Xue Lin, and Peter Chin, “ADVMS: A Multi-source Multi-cost Defense against Adversarial Attacks,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020

[C66] Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, and Xue Lin, “Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness,” International Conference on Learning Representations (ICLR), 2020 <TechTalks_sanitization> <TheNextWeb_sanitization> <Model_Sanitization_code>

[C65] Chulin Xie, Keli Huang, Pin-Yu Chen, and Bo Li, “DBA: Distributed Backdoor Attacks against Federated Learning,” International Conference on Learning Representations (ICLR), 2020 <DBA_video>

[C64] Minhao Cheng*, Simranjit Singh*, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, and Cho-Jui Hsieh, “Sign-OPT: A Query-Efficient Hard-label Adversarial Attack,” International Conference on Learning Representations (ICLR), 2020 (*equal contribution) <Sign-OPT_IBM>

[C63] Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, and Cho-Jui Hsieh, “Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples,” AAAI Conference on Artificial Intelligence (AAAI), 2020 <Seq2Sick_code> <Towards_Data_Science_Seq2Sick>

[C62] Pu Zhao, Pin-Yu Chen, Siyue Wang, and Xue Lin, “Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent,” AAAI Conference on Artificial Intelligence (AAAI), 2020 <ZO_NGD_code>

[C61] Tsui-Wei Weng*, Pu Zhao*, Sijia Liu, Pin-Yu Chen, Xue Lin, and Luca Daniel, “Towards Certificated Model Robustness Against Weight Perturbations,” AAAI Conference on Artificial Intelligence (AAAI), 2020 (*equal contribution) <code> <poster>

[C60] Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Jun Xiao, and Bo Li, “Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States,” AAAI Conference on Artificial Intelligence (AAAI), 2020 <poster>

[C59] Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, and Xue Lin, “On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method,” International Conference on Computer Vision (ICCV), 2019 <ZO_ADMM_code>

[C58] Vachik S. Dave, Baichuan Zhang, Pin-Yu Chen, Mohammad Al Hasan, “Neural-Brane: An Inductive Approach for Attributed Network Embedding,” IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019 <Neural-Brane_code>

[C57] Xiao Wang*, Siyue Wang*, Pin-Yu Chen, Yanzhi Wang, Brian Kulis, Xue Lin, Sang Chin, “Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses,” International Joint Conference on Artificial Intelligence (IJCAI), 2019 (*equal contribution) <IBM_Research_Blog_GNN_HRS> <TechTalks_HRS> <Medium_HRS> <HRS_code>

[C56] Kaidi Xu*, Hongge Chen*, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, and Xue Lin, “Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective,” International Joint Conference on Artificial Intelligence (IJCAI), 2019 (*equal contribution) <IBM_Research_Blog_GNN_HRS>

[C55] Chao-Han Huck Yang*, Yi-Chieh Liu*, Pin-Yu Chen, Xiaoli Ma, Yi-Chang James Tsai, “When Causal Intervention Meets Adversarial Perturbation and Image Masking for Deep Neural Networks,” IEEE International Conference on Image Processing (ICIP), 2019 (*equal contribution)

[C54] Pin-Yu Chen, Lingfei Wu, Sijia Liu, and Indika Rajapakse, “Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications,” International Conference on Machine Learning (ICML), 2019 (long oral presentation) <FINGER_code> <slides>

[C53] Tsui-Wei Weng, Pin-Yu Chen, Lam M. Nguyen, Mark S. Squillante, Ivan Oseledets, Akhilan Boopathy, and Luca Daniel, “PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach,” International Conference on Machine Learning (ICML), 2019 <PROVEN_code> <slides>

[C52] Qi Lei*, Lingfei Wu*, Pin-Yu Chen, Alexandros G. Dimakis, Inderjit S. Dhillon, and Michael Witbrock, “Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification,” The Conference on Systems and Machine Learning (SysML) 2019 (*equal contribution) <Paraphrasing_attack_code> <VB_Paraphrasing> <TechTalks_Paraphrasing> <Jiqizhixin_Paraphasing> <Nature_News>

