Trust as a Social Reality
Although trust is an underdeveloped concept in sociology, promising theoretical formulations are available in the recent work of Luhmann and Barber. This sociological version co...
Publications
Explore 62 academic publications
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62 publications
Automated generation of heuristics for biological sequence comparison
Abstract Background Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to i...
Sparsity and incoherence in compressive sampling
We consider the problem of reconstructing a sparse signal x^0\\in{\\bb R}^n from a limited number of linear measurements. Given m randomly selected samples of Ux0, where U is an...
Uncertainty principles and ideal atomic decomposition
Suppose a discrete-time signal S(t), 0/spl les/t<N, is a superposition of atoms taken from a combined time-frequency dictionary made of spike sequences 1/sub {t=/spl tau/}/ and ...
10.1162/15324430152748236
This paper introduces a general Bayesian framework for obtaining sparse solutions to regression and classification tasks utilising models linear in the parameters. Although this...
Partitioning Sparse Matrices with Eigenvectors of Graphs
The problem of computing a small vertex separator in a graph arises in the context of computing a good ordering for the parallel factorization of sparse, symmetric matrices. An ...
Sample size for qualitative research
Purpose Qualitative researchers have been criticised for not justifying sample size decisions in their research. This short paper addresses the issue of which sample sizes are a...
Using Linear Algebra for Intelligent Information Retrieval
Currently, most approaches to retrieving textual materials from scientific databases depend on a lexical match between words in users’ requests and those in or assigned to docum...
New spectral methods for ratio cut partitioning and clustering
Partitioning of circuit netlists in VLSI design is considered. It is shown that the second smallest eigenvalue of a matrix derived from the netlist gives a provably good approxi...
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
Stochastic Gradient Descent (SGD) is a popular algorithm that can achieve state-of-the-art performance on a variety of machine learning tasks. Several researchers have recently ...
Compressed sensing and best 𝑘-term approximation
Compressed sensing is a new concept in signal processing where one seeks to minimize the number of measurements to be taken from signals while still retaining the information ne...
Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior
This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...