Date & Time:
January 24, 2020 10:30 am – 11:30 am
Location:
TTIC 526, 6045 S. Kenwood Ave., Chicago, IL,
01/24/2020 10:30 AM 01/24/2020 11:30 AM America/Chicago Steve Hanneke (TTIC) – Learning Whenever Learning is Possible: Universal Learning Under General Stochastic Processes UChicago CS/TTIC Machine Learning Seminar Series TTIC 526, 6045 S. Kenwood Ave., Chicago, IL,

Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes

I will present a general theory of learning and generalization without the i.i.d. assumption, starting from first principles. We focus on the problem of universal consistency: the ability to estimate any function from X to Y. We endeavor to answer the question: Does there exist a learning algorithm that is universally consistent under every process on X for which universal consistency is possible? Remarkably, we find the answer is “Yes”. Thus, we replace the i.i.d. assumption with only the most natural (and necessary!) assumption: that learning is at least possible. Along the way, we also find a concise characterization of the family of all processes that admit universally consistent learners. One challenge for learning is that some of these processes do not even have a law of large numbers.

Host: Brian Bullins

Steve Hanneke

Research Assistant Professor, Toyota Technological Institute of Chicago

Steve Hanneke is a Research Assistant Professor at the Toyota Technological Institute at Chicago. His research explores the theory of machine learning, with a focus on reducing the number of training examples sufficient for learning. His work develops new approaches to supervised, semi-supervised, transfer, and active learning, and also revisits the basic probabilistic assumptions at the foundation of learning theory. Steve earned a Bachelor of Science degree in Computer Science from UIUC in 2005 and a Ph.D. in Machine Learning from Carnegie Mellon University in 2009 with a dissertation on the theoretical foundations of active learning.

Related News & Events

Students posing at competition
No Name

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

Mar 17, 2023
Haifeng Xu
No Name

New CS and DSI Faculty Haifeng Xu Brings Strategic Intelligence to NeurIPS 2022

Nov 28, 2022
No Name

UChicago CS Research Finds New Angle on Database Query Processing with Geometry

Nov 08, 2022
No Name

Asst. Prof. Aloni Cohen Receives Award For Revealing Flaws in Deidentifying Data

Sep 09, 2022
No Name

UChicago Hosts NSF Workshop on Frontiers of Quantum Advantage

Aug 15, 2022
No Name

New 2022-23 Faculty Add Expertise in Linguistics, Visualization, Economics, and Data Science Education

Aug 11, 2022
No Name

UChicago Co-Leads $10 Million NSF Institute on Foundations of Data Science

Aug 09, 2022
No Name

Bill Fefferman Comments on New Standards for Quantum-Proof Cryptography

Jul 07, 2022
No Name

UChicago London Colloquium Features Data Science, Quantum Research

Jul 01, 2022
No Name

Faculty Bill Fefferman and Chenhao Tan Receive Google Research Scholar Awards

Jun 21, 2022
No Name

First-Year PhD Student Co-Authors Outstanding Paper Award Winner at TQC 2022

Apr 28, 2022
No Name

Quanta Magazine Features Prof. Bill Fefferman’s Work on Quantum Algorithms

Jan 20, 2022
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