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Composition-Representative Subsets

by Gary Griffing - THEORY AND APPLICATIONS OF CATEGORIES, VOL. 11, NO. 19, 2003, PP. 420--437 , 2003
"... A specific property applicable to subsets of a hom-set in any small category is defined. Subsets with this property are called composition-representative. The notion of composition-representability is motivated both by the representability of a linear functional on an associative algebra, and, by ..."
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A specific property applicable to subsets of a hom-set in any small category is defined. Subsets with this property are called composition-representative. The notion of composition-representability is motivated both by the representability of a linear functional on an associative algebra, and

Representative subset selection

by Doi /s, Michal Daszykowski, Beata Walczak, See Profile , 2002
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.

Clustering by passing messages between data points

by Brendan J. Frey, Delbert Dueck - Science , 2007
"... Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initi ..."
Abstract - Cited by 696 (8 self) - Add to MetaCart
Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only

Relations between the statistics of natural images and the response properties of cortical cells

by David J. Field - J. Opt. Soc. Am. A , 1987
"... The relative efficiency of any particular image-coding scheme should be defined only in relation to the class of images that the code is likely to encounter. To understand the representation of images by the mammalian visual system, it might therefore be useful to consider the statistics of images f ..."
Abstract - Cited by 831 (18 self) - Add to MetaCart
relatively high signal-to-noise ratio and permits information to be transmitted with only a subset of the total number of cells. These results support Barlow's theory that the goal of natural vision is to represent the information in the natural environment with minimal redundancy.

The Lumigraph

by Steven J. Gortler, Radek Grzeszczuk, Richard Szeliski, Michael F. Cohen - IN PROCEEDINGS OF SIGGRAPH 96 , 1996
"... This paper discusses a new method for capturing the complete appearanceof both synthetic and real world objects and scenes, representing this information, and then using this representation to render images of the object from new camera positions. Unlike the shape capture process traditionally used ..."
Abstract - Cited by 1025 (39 self) - Add to MetaCart
This paper discusses a new method for capturing the complete appearanceof both synthetic and real world objects and scenes, representing this information, and then using this representation to render images of the object from new camera positions. Unlike the shape capture process traditionally used

Markov Logic Networks

by Matthew Richardson, Pedro Domingos - MACHINE LEARNING , 2006
"... We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
Abstract - Cited by 816 (39 self) - Add to MetaCart
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects

Iterative point matching for registration of free-form curves and surfaces

by Zhengyou Zhang , 1994
"... A heuristic method has been developed for registering two sets of 3-D curves obtained by using an edge-based stereo system, or two dense 3-D maps obtained by using a correlation-based stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in ma ..."
Abstract - Cited by 660 (8 self) - Add to MetaCart
, which is required for environment modeling (e.g., building a Digital Elevation Map). Objects are represented by a set of 3-D points, which are considered as the samples of a surface. No constraint is imposed on the form of the objects. The proposed algorithm is based on iteratively matching points

Optimally sparse representation in general (non-orthogonal) dictionaries via ℓ¹ minimization

by David L. Donoho, Michael Elad - PROC. NATL ACAD. SCI. USA 100 2197–202 , 2002
"... Given a ‘dictionary’ D = {dk} of vectors dk, we seek to represent a signal S as a linear combination S = ∑ k γ(k)dk, with scalar coefficients γ(k). In particular, we aim for the sparsest representation possible. In general, this requires a combinatorial optimization process. Previous work considered ..."
Abstract - Cited by 633 (38 self) - Add to MetaCart
Given a ‘dictionary’ D = {dk} of vectors dk, we seek to represent a signal S as a linear combination S = ∑ k γ(k)dk, with scalar coefficients γ(k). In particular, we aim for the sparsest representation possible. In general, this requires a combinatorial optimization process. Previous work

Loopy belief propagation for approximate inference: An empirical study. In:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - Proceedings of Uncertainty in AI, , 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
likelihood weighting 3.1 The PYRAMID network All nodes were binary and the conditional probabilities were represented by tables-entries in the conditional probability tables (CPTs) were chosen uniformly in the range (0, 1]. 3.2 The toyQMR network All nodes were binary and the conditional probabilities

Discovering Frequent Closed Itemsets for Association Rules

by Nicolas Pasquier, Yves Bastide, Rafik Taouil, Lotfi Lakhal , 1999
"... In this paper, we address the problem of finding frequent itemsets in a database. Using the closed itemset lattice framework, we show that this problem can be reduced to the problem of finding frequent closed itemsets. Based on this statement, we can construct efficient data mining algorithms by lim ..."
Abstract - Cited by 410 (14 self) - Add to MetaCart
by limiting the search space to the closed itemset lattice rather than the subset lattice. Moreover, we show that the set of all frequent closed itemsets suffices to determine a reduced set of association rules, thus addressing another important data mining problem: limiting the number of rules produced
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