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NIPS
2008
13 years 10 months ago
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Guangzhi Cao, Charles A. Bouman
NIPS
2008
13 years 10 months ago
Asynchronous Distributed Learning of Topic Models
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
Arthur Asuncion, Padhraic Smyth, Max Welling
SDL
2007
152views Hardware» more  SDL 2007»
13 years 10 months ago
TTCN-3 Quality Engineering: Using Learning Techniques to Evaluate Metric Sets
Software metrics are an essential means to assess software quality. For the assessment of software quality, typically sets of complementing metrics are used since individual metric...
Edith Werner, Jens Grabowski, Helmut Neukirchen, N...
HIS
2004
13 years 10 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
CSREASAM
2003
13 years 10 months ago
KDD Feature Set Complaint Heuristic Rules for R2L Attack Detection
Automated rule induction procedures like machine learning and statistical techniques result in rules that lack generalization and maintainability. Developing rules manually throug...
Maheshkumar Sabhnani, Gürsel Serpen