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Displaying 1-7 out of 7 total
Distributed Flow Algorithms for Scalable Similarity Visualization
Found in: Data Mining Workshops, International Conference on
By Novi Quadrianto, Dale Schuurmans, Alex J. Smola
Issue Date:December 2010
pp. 1220-1227
We describe simple yet scalable and distributed algorithms for solving the maximum flow problem and its minimum cost flow variant, motivated by problems of interest in objects similarity visualization. We formulate the fundamental problem as a convex-conca...
 
Learning Graph Matching
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Tibério S. Caetano, Julian J. McAuley, Li Cheng, Quoc V. Le, Alex J. Smola
Issue Date:June 2009
pp. 1048-1058
As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspon...
 
Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments
Found in: Neural Networks, IEEE - INNS - ENNS International Joint Conference on
By Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
Issue Date:July 2000
pp. 5199
In Support Vector (SV) regression, a parameter \math controls the number of Support Vectors and the number of points that come to lie outside of the so-called \math-insensitive tube. For various noise models and SV parameter settings, we experimentally det...
 
Learning Graph Matching
Found in: Computer Vision, IEEE International Conference on
By Tiberio S. Caetano, Li Cheng, Quoc V. Le, Alex J. Smola
Issue Date:October 2007
pp. 1-8
As a fundamental problem in pattern recognition, graph matching has found a variety of applications in the field of computer vision. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the n...
 
Kernelized Sorting
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Novi Quadrianto, Alex J. Smola, Le Song, Tinne Tuytelaars
Issue Date:October 2010
pp. 1809-1821
Object matching is a fundamental operation in data analysis. It typically requires the definition of a similarity measure between the classes of objects to be matched. Instead, we develop an approach which is able to perform matching by requiring a similar...
 
Estimating labels from label proportions
Found in: Proceedings of the 25th international conference on Machine learning (ICML '08)
By Alex J. Smola, Novi Quadrianto, Quoc V. Le, Tiberio S. Caetano
Issue Date:July 2008
pp. 776-783
Consider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, also with known label proportions. This problem appears in areas like e-commerce, spam filtering...
     
Simpler knowledge-based support vector machines
Found in: Proceedings of the 23rd international conference on Machine learning (ICML '06)
By Alex J. Smola, Quoc V. Le, Thomas Gartner
Issue Date:June 2006
pp. 521-528
If appropriately used, prior knowledge can significantly improve the predictive accuracy of learning algorithms or reduce the amount of training data needed. In this paper we introduce a simple method to incorporate prior knowledge in support vector machin...
     
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