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An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions
 ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS
, 1994
"... Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any po ..."
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Cited by 972 (32 self)
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Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
, 1998
"... This article reviews five approximate statistical tests for determining whether one learning algorithm outperforms another on a particular learning task. These tests are compared experimentally to determine their probability of incorrectly detecting a difference when no difference exists (type I err ..."
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Cited by 713 (8 self)
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This article reviews five approximate statistical tests for determining whether one learning algorithm outperforms another on a particular learning task. These tests are compared experimentally to determine their probability of incorrectly detecting a difference when no difference exists (type I
Stable Signal Recovery from Incomplete and Inaccurate Measurements
, 2006
"... Suppose we wish to recover a vector x0 ∈ Rm (e.g., a digital signal or image) from incomplete and contaminated observations y = Ax0 + e; A is an n × m matrix with far fewer rows than columns (n m) and e is an error term. Is it possible to recover x0 accurately based on the data y? To recover x0, we ..."
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Cited by 1361 (38 self)
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discussed in earlier papers. The methodology also explains why one can also very nearly recover approximately sparse signals.
Compressed sensing
, 2004
"... We study the notion of Compressed Sensing (CS) as put forward in [14] and related work [20, 3, 4]. The basic idea behind CS is that a signal or image, unknown but supposed to be compressible by a known transform, (eg. wavelet or Fourier), can be subjected to fewer measurements than the nominal numbe ..."
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Cited by 3557 (22 self)
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number of pixels, and yet be accurately reconstructed. The samples are nonadaptive and measure ‘random’ linear combinations of the transform coefficients. Approximate reconstruction is obtained by solving for the transform coefficients consistent with measured data and having the smallest possible `1
SURF: Speeded Up Robust Features
 ECCV
"... Abstract. In this paper, we present a novel scale and rotationinvariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features). It approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be comp ..."
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Cited by 840 (12 self)
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Abstract. In this paper, we present a novel scale and rotationinvariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features). It approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can
Closedform solution of absolute orientation using unit quaternions
 J. Opt. Soc. Am. A
, 1987
"... Finding the relationship between two coordinate systems using pairs of measurements of the coordinates of a number of points in both systems is a classic photogrammetric task. It finds applications in stereophotogrammetry and in robotics. I present here a closedform solution to the leastsquares pr ..."
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Cited by 968 (4 self)
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. These exact results are to be preferred to approximate methods based on measurements of a few selected points. The unit quaternion representing the best rotation is the eigenvector associated with the most positive eigenvalue of a symmetric 4 X 4 matrix. The elements of this matrix are combinations of sums
Modeling and Forecasting Realized Volatility
, 2002
"... this paper is built. First, although raw returns are clearly leptokurtic, returns standardized by realized volatilities are approximately Gaussian. Second, although the distributions of realized volatilities are clearly rightskewed, the distributions of the logarithms of realized volatilities are a ..."
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Cited by 536 (50 self)
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this paper is built. First, although raw returns are clearly leptokurtic, returns standardized by realized volatilities are approximately Gaussian. Second, although the distributions of realized volatilities are clearly rightskewed, the distributions of the logarithms of realized volatilities
The use of MMR, diversitybased reranking for reordering documents and producing summaries
 In SIGIR
, 1998
"... jadeQcs.cmu.edu Abstract This paper presents a method for combining queryrelevance with informationnovelty in the context of text retrieval and summarization. The Maximal Marginal Relevance (MMR) criterion strives to reduce redundancy while maintaining query relevance in reranking retrieved docum ..."
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Cited by 755 (13 self)
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relevance to the user’s query. In contrast, we motivated the need for “relevant novelty ” as a potentially superior criterion. A first approximation to measuring relevant novelty is to measure relevance and novelty independently and provide a linear combination as the metric. We call the linear combination
A Digital Fountain Approach to Reliable Distribution of Bulk Data
, 1998
"... The proliferation of applications that must reliably distribute bulk data to a large number of autonomous clients motivates the design of new multicast and broadcast protocols. We describe an ideal, fully scalable protocol for these applications that we call a digital fountain. A digital fountain a ..."
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Cited by 494 (20 self)
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allows any number of heterogeneous clients to acquire bulk data with optimal efficiency at times of their choosing. Moreover, no feedback channels are needed to ensure reliable delivery, even in the face of high loss rates. We develop a protocol that closely approximates a digital fountain using a new
Contextuality of Approximate Measurements
"... The claim of Meyer, Kent and Clifton (MKC) that finite precision measurement nullifies the KochenSpecker theorem is criticised. It is argued that, although MKC have nullified the KochenSpecker theorem strictly socalled, there are other, related propositions which are not nullified. The argument g ..."
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Cited by 2 (0 self)
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is unjustified. Consequently, the analysis of MKC is incomplete. To make it complete one needs to investigate the predictions their models make regarding approximate joint measurements of noncommuting observables. Such an investigation is carried out, using methods previously developed in connection
Results 1  10
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