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Of Current Formulations Of ModelBased Diagnosis
, 1991
"... There are three parts to this paper. First, I present what I hope is a conclusive, worstcase, complexity analysis of two wellknown formulations of the Minimal Diagnosis problem — those of [Reiter 87] and [Reggia et al., 85]. I then show that Reiter's conflictsets solution to the problem deco ..."
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There are three parts to this paper. First, I present what I hope is a conclusive, worstcase, complexity analysis of two wellknown formulations of the Minimal Diagnosis problem — those of [Reiter 87] and [Reggia et al., 85]. I then show that Reiter's conflictsets solution to the problem
Approximate Signal Processing
, 1997
"... It is increasingly important to structure signal processing algorithms and systems to allow for trading off between the accuracy of results and the utilization of resources in their implementation. In any particular context, there are typically a variety of heuristic approaches to managing these tra ..."
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Cited by 538 (2 self)
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number of ideas and approaches to approximate processing as currently being formulated in the computer science community. We then present four examples of signal processing algorithms/systems that are structured with these goals in mind. These examples may be viewed as partial inroads toward the ultimate
Multiple kernel learning, conic duality, and the SMO algorithm
 In Proceedings of the 21st International Conference on Machine Learning (ICML
, 2004
"... While classical kernelbased classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. (2004) considered conic combinations of kernel matrices for the support vector machine (SVM), and showed that the optimiz ..."
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Cited by 445 (31 self)
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the technique of MoreauYosida regularization to yield a formulation to which SMO techniques can be applied. We present experimental results that show that our SMObased algorithm is significantly more efficient than the generalpurpose interior point methods available in current optimization toolboxes. 1.
A framework for learning predictive structures from multiple tasks and unlabeled data
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... One of the most important issues in machine learning is whether one can improve the performance of a supervised learning algorithm by including unlabeled data. Methods that use both labeled and unlabeled data are generally referred to as semisupervised learning. Although a number of such methods ar ..."
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Cited by 443 (3 self)
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are proposed, at the current stage, we still don’t have a complete understanding of their effectiveness. This paper investigates a closely related problem, which leads to a novel approach to semisupervised learning. Specifically we consider learning predictive structures on hypothesis spaces (that is, what
TimeDomain Geometric EddyCurrent Formulation for Hexahedral Grids
"... The aim of this paper is to present a 3D timedomain eddycurrent formulation based on the discrete geometric approach (DGA) over unstructured and nonorthogonal hexahedral dual grids. The resulting differential algebraic system of equation, solved by means of a singlydiagonally implicit Runge–Kutt ..."
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The aim of this paper is to present a 3D timedomain eddycurrent formulation based on the discrete geometric approach (DGA) over unstructured and nonorthogonal hexahedral dual grids. The resulting differential algebraic system of equation, solved by means of a singlydiagonally implicit Runge
OPTIMAL CONTROL FOR A STATIONARY MHD SYSTEM IN VELOCITY–CURRENT FORMULATION
"... Abstract. An optimal control problem for the equations governing the stationary problem of magnetohydrodynamics (MHD) is considered. Control mechanisms by external and injected currents and magnetic fields are treated. An optimal control problem is formulated. First order necessary and second order ..."
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Cited by 4 (1 self)
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Abstract. An optimal control problem for the equations governing the stationary problem of magnetohydrodynamics (MHD) is considered. Control mechanisms by external and injected currents and magnetic fields are treated. An optimal control problem is formulated. First order necessary and second order
Group Communication Specifications: A Comprehensive Study
 ACM COMPUTING SURVEYS
, 1999
"... Vieworiented group communication is an important and widely used building block for many distributed applications. Much current research has been dedicated to specifying the semantics and services of vieworiented Group Communication Systems (GCSs). However, the guarantees of different GCSs are for ..."
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Cited by 370 (15 self)
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Vieworiented group communication is an important and widely used building block for many distributed applications. Much current research has been dedicated to specifying the semantics and services of vieworiented Group Communication Systems (GCSs). However, the guarantees of different GCSs
Sampling—50 years after Shannon
 Proceedings of the IEEE
, 2000
"... This paper presents an account of the current state of sampling, 50 years after Shannon’s formulation of the sampling theorem. The emphasis is on regular sampling, where the grid is uniform. This topic has benefited from a strong research revival during the past few years, thanks in part to the math ..."
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Cited by 339 (27 self)
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This paper presents an account of the current state of sampling, 50 years after Shannon’s formulation of the sampling theorem. The emphasis is on regular sampling, where the grid is uniform. This topic has benefited from a strong research revival during the past few years, thanks in part
Correlation Clustering
 MACHINE LEARNING
, 2002
"... We consider the following clustering problem: we have a complete graph on # vertices (items), where each edge ### ## is labeled either # or depending on whether # and # have been deemed to be similar or different. The goal is to produce a partition of the vertices (a clustering) that agrees as mu ..."
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Cited by 332 (4 self)
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clusters). This formulation is motivated from a document clustering problem in which one has a pairwise similarity function # learned from past data, and the goal is to partition the current set of documents in a way that correlates with # as much as possible; it can also be viewed as a kind of "
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