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» Graph Based Semi-supervised Learning with Sharper Edges
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SAT
2009
Springer
117views Hardware» more  SAT 2009»
14 years 2 months ago
Dynamic Symmetry Breaking by Simulating Zykov Contraction
Abstract. We present a new method to break symmetry in graph coloring problems. While most alternative techniques add symmetry breaking predicates in a pre-processing step, we deve...
Bas Schaafsma, Marijn Heule, Hans van Maaren
PRIB
2010
Springer
192views Bioinformatics» more  PRIB 2010»
13 years 6 months ago
Structured Output Prediction of Anti-cancer Drug Activity
We present a structured output prediction approach for classifying potential anti-cancer drugs. Our QSAR model takes as input a description of a molecule and predicts the activity...
Hongyu Su, Markus Heinonen, Juho Rousu
FCT
2009
Springer
14 years 2 months ago
Competitive Group Testing and Learning Hidden Vertex Covers with Minimum Adaptivity
Suppose that we are given a set of n elements d of which are “defective”. A group test can check for any subset, called a pool, whether it contains a defective. It is well know...
Peter Damaschke, Azam Sheikh Muhammad
KDD
2008
ACM
150views Data Mining» more  KDD 2008»
14 years 8 months ago
Hypergraph spectral learning for multi-label classification
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Liang Sun, Shuiwang Ji, Jieping Ye
ECCV
2010
Springer
14 years 14 days ago
From a Set of Shapes to Object Discovery
Abstract. This paper presents an approach to object discovery in a given unlabeled image set, based on mining repetitive spatial configurations of image contours. Contours that si...