Sijia Liu
    Pron.: Si-'gia Liu

    Research Staff Member
    IBM Research, Cambridge
    MIT-IBM Watson AI Lab



Sijia Liu
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Technical Reports/Submissions
P.-Y. Chen, L. Wu, S. Liu, I. Rajapakse
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications
arxiv, 2018.
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S. Liu, P.-Y. Chen, A. O. Hero, and I. Rajapakse
Dynamic Network Analysis of the 4D Nucleome
bioRxiv, 2018.
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Software
H. Chen*, S. Liu*, L. Seaman, C. Najarian, W. Wu, M. Ljungman, G. Higgins, A. O. Hero, M. Wicha, and I. Rajapakse (* co-first authors)
Parental allele-specific genome architecture and transcription during the cell cycle
bioRxiv, 2018.
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O. Khalil, F. Harirchi, D. Kim, S. Liu, P. Elvati and A. Hero
Model Reduction in Chemical Reaction Networks: A Data-Driven Sparse-Learning Approach
arxiv, 2018.
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Conferences
S. Liu, P.-Y. Chen, X. Chen, M. Hong
signSGD via Zeroth-Order Oracle
to appear in ICLR'19 (acceptance rate 31%)
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K. Xu*, S. Liu*, P. Zhao*, P.-Y. Chen, H. Zhang, D. Erdogmus, Y. Wang, X. Lin (* co-first authors)
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
to appear in ICLR'19 (acceptance rate 31%)
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X. Chen, S. Liu, R. Sun, M. Hong
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
to appear in ICLR'19 (acceptance rate 31%)
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A. Boopathy, L. Weng, P.-Y. Chen, S. Liu and L. Daniel
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
to appear in AAAI (acceptance rate 16.2%), 2019.
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C.-C. Tu, P. Ting, P.-Y. Chen, S. Liu, H. Zhang, J. Yi, C.-J. Hsieh, S.-M. Cheng
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
to appear in AAAI (acceptance rate 16.2%), , 2019
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S. Liu, B. Kailkhura, P.-Y. Chen, P. Ting, S. Chang, L. Amini
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
to appear in NIPS (acceptance rate 22.7%), 2018.
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Software
S. Liu, X. Li, P.-Y. Chen, B. Vinzamuri, J. Haupt, L. Amini
Zeroth-Order Stochastic Projected Gradient Descent for Nonconvex Optimization
IEEE GlobalSIP, 2018.
P.-Y. Chen, B. Vinzamuri, S. Liu
Is Ordered Weighted L1 Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR
IEEE GlobalSIP, 2018.
P. Zhao, S. Liu, Y. Wang, and X. Lin
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks
ACM Multimedia (MM), 2018.
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S. Liu, P.-Y. Chen, I. Rajapakse, and A. O. Hero
First-Order Bifurcation Detection for Dynamic Complex Networks
IEEE ICASSP, 2018.

