Somesh Kumar

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We develop protocols for preparing a GHZ state and, in general, a pure multi-partite maximally entangled state in a distributed network with apriori quantum entanglement between agents using classical communication and local operations. We investigate and characterize the minimal combinatorics of the sharing of EPR pairs required amongst agents in a network(More)
BACKGROUND Postpartum intrauterine contraceptive devices (PPIUCD) are increasingly included in many national postpartum family planning (PPFP) programs, but satisfaction of women who have adopted PPIUCD and complication rates need further characterization. Our specific aims were to describe women who accepted PPIUCD, their experience and satisfaction with(More)
Function approximation is an instance of supervised learning which is one of the most studied topics in machine learning, artificial neural networks, pattern recognition, and statistical curve fitting. In principle, any of the methods studied in these fields can be used in reinforcement learning. Multi-layered feed-forward neural networks (MLFNN) have been(More)