**NOTE: this talk is on Friday from 10-11am (not the regularly scheduled time)**
Abstract: There are three axes along which advances in machine learning and deep learning happen. They are (1) network architectures, (2) learning algorithms and (3) spatio-temporal abstraction. In this talk, I will describe a set of research topics I've pursued in each of these axes. For network architectures, I will describe how recurrent neural networks, which were largely forgotten during 90s and early 2000s, have evolved over time and have finally become a de facto standard in machine translation. I continue on to discussing various learning paradigms, how they related to each other, and how they are combined in order to build a strong learning system. Along this line, I briefly discuss my latest research on designing a query-efficient imitation learning algorithm for autonomous driving. Lastly, I present my view on what it means to be a higher-level learning system. Under this view each and every end-to-end trainable neural network serves as a module, regardless of how they were trained, and interacts with each other in order to solve a higher-level task. I will describe my latest research on trainable decoding algorithm as a first step toward building such a framework.
Bio: Kyunghyun Cho is an assistant professor of computer science and data science at New York University. He was a postdoctoral fellow at University of Montreal until summer 2015, and received PhD and MSc degrees from Aalto University early 2014. He tries best to find a balance among machine learning, natural language processing and life, but often fails to do so.
This semester of the UMass Machine Learning and Friends Lunch (MLFL) series has been graciously sponsored by our friends at Oracle Labs. MLFL is a lively and interactive forum held weekly where friends of the UMass Amherst machine learning community can sit down, have lunch, and give or hear a 50-minute presentation on recent machine learning research.
What is it? A gathering of students/faculty/staff with broad interest in the methods and applications of machine learning.
When is it? Thursdays 12:00pm to 1:00pm, unless otherwise noted. Arrive at 11:45 to get pizza.
Where is it? CS150
Who is invited? Everyone is welcome.
Is there food? Yes! Pizza is provided.
Can I present? Yes! If you would like to present your research, please email one of the organizers: Ari Kobren, Rajarshi Das, Li Yang Ku, Hang Su, Samer Nashed and Aruni Roy Chowdhury
Who generously sponsors this regular event Oracle Labs
Suggestions, comments, want to present? Contact us at firstname.lastname@example.org.