20,720 research outputs found
Max vs Min: Tensor Decomposition and ICA with nearly Linear Sample Complexity
We present a simple, general technique for reducing the sample complexity of
matrix and tensor decomposition algorithms applied to distributions. We use the
technique to give a polynomial-time algorithm for standard ICA with sample
complexity nearly linear in the dimension, thereby improving substantially on
previous bounds. The analysis is based on properties of random polynomials,
namely the spacings of an ensemble of polynomials. Our technique also applies
to other applications of tensor decompositions, including spherical Gaussian
mixture models
Satellite Broadcasting Enabled Blockchain Protocol: A Preliminary Study
Low throughput has been the biggest obstacle of large-scale blockchain
applications. During the past few years, researchers have proposed various
schemes to improve the systems' throughput. However, due to the inherent
inefficiency and defects of the Internet, especially in data broadcasting
tasks, these efforts all rendered unsatisfactory. In this paper, we propose a
novel blockchain protocol which utilizes the satellite broadcasting network
instead of the traditional Internet for data broadcasting and consensus tasks.
An automatic resumption mechanism is also proposed to solve the unique
communication problems of satellite broadcasting. Simulation results show that
the proposed algorithm has a lower communication cost and can greatly improve
the throughput of the blockchain system. Theoretical estimation of a satellite
broadcasting enabled blockchain system's throughput is 6,000,000 TPS with a 20
gbps satellite bandwidth.Comment: Accepted by 2020 Information Communication Technologies Conference
(ICTC 2020
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