Date & Time:
February 21, 2019 2:00 pm – 3:00 pm
Location:
Crerar 390, 5730 S. Ellis Ave., Chicago, IL,
02/21/2019 02:00 PM 02/21/2019 03:00 PM America/Chicago Chi Jin (UC Berkeley) – Machine Learning: Why Do Simple Algorithms Work So Well? Crerar 390, 5730 S. Ellis Ave., Chicago, IL,

Machine Learning: Why Do Simple Algorithms Work So Well?

While state-of-the-art machine learning models are deep, large-scale, sequential and highly nonconvex, the backbone of modern learning algorithms are simple algorithms such as stochastic gradient descent, or Q-learning (in the case of reinforcement learning tasks). A basic question endures—why do simple algorithms work so well even in these challenging settings? 

This talk focuses on two fundamental problems: (1) in nonconvex optimization, can gradient descent escape saddle points efficiently? (2) in reinforcement learning, is Q-learning sample efficient? We will provide the first line of provably positive answers to both questions. In particular, we will show that simple modifications to these classical algorithms guarantee significantly better properties, which explains the underlying mechanisms behind their favorable performance in practice.

Host: Rebecca Willett

Chi Jin

Ph.D. Candidate, University of California, Berkeley

Chi Jin is a Ph.D. candidate in Computer Science at UC Berkeley, advised by Michael I. Jordan. He received a B.S. in Physics from Peking University. His research interests lie in machine learning, statistics, and optimization, with his PhD work primarily focused on nonconvex optimization and reinforcement learning. 

Related News & Events

Video

“Machine Learning Foundations Accelerate Innovation and Promote Trustworthiness” by Rebecca Willett

Jan 26, 2024
Video

Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao

Jan 23, 2024
In the News

In The News: U.N. Officials Urge Regulation of Artificial Intelligence

"Security Council members said they feared that a new technology might prove a major threat to world peace."
Jul 27, 2023
UChicago CS News

UChicago Computer Scientists Bring in Generative Neural Networks to Stop Real-Time Video From Lagging

Jun 29, 2023
UChicago CS News

Computer Science Displays Catch Attention at MSI’s Annual Robot Block Party

Apr 07, 2023
UChicago CS News

UChicago, Stanford Researchers Explore How Robots and Computers Can Help Strangers Have Meaningful In-Person Conversations

Mar 29, 2023
Students posing at competition
UChicago CS News

UChicago Undergrad Team Places Second Overall In Regionals For World’s Largest Programming Competition

Mar 17, 2023
UChicago CS News

Postdoc Alum John Paparrizos Named ICDE Rising Star

Mar 15, 2023
UChicago CS News

New EAGER Grant to Asst. Prof. Eric Jonas Will Explore ML for Quantum Spectrometry

Mar 03, 2023
UChicago CS News

Assistant Professor Chenhao Tan Receives Sloan Research Fellowship

Feb 15, 2023
UChicago CS News

UChicago Scientists Develop New Tool to Protect Artists from AI Mimicry

Feb 13, 2023
In the News

Professors Rebecca Willett and Ben Zhao Discuss the Future of AI on Public Radio

Jan 26, 2023
arrow-down-largearrow-left-largearrow-right-large-greyarrow-right-large-yellowarrow-right-largearrow-right-smallbutton-arrowclosedocumentfacebookfacet-arrow-down-whitefacet-arrow-downPage 1CheckedCheckedicon-apple-t5backgroundLayer 1icon-google-t5icon-office365-t5icon-outlook-t5backgroundLayer 1icon-outlookcom-t5backgroundLayer 1icon-yahoo-t5backgroundLayer 1internal-yellowinternalintranetlinkedinlinkoutpauseplaypresentationsearch-bluesearchshareslider-arrow-nextslider-arrow-prevtwittervideoyoutube