[C51] Sijia Liu, Pin-Yu Chen, Xiangyi Chen, and Mingyi Hung, “SignSGD via Zeroth-Order Oracle,” International Conference on Learning Representations (ICLR), 2019

[C50] Minhao Cheng, Thong Le, Pin-Yu Chen, Jinfeng Yi, Huan Zhang, and Cho-Jui Hsieh, “Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach,” International Conference on Learning Representations (ICLR), 2019 <OptAttack_code>

[C49] Kaidi Xu* Sijia Liu*, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin, “Structured Adversarial Attack: Towards General Implementation and Better Interpretability,” International Conference on Learning Representations (ICLR), 2019 (*equal contribution) <StrAttack_code>

[C48] Zhuolin Yang, Bo Li, Pin-Yu Chen, Dawn Song, “Characterizing Audio Adversarial Examples Using Temporal Dependency,” International Conference on Learning Representations (ICLR), 2019 <TD_code> <poster> <TechTalks_temporal_dependency> <IBM_Research_Blog_Temporal_Dependency> <Nature_News>

[C47] Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, and Luca Daniel “CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks,” AAAI Conference on Artificial Intelligence (AAAI), 2019 (oral presentation) <CNN-Cert_code> <slides> <poster> <EE_TIMES> <TechTalks> <IBM_Research_Blog_CNN-Cert> <MIT_IBM_Medium_CNN-Cert> <IBM Response to NIST RFI on AI> <MC.AI_AutoZOOM>

[C46] Chun-Chen Tu*, Paishun Ting*, Pin-Yu Chen*, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, and Shin-Ming Cheng, “AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks,” AAAI Conference on Artificial Intelligence (AAAI), 2019 (oral presentation) (*equal contribution) <AutoZOOM_code> <slides> <poster> <EE_TIMES> <TechTalks_1> <TechTalks_2> <IBM_Research_Blog_AutoZOOM> <PHYS.ORG_AutoZOOM> <IBM_Research_AI_Review_2019> <MC.AI_AutoZOOM>

[C45] Amit Dhurandhar*, Pin-Yu Chen*, Ronny Luss, Chun-Chen Tu, Paishun Ting, Karthikeyan Shanmugam, and Payel Das, “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives,” Neural Information Processing Systems (NeurIPS), 2018 (*equal contribution) <CEM_code> <Forbes_coverage> <PC_Magazine> <IBM_Research_Blog>

[C44] Huan Zhang*, Tsui-Wei Weng*, Pin-Yu Chen, Cho-Jui Hsieh, and Luca Daniel, “Efficient Neural Network Robustness Certification with General Activation Functions,” Neural Information Processing Systems (NeurIPS), 2018 (*equal contribution) <CROWN_code>

[C43] Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen, Pai-Shun Ting, Shiyu Chang, and Lisa Amini, “Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization,” Neural Information Processing Systems (NeurIPS), 2018 <poster>

[C42] Pin-Yu Chen*, Bhanukiran Vinzamuri*, and Sijia Liu, “Is Ordered Weighted $\ell_1$ Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR,” IEEE Global Conference on Signal and Information Processing (GlobalSIP) 2018 (*equal contribution) <slides>

[C41] Tsui-Wei Weng*, Huan Zhang*, Pin-Yu Chen, Aurelie Lozano, Cho-Jui Hsieh, and Luca Daniel, “On Extensions of CLEVER: a Neural Network Robustness Evaluation Algorithm,” IEEE Global Conference on Signal and Information Processing (GlobalSIP) 2018 (*equal contribution) <CLEVER_code> <adversarial_robustness_toolbox> <IBM_Research_Blog> <SiliconANGLE> <MIT_IBM_Medium> <IBM Response to NIST RFI on AI> <Fool_the_Bank_demo>

