JMLR
2006
13 years 5 months ago
2006
In this work we consider the task of relaxing the i.i.d. assumption in pattern recognition (or classification), aiming to make existing learning algorithms applicable to a wider r...
IPL
2008
13 years 5 months ago
2008
An optimal labeling where labels are disjoint axis-parallel equal-size squares is called 2PM labeling if the labels have maximum length each attached to its corresponding point on...
FUIN
2006
13 years 5 months ago
2006
We examine the power and limitations of the weakest vertex relabelling system which allows to change a label of a vertex in function of its own label and of the label of one of its...
DM
2006
13 years 5 months ago
2006
Given a graph G, a function f : V (G) {1, 2, . . . , k} is a k-ranking of G if f (u) = f (v) implies every u - v path contains a vertex w such that f (w) > f (u). A k-ranking ...
DM
2006
13 years 5 months ago
2006
An L(h, k)-labeling of a graph G is an integer labeling of vertices of G, such that adjacent vertices have labels which differ by at least h, and vertices at distance two have lab...
COMCOM
2008
13 years 5 months ago
2008
Internet IP networks utilize multiple-protocol label switching (MPLS), which provides a reliable label switched path (LSP). LSP in MPLS domains needs one label at each Ingress lab...
CIC
2006
13 years 6 months ago
2006
Abstract-Requirement: Clients should experience high-availability when accessing network services. Availability should be transparent and not require altering programs. Problem: Av...
COLING
2008
13 years 6 months ago
2008
We present an algorithm for unsupervised induction of labeled parse trees. The algorithm has three stages: bracketing, initial labeling, and label clustering. Bracketing is done f...
AIML
2008
13 years 6 months ago
2008
Labelled tableaux are extensions of semantic tableaux with annotations (labels, indices) whose main function is to enrich the modal object language with semantic elements. This pap...
FOIKS
2008
Springer
13 years 6 months ago
2008
Springer
Supervised learning deals with the inference of a distribution over an output or label space Y conditioned on points in an observation space X , given a training dataset D of pair...