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1.12 Solving Constrained CASH Problems with ADMM
Parikshit Ram · Sijia Liu

Sat Jul 18 07:20 AM -- 07:25 AM (PDT) @


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Author Information

Parikshit Ram (Infosys, Ltd.)
Sijia Liu (MIT-IBM Watson AI Lab)

Sijia Liu is a Research Staff Member at MIT-IBM Watson AI Lab, IBM research. Prior to joining in IBM Research, he was a Postdoctoral Research Fellow at the University of Michigan, Ann Arbor. He received the Ph.D. degree (with All University Doctoral Prize) in electrical and computer engineering from Syracuse University, NY, USA, in 2016. His recent research interests include deep learning, adversarial machine learning, gradient-free optimization, nonconvex optimization, and graph data analytics. He received the Best Student Paper Finalist Award at Asilomar Conference on Signals, Systems, and Computers (Asilomar'13). He received the Best Student Paper Award at the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'17). He served as a general chair of the Symposium 'Signal Processing for Adversarial Machine Learning' at GlobalSIP, 2018. He is also the co-chair of the workshop 'Adversarial Learning Methods for Machine Learning and Data Mining' at KDD, 2019.

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