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经验
Data Scientist
5月 2013 - 7月 2015 (2 年, 2 个月)
Worked on various projects range from statistical modeling, data analytics, machine learning, optimization and operations research.
教育
B.Tech
(4 年)
出版物
A toolbox for fast and approximate solutions for large linear and semidefinite programs
ACM
The multiplicative weights update is an algorithmic design technique that, over the years, has been discovered independently by several groups of researchers in different contexts. The earliest known use of this technique is by Brown and vonNeumann for the computation of equilibrium strategies in zero-sum games. These ideas and variants thereof have found applications in solving games, linear and semidefinite programming, computational geometry, machine learning, auctions and mechanism design.
A behavior based model for detecting data exfiltration in network environment
IEEE IMSAA-11
There is a growing concern across the globe about exfiltration of sensitive data over network. This coupled with the increase in other insider threats pose greater challenge. Present day perimeter security solutions such as Intrusion detection & prevention system, firewall are not capable of detecting data-exfiltration. Also existing behavior models that can detect intrusions and worms do not incorporate mechanims to detect data-exfiltration.
Fast approximations to solve packing/covering LPs and constant-sum games via multiplicative-weights
International Symposium on Combinatorial Optimization - CO 2012, Sept. 12 - University of Oxford, UK
Abstract: The multiplicative weights algorithm is a well-known technique for approximately solving packing/covering linear programs. The technique originated in the 1940s in the context of solving constant-sum games. There has been considerable recent research building on this work, developing fast and approximate solutions to packing/covering linear as well as semi-denite programs.
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