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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 516 (2 self)
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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
A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge
 PSYCHOLOGICAL REVIEW
, 1997
"... How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LS ..."
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Cited by 1772 (10 self)
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How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LSA), is presented and used to successfully simulate such learning and several other psycholinguistic phenomena. By inducing global knowledge indirectly from local cooccurrence data in a large body of representative text, LSA acquired knowledge about the full vocabulary of English at a comparable rate to schoolchildren. LSA uses no prior linguistic or perceptual similarity knowledge; it is based solely on a general mathematical learning method that achieves powerful inductive effects by extracting the right number of dimensions (e.g., 300) to represent objects and contexts. Relations to other theories, phenomena, and problems are sketched.
Hybrid Algorithms for the Constraint Satisfaction Problem
 Computational Intelligence
, 1993
"... problem (csp), namely, naive backtracking (BT), backjumping (BJ), conflictdirected backjumping ..."
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Cited by 383 (8 self)
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problem (csp), namely, naive backtracking (BT), backjumping (BJ), conflictdirected backjumping
Computing Discrete Minimal Surfaces and Their Conjugates
 EXPERIMENTAL MATHEMATICS
, 1993
"... We present a new algorithm to compute stable discrete minimal surfaces bounded by a number of fixed or free boundary curves in R³, S³ and H³. The algorithm makes no restriction on the genus and can handle singular triangulations. For a discrete harmonic map a conjugation process is presented leading ..."
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Cited by 356 (10 self)
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We present a new algorithm to compute stable discrete minimal surfaces bounded by a number of fixed or free boundary curves in R³, S³ and H³. The algorithm makes no restriction on the genus and can handle singular triangulations. For a discrete harmonic map a conjugation process is presented
A Classification Learning Algorithm
"... Presence of irrelevant features is a fact of life in many realworld applications of classification learning. Although nearestneighbor classification algorithms have emerged as a promising approach to machine learning tasks with their high predictive accuracy, they are adversely affected by the ..."
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by the presence of such irrelevant features. In this paper, we describe a recently proposed classification algorithm called VFI5, which achieves comparable accuracy to nearestneighbor classifiers while it is robust with respect to irrelevant features. The paper compares both the nearestneighbor classifier
A Classification Learning Algorithm Robust to Irrelevant Features
"... Abstract. Presence of irrelevant features is a fact of life in many realworld applications of classification learning. Although nearestneighbor classification algorithms have emerged as a promising approach to machine learning tasks with their high predictive accuracy, they are adversely affected b ..."
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by the presence of such irrelevant features. In this paper, we describe a recently proposed classification algorithm called VFI5, which achieves comparable accuracy to nearestneighbor classifiers while it is robust with respect to irrelevant features. The paper compares both the nearestneighbor classifier
Fast Contact Force Computation for Nonpenetrating Rigid Bodies
, 1994
"... A new algorithm for computing contact forces between solid objects with friction is presented. The algorithm allows a mix of contact points with static and dynamic friction. In contrast to previous approaches, the problem of computing contact forces is not transformed into an optimization problem. B ..."
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Cited by 276 (7 self)
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A new algorithm for computing contact forces between solid objects with friction is presented. The algorithm allows a mix of contact points with static and dynamic friction. In contrast to previous approaches, the problem of computing contact forces is not transformed into an optimization problem
Learning Differential Diagnosis of ErythematoSquamous Diseases using Voting Feature Intervals
"... A new classification algorithm, called VFI5 (for Voting Feature Intervals), is developed and applied to problem of differential diagnosis of ErythematoSquamous diseases. The domain contains records of patients with known diagnosis. Given a training set of such records the VFI5 classifier learns how ..."
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Cited by 17 (9 self)
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A new classification algorithm, called VFI5 (for Voting Feature Intervals), is developed and applied to problem of differential diagnosis of ErythematoSquamous diseases. The domain contains records of patients with known diagnosis. Given a training set of such records the VFI5 classifier learns
A theory of cortical responses
, 2005
"... This article concerns the nature of evoked brain responses and the principles underlying their generation. We start with the premise that the sensory brain has evolved to represent or infer the causes of changes in its sensory inputs. The problem of inference is well formulated in statistical terms. ..."
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Cited by 249 (30 self)
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This article concerns the nature of evoked brain responses and the principles underlying their generation. We start with the premise that the sensory brain has evolved to represent or infer the causes of changes in its sensory inputs. The problem of inference is well formulated in statistical terms. The statistical fundaments of inference may therefore afford important constraints on neuronal implementation. By formulating the original ideas of Helmholtz on perception, in terms of modernday statistical theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. It turns out that the problems of inferring the causes of sensory input (perceptual inference) and learning the relationship between input and cause (perceptual learning) can be resolved using exactly the same principle. Specifically, both inference and learning rest on minimizing the brain’s free energy, as defined in statistical physics. Furthermore, inference and learning can proceed in a biologically plausible fashion. Cortical responses can be seen as the brain’s attempt to minimize the free energy induced by a stimulus and thereby encode the most likely cause of that stimulus. Similarly, learning emerges from changes in synaptic efficacy that minimize the free energy, averaged over all stimuli encountered. The underlying scheme rests on empirical Bayes and hierarchical models
Bayesian Haplotype Inference for Multiple Linked SingleNucleotide Polymorphisms .American
 Journal of Human Genetics
, 2002
"... Haplotypes have gained increasing attention in the mapping of complexdisease genes, because of the abundance of singlenucleotide polymorphisms (SNPs) and the limited power of conventional singlelocus analyses. It has been shown that haplotypeinference methods such as Clark’s algorithm, the expec ..."
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Cited by 232 (5 self)
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Haplotypes have gained increasing attention in the mapping of complexdisease genes, because of the abundance of singlenucleotide polymorphisms (SNPs) and the limited power of conventional singlelocus analyses. It has been shown that haplotypeinference methods such as Clark’s algorithm
Results 1  10
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