Results 11  20
of
3,364
The Usual Suspects: DataOriented Models for the Identification and Representation of Lexical Collocations. DFKI & Universit t des Saarlandes, Saarbrcken
 Bioinformatics
, 2005
"... Summary: VizRank is a tool that finds interesting twodimensional projections of classlabeled data. When applied to multidimensional functional genomics data sets, VizRank can systematically find relevant biological patterns. ..."
Abstract

Cited by 11 (3 self)
 Add to MetaCart
Summary: VizRank is a tool that finds interesting twodimensional projections of classlabeled data. When applied to multidimensional functional genomics data sets, VizRank can systematically find relevant biological patterns.
unknown title
"... Summary: VizRank is a tool that finds interesting twodimensional projections of classlabeled data. When applied to multidimensional functional genomics datasets, VizRank can systematically find relevant biological patterns. ..."
Abstract
 Add to MetaCart
Summary: VizRank is a tool that finds interesting twodimensional projections of classlabeled data. When applied to multidimensional functional genomics datasets, VizRank can systematically find relevant biological patterns.
Interactive Volume Rendering Using MultiDimensional Transfer Functions and Direct Manipulation Widgets
, 2001
"... Most direct volume renderings produced today employ onedimensional transfer functions, which assign color and opacity to the volume based solely on the single scalar quantity which comprises the dataset. Though they have not received widespread attention, multidimensional transfer functions are a ..."
Abstract

Cited by 180 (10 self)
 Add to MetaCart
Most direct volume renderings produced today employ onedimensional transfer functions, which assign color and opacity to the volume based solely on the single scalar quantity which comprises the dataset. Though they have not received widespread attention, multidimensional transfer functions are a
A Theory of Networks for Approximation and Learning
 Laboratory, Massachusetts Institute of Technology
, 1989
"... Learning an inputoutput mapping from a set of examples, of the type that many neural networks have been constructed to perform, can be regarded as synthesizing an approximation of a multidimensional function, that is solving the problem of hypersurface reconstruction. From this point of view, t ..."
Abstract

Cited by 235 (24 self)
 Add to MetaCart
Learning an inputoutput mapping from a set of examples, of the type that many neural networks have been constructed to perform, can be regarded as synthesizing an approximation of a multidimensional function, that is solving the problem of hypersurface reconstruction. From this point of view
MultiDimensional Online Tracking ∗
"... We propose and study a new class of online problems, which we call online tracking. Suppose an observer, say Alice, observes a multivalued function f: Z + → Z d over time in an online fashion, i.e., she only sees f(t) for t ≤ tnow where tnow is the current time. She would like to keep a tracker, sa ..."
Abstract

Cited by 26 (2 self)
 Add to MetaCart
We propose and study a new class of online problems, which we call online tracking. Suppose an observer, say Alice, observes a multivalued function f: Z + → Z d over time in an online fashion, i.e., she only sees f(t) for t ≤ tnow where tnow is the current time. She would like to keep a tracker
Indexing multidimensional uncertain data with arbitrary probability density functions
 In Proc. VLDB
, 2005
"... In an “uncertain database”, an object o is associated with a multidimensional probability density function (pdf), which describes the likelihood that o appears at each position in the data space. A fundamental operation is the “probabilistic range search ” which, given a value pq and a rectangular ..."
Abstract

Cited by 116 (15 self)
 Add to MetaCart
In an “uncertain database”, an object o is associated with a multidimensional probability density function (pdf), which describes the likelihood that o appears at each position in the data space. A fundamental operation is the “probabilistic range search ” which, given a value pq and a rectangular
Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing
 Advances in Neural Information Processing Systems 9
, 1996
"... The Support Vector (SV) method was recently proposed for estimating regressions, constructing multidimensional splines, and solving linear operator equations [Vapnik, 1995]. In this presentation we report results of applying the SV method to these problems. 1 Introduction The Support Vector method i ..."
Abstract

Cited by 292 (24 self)
 Add to MetaCart
is a universal tool for solving multidimensional function estimation problems. Initially it was designed to solve pattern recognition problems, where in order to find a decision rule with good generalization ability one selects some (small) subset of the training data, called the Support Vectors (SVs
MULTIDIMENSIONAL IMAGE RECONSTRUCTION AND FIELD ESTIMATION FROM RANDOMLY SCATTERED SENSORS
"... Many important problems in statistical signal processing can be formulated as function estimation from randomly scattered sensors in a multidimensional space, e.g. image reconstruction from photonlimited images. We model the problem of image reconstruction and field estimation from scattered senso ..."
Abstract
 Add to MetaCart
Many important problems in statistical signal processing can be formulated as function estimation from randomly scattered sensors in a multidimensional space, e.g. image reconstruction from photonlimited images. We model the problem of image reconstruction and field estimation from scattered
HighSpeed Policybased Packet Forwarding Using Efficient Multidimensional Range Matching
 In ACM SIGCOMM
, 1998
"... The ability to provide differentiated services to users with widely varying requirements is becoming increasingly important, and Internet Service Providers would like to provide these differentiated services using the same shared network infrastructure. The key mechanism, that enables differentiatio ..."
Abstract

Cited by 172 (0 self)
 Add to MetaCart
differentiation in a connectionless network, is the packet classification function that parses the headers of the packets, and after determining their context, classifies them based on administrative policies or realtime reservation decisions. Packet classification, however, is a complex operation that can
Results 11  20
of
3,364