[C40] Sijia Liu, Xingguo Li, Pin-Yu Chen, Jarvis Haupt, and Lisa Amini, “Zeroth-Order Stochastic Projected Gradient Descent for Nonconvex Optimization,” IEEE Global Conference on Signal and Information Processing (GlobalSIP) 2018

[C39] Chia-Yi Hsu, Pei-Hsuan Lu, Pin-Yu Chen, and Chia-Mu Yu, “On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces,” IEEE Global Conference on Signal and Information Processing (GlobalSIP) 2018 <poster>

[C38] Lingfei Wu, Ian E.H. Yen, Kun Xu, Fangli Xu, Avinash Balakrishnan, Pin-Yu Chen, Pradeep Ravikumar, and Michael J. Witbrock, “Word Mover's Embedding: From Word2Vec to Document Embedding,” Conference on Empirical Methods in Natural Language Processing (EMNLP) 2018 <IBM_Research_Blog>

[C37] Dong Su*, Huan Zhang*, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, and Yupeng Gao, “Is Robustness the Cost of Accuracy? A Comprehensive Study on the Robustness of 18 Deep Image Classification Models,” European Conference on Computer Vision (ECCV) 2018 (*equal contribution) <Code> <slides>

[C36] Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, and Charu Aggarwal, “Scalable Spectral Clustering Using Random Binning Features,” ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) 2018 (oral presentation) <IBM_Research_Blog> <poster> <slides> <SC-RB_Code>

[C35] Hongge Chen*, Huan Zhang*, Pin-Yu Chen, Jinfeng Yi, and Cho-Jui Hsieh, “Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning,” Annual Meeting of the Association for Computational Linguistics (ACL) 2018 (*equal contribution) <ShowAndFool_code> <poster>

[C34] Pei-Hsuan Lu, Pin-Yu Chen, Kang-Cheng Chen, and Chia-Mu Yu, “On the Limitation of MagNet Defense against $L_1$ based Adversarial Examples,” IEEE/IFIP International Conference on Dependable and Systems and Networks (DSN) 2018, Workshop on Dependable and Secure Machine Learning

[C33] Pei-Hsuan Lu, Pin-Yu Chen, and Chia-Mu Yu, “On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples,” International Conference on Learning Representations (ICLR) 2018 Workshop <poster>

[C32] Yash Sharma and Pin-Yu Chen, “Attacking the Madry Defense Model with $L_1$-based Adversarial Examples,” International Conference on Learning Representations (ICLR) 2018 Workshop <poster>

[C31] Tsui-Wei Weng*, Huan Zhang*, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Guo, Cho-Jui Hsieh, and Luca Daniel, “Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach,” International Conference on Learning Representations (ICLR) 2018 (*equal contribution) <CLEVER_code> <IBM_Research_Blog> <SiliconANGLE_news> <MIT_IBM_Medium> <IBM_Research_AI_2018_Review> <IBM Response to NIST RFI on AI> <Fool_the_Bank_demo>

[C30] Pin-Yu Chen* and Dennis Wei*, “On the Supermodularity of Active Graph-based Semi-supervised Learning with Stieltjes Matrix Regularization,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 (*equal contribution) <poster>

[C29] Sijia Liu, Pin-Yu Chen, Indika Rajapakse, and Alfred Hero, “First-order Bifurcation Detection for Dynamic Complex Networks,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018

[C28] Jie Chen, Sijia Liu, and Pin-Yu Chen, “Zeroth-order Diffusion Adaptation over Networks,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018

[C27] Sijia Liu, Jie Chen, Pin-Yu Chen, and Alfred Hero, “Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications,” International Conference on Artificial Intelligence and Statistics (AISTATS), 2018 - Also presented at NeurIPS 2017 Optimization for Machine Learning Workshop <poster>

[C26] Pin-Yu Chen*, Yash Sharma*, Huan Zhang, Jinfeng Yi, and Cho-Jui Hsieh, “EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples,” AAAI Conference on Artificial Intelligence (AAAI), 2018 (*equal contribution) <EAD_code> <cleverhans> <adversarial_robustness_toolbox> <Foolbox> <slides>

