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Results 1 - 10
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441
A Distance-Based Branch and Bound Feature Selection Algorithm
- UAI 2003
, 2003
"... There is no known efficient method for selecting k Gaussian features from n which achieve the lowest Bayesian classification error. We show an example of how greedy algorithms faced with this task are led to give results that are not optimal. This motivates us to propose a more robust approach. We p ..."
Abstract
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Cited by 1 (0 self)
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present a Branch and Bound algorithm for finding a subset of k independent Gaussian features which minimizes the naive Bayesian classification error. Our algorithm uses additive monotonic distance measures to produce bounds for the Bayesian classification error in order to exclude many feature subsets
Near-optimal sensor placements in gaussian processes
- In ICML
, 2005
"... When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to address this task, for example, geometry or disk models, placing sensors at the points of highest entropy (variance) in t ..."
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Cited by 342 (34 self)
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information is NP-complete. To address this issue, we describe a polynomial-time approximation that is within (1 − 1/e) of the optimum by exploiting the submodularity of mutual information. We also show how submodularity can be used to obtain online bounds, and design branch and bound search procedures. We
An improved branch and bound algorithm for feature selection
- Pattern Recognition Letters
, 2003
"... Feature selection plays an important role in pattern classification. In this paper, we present an improved Branch and Bound algorithm for optimal feature subset selection. This algorithm searches for an optimal solution in a large solution tree in an efficient manner by cutting unnecessary paths whi ..."
Abstract
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Cited by 18 (0 self)
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Feature selection plays an important role in pattern classification. In this paper, we present an improved Branch and Bound algorithm for optimal feature subset selection. This algorithm searches for an optimal solution in a large solution tree in an efficient manner by cutting unnecessary paths
Fast Branch Bound Algorithm in Feature Selection
"... We introduce a novel algorithm for optimal subset selection. Due to its simple mechanism for predicting criterion values the algorithm finds optimum usually several times faster than any other known Branch & Bound [5], [7] algorithm. This behavior is expected when the algorithm is used in conjun ..."
Abstract
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Cited by 9 (2 self)
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We introduce a novel algorithm for optimal subset selection. Due to its simple mechanism for predicting criterion values the algorithm finds optimum usually several times faster than any other known Branch & Bound [5], [7] algorithm. This behavior is expected when the algorithm is used
Fast branch & bound algorithms for optimal feature selection
- IEEE Pattern Analysis and Machine Intelligence
, 2004
"... Abstract—A novel search principle for optimal feature subset selection using the Branch & Bound method is introduced. Thanks to a simple mechanism for predicting criterion values, a considerable amount of time can be saved by avoiding many slow criterion evaluations. We propose two implementatio ..."
Abstract
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Cited by 41 (4 self)
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Abstract—A novel search principle for optimal feature subset selection using the Branch & Bound method is introduced. Thanks to a simple mechanism for predicting criterion values, a considerable amount of time can be saved by avoiding many slow criterion evaluations. We propose two
An optimal and progressive algorithm for skyline queries
- In SIGMOD
, 2003
"... The skyline of a set of d-dimensional points contains the points that are not dominated by any other point on all dimensions. Skyline computation has recently received considerable attention in the database community, especially for progressive (or online) algorithms that can quickly return the firs ..."
Abstract
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Cited by 225 (16 self)
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points, applicability to arbitrary data distributions and dimensions), it also presents several inherent disadvantages (need for duplicate elimination if d>2, multiple accesses of the same node, large space overhead). In this paper we develop BBS (branch-and-bound skyline), a progressive algorithm
Branch and Bound Algorithm Selection by Performance Prediction
- In AAAI
, 1998
"... We propose a method called Selection by Performance Prediction (SPP) which allows one, when faced with a particular problem instance, to select a Branch and Bound algorithm from among several promising ones. This method is based on Knuth's sampling method which estimates the efficiency of ..."
Abstract
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Cited by 37 (1 self)
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We propose a method called Selection by Performance Prediction (SPP) which allows one, when faced with a particular problem instance, to select a Branch and Bound algorithm from among several promising ones. This method is based on Knuth's sampling method which estimates the efficiency
Constrained branch-and-bound algorithm for image registration *
, 2005
"... Abstract: In this paper, the authors propose a refined Branch-and-Bound algorithm for affine-transformation based image registration. Given two feature point-sets in two images respectively, the authors first extract a sequence of high-probability matched point-pairs by considering well-defined feat ..."
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Abstract: In this paper, the authors propose a refined Branch-and-Bound algorithm for affine-transformation based image registration. Given two feature point-sets in two images respectively, the authors first extract a sequence of high-probability matched point-pairs by considering well
A performance comparison of distance-based query algorithms using R-trees in spatial databases
, 2006
"... Efficient processing of distance-based queries (DBQs) is of great importance in spatial databases due to the wide area of applications that may address such queries. The most representative and known DBQs are the K Nearest Neighbors Query (KNNQ), q Distance Range Query (qDRQ), K Closest Pairs Query ..."
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Cited by 1 (0 self)
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Efficient processing of distance-based queries (DBQs) is of great importance in spatial databases due to the wide area of applications that may address such queries. The most representative and known DBQs are the K Nearest Neighbors Query (KNNQ), q Distance Range Query (qDRQ), K Closest Pairs Query
Multiscale Branch and Bound Image Database Search
- In SPIE: Storage and Retrieval for Image and Video Databases V
, 1997
"... This paper presents a formal framework for designing search algorithms which can identify target images by the spatial distribution of color, edge and texture attributes. The framework is based on a multiscale representation of both the image data, and the associated parameter space that must be sea ..."
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Cited by 11 (2 self)
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be searched. We define a general form for the distance function which insures that branch and bound search can be used to find the globally optimal match. Our distance function depends on the choice of a convex measure of feature distance. For this purpose, we propose the L 1 norm and some other alternative
Results 1 - 10
of
441
