Sijia Liu
Sijia Liu
Research Staff Member, MIT-IBM Watson AI Lab, IBM Research
Dirección de correo verificada de ibm.com - Página principal
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On the convergence of a class of adam-type algorithms for non-convex optimization
X Chen, S Liu, R Sun, M Hong
arXiv preprint arXiv:1808.02941, 2018
1072018
Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks
CC Tu, P Ting, PY Chen, S Liu, H Zhang, J Yi, CJ Hsieh, SM Cheng
Proceedings of the AAAI Conference on Artificial Intelligence 33, 742-749, 2019
1032019
Sensor selection for estimation with correlated measurement noise
S Liu, SP Chepuri, M Fardad, E Maşazade, G Leus, PK Varshney
IEEE Transactions on Signal Processing 64 (13), 3509-3522, 2016
1002016
Optimal periodic sensor scheduling in networks of dynamical systems
S Liu, M Fardad, E Masazade, PK Varshney
IEEE Transactions on Signal Processing 62 (12), 3055-3068, 2014
732014
Learning sparse graphs under smoothness prior
SP Chepuri, S Liu, G Leus, AO Hero
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
712017
Structured adversarial attack: Towards general implementation and better interpretability
K Xu, S Liu, P Zhao, PY Chen, H Zhang, Q Fan, D Erdogmus, Y Wang, ...
arXiv preprint arXiv:1808.01664, 2018
602018
Topology attack and defense for graph neural networks: An optimization perspective
K Xu, H Chen, S Liu, PY Chen, TW Weng, M Hong, X Lin
arXiv preprint arXiv:1906.04214, 2019
552019
Zeroth-order stochastic variance reduction for nonconvex optimization
S Liu, B Kailkhura, PY Chen, P Ting, S Chang, L Amini
Advances in Neural Information Processing Systems, 3727-3737, 2018
452018
Zeroth-order online alternating direction method of multipliers: Convergence analysis and applications
S Liu, J Chen, PY Chen, A Hero
International Conference on Artificial Intelligence and Statistics, 288-297, 2018
442018
Cnn-cert: An efficient framework for certifying robustness of convolutional neural networks
A Boopathy, TW Weng, PY Chen, S Liu, L Daniel
Proceedings of the AAAI Conference on Artificial Intelligence 33, 3240-3247, 2019
412019
Sparsity-aware sensor collaboration for linear coherent estimation
S Liu, S Kar, M Fardad, PK Varshney
IEEE Transactions on Signal Processing 63 (10), 2582-2596, 2015
392015
Energy-aware sensor selection in field reconstruction
S Liu, A Vempaty, M Fardad, E Masazade, PK Varshney
IEEE Signal Processing Letters 21 (12), 1476-1480, 2014
312014
Sensor selection for nonlinear systems in large sensor networks
X Shen, S Liu, PK Varshney
IEEE Transactions on Aerospace and Electronic Systems 50 (4), 2664-2678, 2014
302014
Sparsity-aware field estimation via ordinary kriging
S Liu, E Masazade, M Fardad, PK Varshney
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
272014
Adversarial Robustness vs. Model Compression, or Both?
S Ye, K Xu, S Liu, H Cheng, JH Lambrechts, H Zhang, A Zhou, K Ma, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision, 111-120, 2019
25*2019
Sign-opt: A query-efficient hard-label adversarial attack
M Cheng, S Singh, P Chen, PY Chen, S Liu, CJ Hsieh
arXiv preprint arXiv:1909.10773, 2019
212019
Automated machine learning via ADMM
S Liu, P Ram, D Bouneffouf, G Bramble, AR Conn, H Samulowitz, ...
CoRR, abs/1905.00424, 2019
21*2019
Interpreting adversarial examples by activation promotion and suppression
K Xu, S Liu, G Zhang, M Sun, P Zhao, Q Fan, C Gan, X Lin
arXiv preprint arXiv:1904.02057, 2019
192019
Progressive dnn compression: A key to achieve ultra-high weight pruning and quantization rates using admm
S Ye, X Feng, T Zhang, X Ma, S Lin, Z Li, K Xu, W Wen, S Liu, J Tang, ...
arXiv preprint arXiv:1903.09769, 2019
192019
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 Fardad, S Liu, ...
arXiv preprint arXiv:1810.07378, 2018
192018
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Artículos 1–20