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10,433
Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems
- IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
, 2007
"... Many problems in signal processing and statistical inference involve finding sparse solutions to under-determined, or ill-conditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined with a spa ..."
Abstract
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Cited by 539 (17 self)
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sparseness-inducing (ℓ1) regularization term.Basis pursuit, the least absolute shrinkage and selection operator (LASSO), wavelet-based deconvolution, and compressed sensing are a few well-known examples of this approach. This paper proposes gradient projection (GP) algorithms for the bound
N Degrees of Separation: Multi-Dimensional Separation of Concerns
- IN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING
, 1999
"... Done well, separation of concerns can provide many software engineering benefits, including reduced complexity, improved reusability, and simpler evolution. The choice of boundaries for separate concerns depends on both requirements on the system and on the kind(s) of decompositionand composition a ..."
Abstract
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Cited by 522 (8 self)
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given formalism supports. The predominant methodologies and formalisms available, however, support only orthogonal separations of concerns, along single dimensions of composition and decomposition. These characteristics lead to a number of well-known and difficult problems. This paper describes a new
Large margin methods for structured and interdependent output variables
- JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
Abstract
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Cited by 624 (12 self)
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to accomplish this, we propose to appropriately generalize the well-known notion of a separation margin and derive a corresponding maximum-margin formulation. While this leads to a quadratic program with a potentially prohibitive, i.e. exponential, number of constraints, we present a cutting plane algorithm
Statistical pattern recognition: A review
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2000
"... The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network techniques ..."
Abstract
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Cited by 1035 (30 self)
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The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network
Loopy belief propagation for approximate inference: An empirical study. In:
- Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract
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Cited by 676 (15 self)
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. Introduction The task of calculating posterior marginals on nodes in an arbitrary Bayesian network is known to be NP hard In this paper we investigate the approximation performance of "loopy belief propagation". This refers to using the well-known Pearl polytree algorithm [12] on a Bayesian network
Determinants of long-term growth: a Bayesian Averaging of Classical Estimates (BACE) approach
, 2003
"... This paper examines the robustness and joint interaction of explanatory variables in cross-country economic growth regressions. It employs a novel approach, Bayesian Averaging of Classical Estimates (BACE), which constructs estimates as a weighted average of OLS estimates for every possible combina ..."
Abstract
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Cited by 374 (3 self)
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This paper examines the robustness and joint interaction of explanatory variables in cross-country economic growth regressions. It employs a novel approach, Bayesian Averaging of Classical Estimates (BACE), which constructs estimates as a weighted average of OLS estimates for every possible
Sparse Reconstruction by Separable Approximation
, 2007
"... Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), wavelet-based deconvolution and reconstruction, and compressed sensing ..."
Abstract
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Cited by 373 (38 self)
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(CS) are a few well-known areas in which problems of this type appear. One standard approach is to minimize an objective function that includes a quadratic (ℓ2) error term added to a sparsity-inducing (usually ℓ1) regularizer. We present an algorithmic framework for the more general problem
The Fast Downward planning system
- Journal of Artifical Intelligence Research
, 2006
"... Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, including advanced features like ADL conditions and effects and derived predicates (axioms). Like other well-known planne ..."
Abstract
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Cited by 347 (29 self)
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Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, including advanced features like ADL conditions and effects and derived predicates (axioms). Like other well-known
Shape from Shading: A Survey
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1999
"... ... this paper, six well-known SFS algorithms are implemented and compared. The performance of the algorithms was analyzed on synthetic images using mean and standard deviation of depth (Z) error, mean of surface gradient (p, q) error, and CPU timing. Each algorithm works well for certain images, ..."
Abstract
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Cited by 305 (1 self)
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... this paper, six well-known SFS algorithms are implemented and compared. The performance of the algorithms was analyzed on synthetic images using mean and standard deviation of depth (Z) error, mean of surface gradient (p, q) error, and CPU timing. Each algorithm works well for certain images
How People revisit Web Pages: empirical findings and implications for the design of history systems
- International Journal of Human Computer Studies
, 1997
"... We report on users ’ revisitation patterns to World Wide Web (web) pages, and use the results to lay an empirical foundation for the design of history mechanisms in web browsers. Through history, a user can return quickly to a previously visited page, possibly reducing the cognitive and physical ove ..."
Abstract
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Cited by 313 (10 self)
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overhead required to navigate to it from scratch. We analysed 6 weeks of detailed usage data collected from 23 users of a wellknown web browser. We found that 58 % of an individual’s pages are revisits, and that users continually add new web pages into their repertoire of visited pages. People tend
Results 1 - 10
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10,433
