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Events for March 05, 2015
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Computer Science PhD Visit Days
Thu, Mar 05, 2015
Thomas Lord Department of Computer Science
Workshops & Infosessions
Computer Science PhD Visit Day, March 5 and March 6, 2015. Details emailed to attendees. Includes Research Review at 3:30 PM on GER patio.
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Research Review and Poster Session
Thu, Mar 05, 2015 @ 03:30 PM - 06:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Come see Computer Science PhD Candidate research through an interactive poster session! Grab some light refreshments and see our students' current work. All departments are invited to attend.
Location: Ethel Percy Andrus Gerontology Center (GER) - Patio
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Prof. Ameet Talwalkar (UCLA) - Scalable and User-Friendly Machine Learning in Apache Spark
Thu, Mar 05, 2015 @ 04:00 PM - 05:15 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ameet Talwalkar, UCLA
Talk Title: Scalable and User-Friendly Machine Learning in Apache Spark
Series: CS Colloquium
Abstract: Modern datasets are rapidly growing in size and complexity, and this wealth of data holds the promise for many transformational applications. Machine learning is seemingly poised to deliver on this promise, having proposed and rigorously evaluated a wide range of data processing techniques over the past several decades. However, concerns over scalability and usability present major roadblocks to the wider adoption of these methods. In this talk I will describe the MLbase project, which aims to address these concerns by developing machine learning functionality on top of Apache Spark, a popular cluster computing engine designed for iterative computation. I will first describe MLlib, Sparkâs scalable machine learning library that grew out of the MLbase project. I will also discuss higher level components of MLbase, focusing on the problem of hyperparameter optimization as a means to simplify the task of machine learning pipeline construction.
Biography: Ameet Talwalkar is an assistant professor of Computer Science at UCLA and a technical advisor for Databricks. His research addresses scalability and ease-of-use issues in the field of statistical machine learning, with applications in computational genomics. He led the initial development of the MLlib project in Apache Spark and is a co-author of the graduate-level textbook 'Foundations of Machine Learning' (2012, MIT Press). Prior to UCLA, he was an NSF post-doctoral fellow in the AMPLab at UC Berkeley. He obtained a B.S. from Yale University and a Ph.D. from the Courant Institute at NYU.
Host: Fei Sha
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
