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Abstract: We give a deterministic O(log n)^n algorithm for the {\em Shortest Vector Problem (SVP)} of a lattice under {\em any} norm, improving on the previous best deterministic bound of n^O(n) for g...
Abstract: Nonnegative matrix factorization (NMF) is a data analysis technique used in a great variety of applications such as text mining, image processing, hyperspectral data analysis, computational ...
Abstract: We consider the problem of detecting a small subset of defective items from a large set via non-adaptive "random pooling" group tests. We consider both the case when the measurements are noi...
Abstract: We consider several stochastic service systems, and study the asymptotic behavior of the moments of various quantities that have application to models for random interval graphs and algorith...
Evaluating Data Assimilation Algorithms     Data Assimilation Algorithms  Data Analysis  Statistics and Probability       font style='font-size:12px;'> 2011/10/9
Abstract: Data assimilation refers to methodologies for the incorporation of noisy observations of a physical system into an underlying model in order to infer the properties of the state of the syste...
Explicit n-descent on elliptic curves. III. Algorithms     Explicit n-descent  elliptic curves  Algorithms  Number Theory       font style='font-size:12px;'> 2011/9/14
Abstract: This is the third in a series of papers in which we study the n-Selmer group of an elliptic curve, with the aim of representing its elements as genus one normal curves of degree n. The metho...
Abstract: The sparsity constrained rank-one matrix approximation problem is a difficult mathematical optimization problem which arises in a wide array of useful applications in engineering, machine le...
Abstract: Several implicit (continuum) solvent models are considered: the Polarized Continuum Model (PCM), the Surface Generalized Born model (SGB), and the COnductor-like Screening model (COSMO) as w...
Simulation studies are presented regarding the performance of algorithms that localize point-like radioactive sources detected by a position sensitive portable radiation instrument (COCAE). The source...
Evaluating Data Assimilation Algorithms     Evaluate   Data Assimilation  Algorithms  assimilation refers       font style='font-size:12px;'> 2011/8/5
Abstract: Data assimilation refers to methodologies for the incorporation of noisy observations of a physical system into an underlying model in order to infer the properties of the state of the syste...
Given a set of sensor nodes V where each node wants to broadcast a message to all its neighbors that are within a certain broadcasting range, the local broadcasting problem is to schedule all these re...
This paper deals with exploiting symmetry for solving linear and integer programming problems. Basic properties of linear representations of finite groups can be used to reduce symmetric linear progra...
Recent years have witnessed the popularity of using rank minimization as a regularizer for various signal processing and machine learning problems.
A fast and simple O(log n) iteration algorithm for individual Lucas numbers is given. This is faster than using Fibonacci based methods because of the structure of Lucas numbers. Using a √5 conversion...
In multi-user communication from one base station (BS) to multiple users, the problem of minimizing the transmit power to achieve some target guaranteed performance (rates) at users has been well inve...

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