J. Chen, S. Liu, and P.-Y. Chen
Zeroth-Order Diffusion Adaptation over Networks
IEEE ICASSP, 2018.

S. Liu, J. Chen, P.-Y. Chen, and A. O. Hero
Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications
AISTATS, 2018.
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Software
S. Liu, P.-Y. Chen, J. Chen, and A. O. Hero
Convergence Analysis of Zeroth-Order Online Alternating Direction Method of Multipliers
NIPS Workshop on Optimization for Machine Learning, 2017.
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F. Harirchi, O. A. Khalil, S. Liu, P. Elvati, A. Violi, and A. O. Hero
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks
NIPS workshop on Advances in Modeling and Learning Interactions using Complex Data, 2017.
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T. P. Xie, S. Liu, and A. O. Hero
Semiblind Subgraph Reconstruction in Gaussian Graphical Models
IEEE GlobalSIP, 2017.
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S. Liu, A. Ren, Y. Wang, and P. K. Varshney
Ultra-Fast Robust Compressive Sensing Based on Memristor Crossbars
IEEE ICASSP, 2017 (Best Student Paper Award, Thrid Place)
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S. Liu, P.-Y. Chen, and A. O. Hero
Distributed Optimization for Evolving Networks of Growing Connectivity
IEEE ICASSP, 2017.
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S. Liu, S. P. Chepuri, G. Leus, and A. O. Hero
Distributed Sensor Selection for Field Estimation
IEEE ICASSP, 2017.
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S. P. Chepuri, S. Liu, G. Leus and A. O. Hero
Learning Sparse Graphs Under Smoothness Prior
IEEE ICASSP, 2017.
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A. Ren, S. Liu, R. Cai, P. K. Varshney and Y. Wang
Algorithm-Hardware Co-Optimization of Memristor Crossbar-Based Framework for Solving SOCP and Homogeneous QCQP Problems
22nd Asia and South Pacific Design Automation Conference (ASPDAC), 2016.
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S. Liu, V. Sharma, and P. K. Varshney
Towards An Online Energy Allocation Policy for Distributed Estimation with Sensor Collaboration Using Energy Harvesting Sensor
IEEE GlobalSIP, 2016.
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S. Liu, N. Cao, and P. K. Varshney
Sensor Placement for Field Estimation via Poisson Disk Sampling
IEEE GlobalSIP, 2016.
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S. Liu, Y. Wang, M. Fardad, and P. K. Varshney
Optimal Energy Allocation and Storage Control for Distributed Estimation with Sensor Collaboration
CISS, 2016.
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S. Liu, S. Kar, M. Fardad, and P. K. Varshney
On Optimal Sensor Collaboration for Distributed Estimation with Individual Power Constraints
Asilomar, 2015.
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V. Gupta, B. Kailkhura, T. Wimalajeewa, S. Liu, and P. K. Varshney
Joint Sparsity Pattern Recovery with 1-bit Compressive Sensing in Sensor Networks
Asilomar, 2015.
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S. Liu, F. Chen, A. Vempaty, M. Fardad, and P. K. Varshney
Sparsity-Promoting Sensor Management for Estimation: An Energy Balance Point of View
FUSION, 2015.
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Nadendla, V. S. S., S. Liu, and P. K. Varshney
Design of transmit-diversity schemes in detection networks under secrecy constraints
Allerton, 2015.
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S. Liu, E. Masazade, M. Fardad, and P. K. Varshney
Sensor Selection with Correlated Measurements for Target Tracking in Wireless Sensor Networks
IEEE ICASSP, 2015.
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S. Liu, E. Masazade, M. Fardad, and P. K. Varshney
Sparsity-Aware Field Estimation via Ordinary Kriging
IEEE ICASSP, 2014.
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S. Liu, M. Fardad, S. Kar, and P. K. Varshney
On Optimal Sensor Collaboration Topologies for Linear Coherent Estimation
IEEE ISIT, 2014.
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S. Liu, M. Fardad, E. Masazade, and P. K. Varshney
On Optimal Periodic Sensor Scheduling for Field Estimation in Wireless Sensor Networks
IEEE GlobalSIP, 2013.
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S. Liu, E. Masazade, X. Shen and P. K. Varshney
Adaptive Non-Myopic Quantizer Design for Target Tracking in Wireless Sensor Networks
Asilomar, 2013. (Finalist Best Student Paper Award)
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S. Liu, E. Masazade, and P. K. Varshney
Temporally Staggered Sensing for Field Estimation with Quantized Data in Wireless Sensor Networks
IEEE SSP, 2012.
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Journals
S. Liu, H. Chen, S. Ronquist, L. Seaman, N. Ceglia, W. Meixner, L. A. Muir, P.-Y. Chen, G. Higgins, P. Baldi, S. Smale, A. O. Hero, and I. Rajapakse
Genome Architecture Leads a Bifurcation in Cell Identity
iScience , Cell, 2018.
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S. Zhang, S. Liu, V. Sharma, and P. K. Varshney,
Optimal Sensor Collaboration for Parameter Tracking Using Energy Harvesting Sensors
IEEE Transactions on Signal Processing, 2018.
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S. Liu, Y. Wang, M. Fardad, and P. K. Varshney
A Memristor-Based Optimization Framework for AI Applications
IEEE Circuits and Systems Magazine, 2018.
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Software
S. Liu, P.-Y. Chen, and A. O. Hero
Accelerated Distributed Dual Averaging over Evolving Networks of Growing Connectivity
IEEE Transactions on Signal Processing, in press, 2018.
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P.-Y. Chen and S. Liu
Bias-Variance Tradeoff of Graph Laplacian Smoothing Regularizer
IEEE Signal Process. Lett., , 2017.
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H. Chen, L. Seaman, S. Liu, T. Ried, and I. Rajapakse
Chromosome conformation and gene expression patterns differ profoundly in human fibroblasts grown in spheroids versus monolayers
Nucleus , 2017.
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S. Liu, S. Kar, M. Fardad, and P. K. Varshney
Optimized Sensor Collaboration for Estimation of Temporally Correlated Parameters
IEEE Transactions on Signal Processing , 2017.
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B. Kailkhura, S. Liu, T. Wimalajeewa, and P. K. Varshney
Measurement Matrix Design for Compressive Detection with Secrecy Guarantees
IEEE Wireless Communications Letters , 2016.
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S. Liu, S. Kar, M. Fardad, and P. K. Varshney
Joint Design of Optimal Sensor Selection and Collaboration Strategies for Distributed Estimation
IEEE ComSoc MMTC E-letter , Special Issue on "Energy efficiency management for distributed computation and applications in sensor networks" 2016.
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S. Liu, S. P. Chepuri, M. Fardad, E. Masazade, G. Leus, and P. K. Varshney
Sensor Selection for Estimation with Correlated Measurement Noise
IEEE Transactions on Signal Processing , 2016.
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S. Liu, S. Kar, M. Fardad, and P. K. Varshney
Sparsity-Aware Sensor Collaboration for Linear Coherent Estimation
IEEE Transactions on Signal Processing , 2015.
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S. Liu, A. Vempaty, M. Fardad, E. Masazade, and P. K. Varshney
Energy-Aware Sensor Selection in Field Reconstruction
IEEE Signal Processing Letters , 2014.
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X. Shen, S. Liu, and P. K. Varshney
Sensor Selection for Nonlinear Systems in Large Sensor Networks
IEEE Transactions on Aerospace and Electronic Systems , 2014.
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S. Liu, M. Fardad, E. Masazade and P. K. Varshney
Optimal Periodic Sensor Scheduling in Networks of Dynamical Systems
IEEE Transactions on Signal Processing , 2014.
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Patents
K. Yang and S. Liu
System and Method for Analyzing A Root Cause of Anomalous Behavior Using Hypothesis Testing
US Patent Application, Serial No. 14/991685, 2016.