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NIPS
2004
13 years 10 months ago
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
SIAMIS
2008
279views more  SIAMIS 2008»
13 years 9 months ago
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
We propose, analyze and test an alternating minimization algorithm for recovering images from blurry and noisy observations with total variation (TV) regularization. This algorith...
Yilun Wang, Junfeng Yang, Wotao Yin, Yin Zhang
TIP
2008
126views more  TIP 2008»
13 years 8 months ago
Maximum-Entropy Expectation-Maximization Algorithm for Image Reconstruction and Sensor Field Estimation
Abstract--In this paper, we propose a maximum-entropy expectation-maximization (MEEM) algorithm. We use the proposed algorithm for density estimation. The maximum-entropy constrain...
Hunsop Hong, Dan Schonfeld
COLT
2005
Springer
14 years 2 months ago
Stability and Generalization of Bipartite Ranking Algorithms
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
Shivani Agarwal, Partha Niyogi
ECML
2006
Springer
13 years 11 months ago
Cascade Evaluation of Clustering Algorithms
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
Laurent Candillier, Isabelle Tellier, Fabien Torre...