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Short stories about the working days of managers of the Baltimore & Ohio Railroad from 1950-1980. Some sad; some funny; all enlightening about working on the railroad in that time frame.
Lifelong Machine Learning (or Lifelong Learning) is an advanced machine learning paradigm that learns continuously, accumulates the knowledge learned in previous tasks, and uses it to help future learning. In the process, the learner becomes more and more knowledgeable and effective at learning. This learning ability is one of the hallmarks of human intelligence. However, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model. It makes no attempt to retain the learned knowledge and use it in future learning. Although this isolated learning paradigm has been very successful, it requir...
"Clark Gable is a man de-classed. You can't guess in any way where he came from or what he was." Frank Taylor, producer of Gable's last film, The Misfits (1961), said this of the man who, to many people, will forever be Southern gentleman Rhett Butler of Gone with the Wind. This work tells Gable's life story, from his birth in 1901 in Cadiz, Ohio, to his death in 1960 in Hollywood. It chronicles his stage career, and of course gives information on every one of his films. His family background, his development as a person, the many romances including five marriages, and his relationships with friends and co-workers are all explored in detail. The sources used and the bibliography are fully annotated.
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A young priest, unaware that he has only two years to live, is sent to a parish in the seacoast wilds of British Columbia.
Originally published in The New Yorker, Mollie Panter-Downes was the voice of England during the Second World War.
This book constitutes the thoroughly refereed post-proceedings of the RECOMB 2004 Satellite Workshop on Regulatory Genomics, RRG 2004, held in San Diego, CA, USA in March 2004. The 10 revised full papers presented were carefully reviewed and improved for inclusion in the book. The papers address a broad variety of aspects of regulatory genomics including classification, functional module detection, proteonomics, sampling, kernel methods, TF binding motifs, gene expression data analysis, regulatory network model learning, RNA regulatory sequence motifs, DNA regulatory sequence motifs, parameter landscape analysis, and biological network regulation.
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