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SIGIR
2006
ACM
15 years 3 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
ICDM
2005
IEEE
161views Data Mining» more  ICDM 2005»
15 years 3 months ago
Making Logistic Regression a Core Data Mining Tool with TR-IRLS
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Paul Komarek, Andrew W. Moore
GRAPHITE
2005
ACM
15 years 3 months ago
Uniting cartoon textures with computer assisted animation
We present a novel method to create perpetual animations from a small set of given keyframes. Existing approaches either are limited to re-sequencing large amounts of existing ima...
William Van Haevre, Fabian Di Fiore, Frank Van Ree...
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 3 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
GFKL
2005
Springer
142views Data Mining» more  GFKL 2005»
15 years 3 months ago
Near Similarity Search and Plagiarism Analysis
Abstract. Existing methods to text plagiarism analysis mainly base on “chunking”, a process of grouping a text into meaningful units each of which gets encoded by an integer nu...
Benno Stein, Sven Meyer zu Eissen