Results 1  10
of
6,273
Features of similarity.
 Psychological Review
, 1977
"... Similarity plays a fundamental role in theories of knowledge and behavior. It serves as an organizing principle by which individuals classify objects, form concepts, and make generalizations. Indeed, the concept of similarity is ubiquitous in psychological theory. It underlies the accounts of stimu ..."
Abstract

Cited by 1455 (2 self)
 Add to MetaCart
. These models represent objects as points in some coordinate space such that the observed dissimilarities between objects correspond to the metric distances between the respective points. Practically all analyses of proximity data have been metric in nature, although some (e.g., hierarchical clustering) yield
Computing semantic relatedness using Wikipediabased explicit semantic analysis
 In Proceedings of the 20th International Joint Conference on Artificial Intelligence
, 2007
"... Computing semantic relatedness of natural language texts requires access to vast amounts of commonsense and domainspecific world knowledge. We propose Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a highdimensional space of concepts derived from Wikipedi ..."
Abstract

Cited by 562 (9 self)
 Add to MetaCart
Computing semantic relatedness of natural language texts requires access to vast amounts of commonsense and domainspecific world knowledge. We propose Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a highdimensional space of concepts derived from
Cognitive Radio: BrainEmpowered Wireless Communications
, 2005
"... Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a softwaredefined radio, is defined as an intelligent wireless communication system that is aware of its environment and use ..."
Abstract

Cited by 1541 (4 self)
 Add to MetaCart
Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a softwaredefined radio, is defined as an intelligent wireless communication system that is aware of its environment
Geodesic Active Contours
, 1997
"... A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both in ..."
Abstract

Cited by 1425 (47 self)
 Add to MetaCart
A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both
INVARIANCE OF gNATURAL METRICS ON LINEAR FRAME BUNDLES
"... Abstract. In this paper we prove that each gnatural metric on a linear frame bundle LM over a Riemannian manifold (M, g) is invariant with respect to a lifted map of a (local) isometry of the base manifold. Then we define gnatural metrics on the orthonormal frame bundle OM and we prove the same in ..."
Abstract
 Add to MetaCart
Abstract. In this paper we prove that each gnatural metric on a linear frame bundle LM over a Riemannian manifold (M, g) is invariant with respect to a lifted map of a (local) isometry of the base manifold. Then we define gnatural metrics on the orthonormal frame bundle OM and we prove the same
Informationtheoretic metric learning
 in NIPS 2006 Workshop on Learning to Compare Examples
, 2007
"... We formulate the metric learning problem as that of minimizing the differential relative entropy between two multivariate Gaussians under constraints on the Mahalanobis distance function. Via a surprising equivalence, we show that this problem can be solved as a lowrank kernel learning problem. Spe ..."
Abstract

Cited by 359 (15 self)
 Add to MetaCart
We formulate the metric learning problem as that of minimizing the differential relative entropy between two multivariate Gaussians under constraints on the Mahalanobis distance function. Via a surprising equivalence, we show that this problem can be solved as a lowrank kernel learning problem
ON NATURAL METRICS ON TANGENT BUNDLES OF RIEMANNIAN MANIFOLDS
"... Abstract. There is a class of metrics on the tangent bundle TM of a Riemannian manifold (M; g) (oriented, or nonoriented, respectively), which are 'naturally constructed ' from the base metric g [15]. We call them \gnatural metrics " on TM. To our knowledge, the geometric propertie ..."
Abstract
 Add to MetaCart
Abstract. There is a class of metrics on the tangent bundle TM of a Riemannian manifold (M; g) (oriented, or nonoriented, respectively), which are 'naturally constructed ' from the base metric g [15]. We call them \gnatural metrics " on TM. To our knowledge, the geometric
Natural Metrics and LeastCommitted Priors for Articulated Tracking
"... In articulated tracking, one is concerned with estimating the pose of a person in every frame of a film. This pose is most often represented as a kinematic skeleton where the joint angles are the degrees of freedom. Leastcommitted predictive models are then phrased as a Brownian motion in joint ang ..."
Abstract
 Add to MetaCart
on the manifold that respects the natural metric. This model is expressed in terms of a stochastic differential equation, which we solve using a novel numerical scheme. Empirically, we validate the new model in a particle filter based articulated tracking system. Here, we not only outperform the standard Brownian
Probabilistic Approximation of Metric Spaces and its Algorithmic Applications
 In 37th Annual Symposium on Foundations of Computer Science
, 1996
"... The goal of approximating metric spaces by more simple metric spaces has led to the notion of graph spanners [PU89, PS89] and to lowdistortion embeddings in lowdimensional spaces [LLR94], having many algorithmic applications. This paper provides a novel technique for the analysis of randomized ..."
Abstract

Cited by 351 (32 self)
 Add to MetaCart
. We prove that any metric space can be probabilisticallyapproximated by hierarchically wellseparated trees (HST) with a polylogarithmic distortion. These metric spaces are "simple" as being: (1) tree metrics. (2) natural for applying a divideandconquer algorithmic approach
Blobworld: Image segmentation using ExpectationMaximization and its application to image querying
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1999
"... Retrieving images from large and varied collections using image content as a key is a challenging and important problem. We present a new image representation which provides a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture. This "B ..."
Abstract

Cited by 438 (10 self)
 Add to MetaCart
;Blobworld" representation is created by clustering pixels in a joint colortextureposition feature space. The segmentation algorithm is fully automatic and has been run on a collection of 10,000 natural images. We describe a system that uses the Blobworld representation to retrieve images from this collection
Results 1  10
of
6,273