[C25] Pin-Yu Chen*, Huan Zhang*, Yash Sharma, Jinfeng Yi, and Cho-Jui Hsieh, “ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models,” ACM Conference on Computer and Communications Security (CCS) Workshop on Artificial Intelligence and Security (AISec), Nov. 2017 (*equal contribution) <ZOO_code> <adversarial_robustness_toolbox> <slides> (best paper award finalist) - Also presented at NeurIPS 2017 Machine Learning and Computer Security Workshop

[C24] W. Liu, P.-Y. Chen, S. Yeung, T. Suzumura and L. Chen, “Principled Multilayer Network Embedding,” IEEE Conference on Data Mining (ICDM) Workshop on Data Mining in Networks, pp. 134-141, Nov., 2017

[C23] P.-Y. Chen and L. Wu, “Revisiting Spectral Graph Clustering with Generative Community Models,” IEEE Conference on Data Mining (ICDM), pp. 51-60, Nov., 2017 <slides> (9.25 % regular paper acceptance rate)

[C22] W. Liu, P.-Y. Chen, H. Cooper, M.-H. Oh, S. Yeung, and T. Suzumura, “Can GAN Learn Topological Features of a Graph?” International Conference on Machine Learning (ICML) Workshop on Implicit Generative Models, Aug., 2017

[C21] P.-S. Ting, C.-C. Tu, P.-Y. Chen, Y-.Y. Luo, and S.-M. Cheng, “FEAST: An Automated Feature Selection Framework for Compilation Tasks,” 31-st IEEE International Conference on Advanced Information Networking and Applications (AINA), pp. 1138-1145, Mar. 2017 <slides><slides+audio>

[C20] P.-Y. Chen, T. Gensollen, and A. O. Hero, “AMOS: An Automated Model Order Selection Algorithm for Spectral Graph Clustering,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6448--6452, Mar. 2017 (oral presentation) <AMOS code> <slides>

[C19] S. Liu, P.-Y. Chen, and A. O. Hero, “Distributed Optimization for Evolving Networks of Growing Connectivity,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4079--4083, Mar. 2017 (oral presentation)

[C18] P.-Y. Chen and A. O. Hero, “Multilayer Spectral Graph Clustering via Convex Layer Aggregation,” IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 317-321, Dec. 2016 <slides> (oral presentation; awarded IEEE GlobalSIP Student Travel Grant)

[C17] P.-Y. Chen, B. Zhang, M. Hasan, and A. O. Hero, “Incremental Method for Spectral Clustering of Increasing Orders,” ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) workshop on Mining and Learning with Graphs (MLG), 2016 <slides> <poster> <video> (contributed talk; awarded ACM KDD Student Travel Award)

[C16] S.-M. Cheng and P.-Y. Chen, “Ecology-based DoS Attack in Cognitive Radio Networks,” IEEE Symposium on Security and Privacy (S&P) workshop on Bio-inspired Security, Trust, Assurance, and Resilience (BioSTAR), pp. 104-110, May 2016 (awarded IEEE S&P Student Travel Grant)

[C15] P.-Y. Chen, S. Choudhury, and A. O. Hero, “Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4553-4556, Mar. 2016 <slides><poster> <video>

[C14] P.-Y. Chen, C.-W. Lien, F.-J. Chu, P.-S. Ting, and S.-M. Cheng, “Supervised Collective Classification for Crowdsourcing,” IEEE Global Communications Conference (GLOBECOM) Workshop on Networking and Collaboration Issues for the Internet of Everything, pp. 1-6, Dec. 2015

[C13] S. Choudhury, P.-Y. Chen, L. Rodriguez, D. Curtis, P. Nordquist, I. Ray, K. Oler and and P. Nordquist, “Action Recommendation for Cyber Resilience,” ACM Conference on Computer and Communications Security (CCS) Workshop on Automated Decision Making for Active Cyber Defense, pp. 3-8, Oct. 2015 (acceptance rate 8/27 (Covered by PNNL research highlight <Link>)

