Sparse and large-scale learning with heterogeneous data

Google Tech Talks
September 5, 2006

Gert Lanckriet is assistant professor in the Electrical and Computer Engineering Department at the University of California, San Diego. He conducts research on machine learning, applied statistics and convex optimization with applications in computational biology, finance, music and vision. ABSTRACT
An important challenge for the field of machine learning is to deal with the increasing amount of data that is available for learning and to leverage the (also increasing) diversity of information sources, describing these data. Beyond classical vectorial data formats, data in the format of graphs, trees, strings and beyond have become widely available for data...

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[chrisrdow]

you should learn a little bit about what a typical engineer does. We dont sit in classrooms all day and learn from experts like this. Typically we are hearded like cattle by deviants (managers) and work for companies run by executives drawn from marketing who dont undertand how problems are solved, refuse to admit solving any difficult problem requires an amount of research and who (to a man !) instinctlively freeze when presented with a decision .

[troublemakerjo89]

i have a question, mmm i'm 16 years old and i really want to be a computer engineer later would it be helpful if i watched this?