Events
DMS Statistics and Data Science Seminar |
| Time: Nov 12, 2020 (02:00 PM) |
| Location: ZOOM |
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Details: Speaker: Ernest Fokoué (School of Mathematical Sciences, Rochester Institute of Technology) Title: On the Ubiquity of Kernels in Statistical Machine Learning
Abstract: In this lecture, I will present a general tour of some of the most commonly used kernel methods in statistical machine learning and data mining. I will touch on elements of artificial neural networks and then highlight their intricate connections to some general purpose kernel methods like Gaussian process learning machines. I will also resurrect the famous universal approximation theorem and will most likely ignite a [controversial] debate around the theme: could it be that [shallow] networks like radial basis function networks or Gaussian processes are all we need for well behaved functions? Do we really need many hidden layers as the hype around Deep Neural Network architectures seem to suggest or should we heed Ockham’s principle of parsimony, namely “Entities should not be multiplied beyond necessity.” (“Entia non sunt multiplicanda praeter necessitatem.”)
Seminar website: http://webhome.auburn.edu/~ezc0066/stat-datasci-seminar.html
Join from PC, Mac, Linux, iOS or Android: https://auburn.zoom.us/j/93758346031 —————————————————————————————————————————————————————————— More details on the Zoom meeting.
Topic: Statistics & Data Science Seminar Time: Nov 12, 2020 02:00 PM Central Time (US and Canada)
Join from PC, Mac, Linux, iOS or Android: https://auburn.zoom.us/j/93758346031 Connect using Computer/Device audio if possible.
Or Telephone: Meeting ID: 937 5834 6031 Dial: +1 646 876 9923 (US Toll) or +1 301 715 8592 (US Toll)
Or an H.323/SIP room system: H.323: 162.255.37.11 (US West) or 162.255.36.11 (US East) Meeting ID: 937 5834 6031
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