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| Optimization for Machine Learning |
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Google Tech Talks
March, 25 2008
ABSTRACT
S.V.N. Vishwanathan - Research Scientist
Regularized risk minimization is at the heart of
many machine learning algorithms. The underlying
objective function to be minimized is convex, and
often non-smooth. Classical optimization
algorithms cannot handle this efficiently. In this
talk we present two algorithms for dealing with
convex non-smooth objective functions. First, we
extend the well known BFGS quasi-Newton algorithm
to handle non-smooth
functions. Second, we show how bundle methods can
be applied in a machine learning context. We
present both theoretical and experimental
justification of our algorithms.
Speaker: S.V.N. Vishwanathan - Research Scientist
- Zurich
S.V.N Vishwanathan is a principal researcher in
the Statistical Machine Learning program, National
ICT Australia with an adjunct appointment at the
College of Engineering and Computer Science(CECS),
Australian National University. I got my Ph.D in
2002 from the Department of Computer Science and
Automation (CSA) at the Indian Institute of
Science. Tags : google techtalks techtalk engedu talk talks googletechtalks education |
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Affichage : 2845
Durée : 3344 s |
| Search Engine Optimization SEO Tutorial -- WebBizIdeas |
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Search Engine Optimization SEO Tutorial by
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release optimization. Tags : Search Engine Optimization SEO Tutotial WebBizIdeas internet marketing increase search engine rankings techniques |
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Affichage : 43
Durée : 543 s |
| Learning Search Engine Optimization |
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http://www.ryanmoran.org - Learning Search Engine
Optimization
Search engine is a skill that internet marketing
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early in your career as an online marketer. Tags : Learning Search Engine Optimization seo |
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Affichage : 99
Durée : 242 s |
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