[Demo Video: Defending Real-Time Attacks on Amazon Cloud]

[C12] P.-Y. Chen, Z. Qi, Y. Pan, and S.-M. Cheng, “Multivariate and Categorical Analysis of Gaming Statistics,” 18th International Conference on Network-Based Information Systems (NBiS), pp. 286-293, Sep. 2015

[C11] P.-Y. Chen, and A. O. Hero, “Phase Transitions in Spectral Community Detection of Large Noisy Networks,“ IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3402-3406, Apr. 2015 (Oral Presentation <Link>; awarded SPS Travel Grant)

[C10] P.-Y. Chen, and A. O. Hero, “Local Fiedler Vector Centrality for Detection of Deep and Overlapping Communities in Networks,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1120-1124, May 2014 (awarded NSF Travel Grant) <LFVC_code> <poster>

[C9] P.-Y. Chen, H.-F. Lin,K.-H. Hsu, and S.-M. Cheng, “Modeling Dynamics of Malware with Incubation Period from the View of Individual,” IEEE Vehicular Technology Conference (VTC), pp. 1-5, May 2014

[C8] P.-Y. Chen, and A. O. Hero, “Node Removal Vulnerability of the Largest Component of a Network”, IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 587-590. Dec. 2013 <poster>

[C7] S.-Y. Lien, H.-H. Lee, S.-Y. Shih, P.-Y. Chen, and K.-C. Chen, “Network Synchronization among Femtocells,” IEEE Global Communications Conference (GLOBECOM) Workshops, pp.248-252, Dec. 2011

[C6] P.-Y. Chen, W. C. Ao, S.-C. Lin, and K.-C. Chen, “Reciprocal Spectrum Sharing Game and Mechanism in Cellular Systems with Cognitive Radio Users,” IEEE Global Communications Conference (GLOBECOM) Workshops, pp.981-985, Dec. 2011

[C5] P.-Y. Chen, and K.-C. Chen, “Optimal Control of Epidemic Information Dissemination in Mobile Ad Hoc Networks," IEEE Global Communications Conference (GLOBECOM), pp. 1–5. Dec. 2011

[C4] P.-Y. Chen, and K.-C. Chen, “Intentional Attack and Fusion-based Defense Strategy in Complex Networks," IEEE Global Communications Conference (GLOBECOM), pp. 1–5. Dec. 2011

[C3] P.-Y. Chen, V. Karyotis, S. Papavassiliou, and K.-C. Chen, “Topology Control in Multi-channel Cognitive Radio Networks with Non-uniform Node Arrangements," IEEE Symposium on Computers and Communications (ISCC), pp.1033-1037, June 2011

[C2] P.-Y. Chen, S.-M. Cheng, W. C. Ao, and K.-C. Chen, “Multi-path Routing with End-to-end Statistical QoS Provisioning in Underlay Cognitive Radio Networks,” IEEE International Conference on Computer Communications (INFOCOM) Workshops, pp.7-12, April 2011

[C1] P.-Y. Chen, and K.-C. Chen, “Information Epidemics in Complex Networks with Opportunistic Links and Dynamic Topology," IEEE Global Communications Conference (GLOBECOM), pp.1-6, Dec. 2010 (Received GOLD Best Paper Award <Link>)

Demos

[D1] L. Rodriguez, D. Curtis, S. Choudhury, K. Oler, P. Nordquist, P.-Y. Chen, and I. Ray, “DEMO: Action Recommendation for Cyber Resilience,” ACM Conference on Computer and Communications Security (CCS), pp. 1620-1622, Oct. 2015 (acceptance rate 27/47) (Covered by PNNL research highlight <Link>) [Demo Video: Defending Real-Time Attacks on Amazon Cloud]