Sciweavers

TVCG
2008
108views more  TVCG 2008»
13 years 4 months ago
Particle-based labeling: Fast point-feature labeling without obscuring other visual features
In many information visualization techniques, labels are an essential part to communicate the visualized data. To preserve the expressiveness of the visual representation, a placed...
Martin Luboschik, Heidrun Schumann, Hilko Cords
JCO
2007
128views more  JCO 2007»
13 years 5 months ago
Approximation algorithms and hardness results for labeled connectivity problems
Let G = (V, E) be a connected multigraph, whose edges are associated with labels specified by an integer-valued function L : E → N. In addition, each label ℓ ∈ N has a non-...
Refael Hassin, Jérôme Monnot, Danny S...
JANCL
2007
74views more  JANCL 2007»
13 years 5 months ago
Operations on proofs and labels
Logic of proofs LP introduced by S. Artemov in 1995 describes properties of proof predicate “t is a proof of F” in the propositional language extended by atoms of the form [[t...
Tatiana Yavorskaya, Natalia Rubtsova
TCOM
2008
81views more  TCOM 2008»
13 years 5 months ago
On optimal computation of MPLS label binding for multipoint-to-point connections
Most network operators have considered reducing Label Switched Routers (LSR) label spaces (i.e. the number of labels that can be used) as a means of simplifying management of under...
Fernando Solano, Ramón Fabregat, José...
SYNTHESE
2008
130views more  SYNTHESE 2008»
13 years 5 months ago
Appropriateness measures: an uncertainty model for vague concepts
Abstract We argue that in the decision making process required for selecting assertible vague descriptions of an object, it is practical that communicating agents adopt an epistemi...
Jonathan Lawry
PAMI
2006
206views more  PAMI 2006»
13 years 5 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
JMLR
2006
99views more  JMLR 2006»
13 years 5 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
JMLR
2006
125views more  JMLR 2006»
13 years 5 months ago
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...
Shai Shalev-Shwartz, Yoram Singer
JMLR
2006
109views more  JMLR 2006»
13 years 5 months ago
Some Discriminant-Based PAC Algorithms
A classical approach in multi-class pattern classification is the following. Estimate probability distributions that generated the observations for each label class, and then labe...
Paul W. Goldberg
JCT
2006
75views more  JCT 2006»
13 years 5 months ago
Sperner labellings: A combinatorial approach
In 2002, De Loera, Peterson and Su proved the following conjecture of Atanassov: let T be a triangulation of a d-dimensional polytope P with n vertices v1, v2, . . . , vn; label t...
Frédéric Meunier