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Thursday 02 April 2015, 15:00-16:30
Informational Geometry
- đ¤ Speaker: Nilesh Tripuraneni, Shane Gu
- đ Date & Time: Thursday 02 April 2015, 15:00 - 16:30
- đ Venue: Engineering Department, CBL Room 438
Questions? Contact
Rowan McAllister
Abstract
Abstract: We will review the max-ent interpretation of exponential families, and it’s connection to information projections. After exploring some simple results about I-projections, Fisher information, and their relation to ideas in machine learning, we will explain how to geometrically interpret AdaBoost in this framework.
Optional Background: Familiarity with Lagrange Multipliers/Lagrange duality will be helpful
Series This talk is part of the Machine Learning Reading Group @ CUED series.
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