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Quantization Index Modulation: A Class of Provably Good Methods for Digital Watermarking and Information Embedding

by Brian Chen, Gregory W. Wornell - IEEE TRANS. ON INFORMATION THEORY , 1999
"... We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing information-embedding rate, mini ..."
Abstract - Cited by 496 (14 self) - Add to MetaCart
We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing information-embedding rate

Image denoising using a scale mixture of Gaussians in the wavelet domain

by Javier Portilla, Vasily Strela, Martin J. Wainwright, Eero P. Simoncelli - IEEE TRANS IMAGE PROCESSING , 2003
"... We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vecto ..."
Abstract - Cited by 513 (17 self) - Add to MetaCart
We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian

Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer

by Peter W. Shor - SIAM J. on Computing , 1997
"... A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. ..."
Abstract - Cited by 1277 (4 self) - Add to MetaCart
A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration

CoSaMP: Iterative signal recovery from incomplete and inaccurate samples

by D. Needell, J. A. Tropp - California Institute of Technology, Pasadena , 2008
"... Abstract. Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery alg ..."
Abstract - Cited by 770 (13 self) - Add to MetaCart
algorithm called CoSaMP that delivers the same guarantees as the best optimization-based approaches. Moreover, this algorithm offers rigorous bounds on computational cost and storage. It is likely to be extremely efficient for practical problems because it requires only matrix–vector multiplies

Secure spread spectrum watermarking for multimedia

by Ingemar J. Cox, Joe Kilian, F. Thomson Leighton, Talal Shamoon - IEEE TRANSACTIONS ON IMAGE PROCESSING , 1997
"... This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i.i.d.) Gauss ..."
Abstract - Cited by 1100 (10 self) - Add to MetaCart
This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i

Hidden Markov models in computational biology: applications to protein modeling

by Anders Krogh, Michael Brown, I. Saira Mian, Kimmen Sjölander, David Haussler - JOURNAL OF MOLECULAR BIOLOGY , 1994
"... Hidden.Markov Models (HMMs) are applied t.0 the problems of statistical modeling, database searching and multiple sequence alignment of protein families and protein domains. These methods are demonstrated the on globin family, the protein kinase catalytic domain, and the EF-hand calcium binding moti ..."
Abstract - Cited by 655 (39 self) - Add to MetaCart
Hidden.Markov Models (HMMs) are applied t.0 the problems of statistical modeling, database searching and multiple sequence alignment of protein families and protein domains. These methods are demonstrated the on globin family, the protein kinase catalytic domain, and the EF-hand calcium binding

Distance metric learning for large margin nearest neighbor classification

by Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul - In NIPS , 2006
"... We show how to learn a Mahanalobis distance metric for k-nearest neighbor (kNN) classification by semidefinite programming. The metric is trained with the goal that the k-nearest neighbors always belong to the same class while examples from different classes are separated by a large margin. On seven ..."
Abstract - Cited by 695 (14 self) - Add to MetaCart
. On seven data sets of varying size and difficulty, we find that metrics trained in this way lead to significant improvements in kNN classification—for example, achieving a test error rate of 1.3 % on the MNIST handwritten digits. As in support vector machines (SVMs), the learning problem reduces to a

Machine Learning in Automated Text Categorization

by Fabrizio Sebastiani - ACM COMPUTING SURVEYS , 2002
"... The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this p ..."
Abstract - Cited by 1734 (22 self) - Add to MetaCart
The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach

A Theory of Diagnosis from First Principles

by Raymond Reiter - ARTIFICIAL INTELLIGENCE , 1987
"... Suppose one is given a description of a system, together with an observation of the system's behaviour which conflicts with the way the system is meant to behave. The diagnostic problem is to determine those components of the system which, when assumed to be functioning abnormally, will explain ..."
Abstract - Cited by 1120 (5 self) - Add to MetaCart
Suppose one is given a description of a system, together with an observation of the system's behaviour which conflicts with the way the system is meant to behave. The diagnostic problem is to determine those components of the system which, when assumed to be functioning abnormally

Shape Matching and Object Recognition Using Shape Contexts

by Serge Belongie, Jitendra Malik, Jan Puzicha - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2001
"... We present a novel approach to measuring similarity between shapes and exploit it for object recognition. In our framework, the measurement of similarity is preceded by (1) solv- ing for correspondences between points on the two shapes, (2) using the correspondences to estimate an aligning transform ..."
Abstract - Cited by 1809 (21 self) - Add to MetaCart
transform. In order to solve the correspondence problem, we attach a descriptor, the shape context, to each point. The shape context at a reference point captures the distribution of the remaining points relative to it, thus offering a globally discriminative characterization. Corresponding points on two
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