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Researcher, NEC Labs
- Program Committee: AAAI 2018, SoCC 2017(Scholarship Chair), ICML 2017, APSys 2016.
- Conference Reviewer: NIPS 2017, NIPS 2016, USENIX ATC 2011, SIGMETRICS 2010.
- Journal/Workshop: NIPS LearningSys 2016, EMDNN 2016, IEEE Computing, Software; ACM: TACO, TECS, TOCS.
I am a researcher at NEC Labs working on efficient representation learning and distributed machine learning.
I received my PhD from University of Wisconsin in 2013. My research interests are in machine
learning, operating and distributed systems and program analysis.
At NEC, I started the MALT project first working towards efficient RDMA based distributed processing systems with support for
non-iid data and efficient synchronization. Recently, I am working on efficient networks and representations as well as applying
ML towards systems problems.
Recent Publications | All Publications
- A Context-Aware Attention Network for Interactive Question Answering.(Preprint) Huayu Li, Martin Renqiang Min, Yong Ge, Asim Kadav. In KDD, 2017.
- Pruning Filters for Efficient ConvNets. Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, Hans Peter Graf. In ICLR'17.
- Privacy preserving collaboration in Bring Your Own Apps. Sangmin Lee, Deepak Goel, Edmund L. Wong, Asim Kadav, Mike Dahlin. In Symposium on Cloud Computing (SOCC '16).
- Random Walk Distributed Dual Averaging Method For Decentralized Consensus Optimization.
Cun Mu, Asim Kadav, Erik Kruus, Donald Goldfarb, and Martin Renqiang Min.
NIPS Optimization Workshop (NIPS OPT'15), Montreal, Canada, December 2015.
MALT: Distributed Data-Parallelism for existing ML applications.
Hao Li, Asim Kadav, Erik Kruus, Cristian Ungureanu.
ACM European Conference on Computer Systems, (Eurosys '15), Bordeaux, France, April 2015. Poster
Blizzard: Fast, Cloud-scale Block Storage for Cloud-oblivious Applications.
James Mickens, Ed Nightingale, Jeremy Elson, Bin Fan, Asim Kadav, Vijay Chidambaram, Osama Khan, Krishna Nareddy, and Darren Gehring. Network Systems Design and Implementation (NSDI '14), April 2014.
Picture (via Deep Dream)
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