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» Approximate Discovery of Random Graphs
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ICML
2004
IEEE
14 years 8 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
ICML
2007
IEEE
14 years 8 months ago
Online discovery of similarity mappings
We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated ...
Alexander Rakhlin, Jacob Abernethy, Peter L. Bartl...
CPM
2011
Springer
283views Combinatorics» more  CPM 2011»
12 years 11 months ago
Frequent Submap Discovery
Combinatorial maps are nice data structures for modeling the topology of nD objects subdivided in cells (e.g., vertices, edges, faces, volumes, ...) by means of incidence and adjac...
Stéphane Gosselin, Guillaume Damiand, Chris...
ICML
2004
IEEE
14 years 8 months ago
SVM-based generalized multiple-instance learning via approximate box counting
The multiple-instance learning (MIL) model has been very successful in application areas such as drug discovery and content-based imageretrieval. Recently, a generalization of thi...
Qingping Tao, Stephen D. Scott, N. V. Vinodchandra...
FOCS
2009
IEEE
14 years 2 months ago
Faster Generation of Random Spanning Trees
In this paper, we set forth a new algorithm for generating approximately uniformly random spanning trees in undirected graphs. We show how to sample from a distribution that is wi...
Jonathan A. Kelner, Aleksander Madry