Lev Reyzin
PhD Student
Department of Computer Science
Yale University
left. A picture of me on a bridge at Cornell
I am a 3rd year Computer
Science Ph.D. student at Yale University
in Connecticut, on an NSF Graduate
Fellowship.
Before starting grad school, I graduated from Princeton University where I got a B.S.E.
degree in Computer Science and a
certificate in Applied Math.
I have spent the previous two summers doing research at Google in California.
I am interested in theoretical computer
science and machine
learning, especially
computational learning theory.
My advisor is Professor Dana
Angluin.
My current research focus within learning theory lies in learning hidden
structures such as circuits, networks, and graphs. I am interested in creating
and analyzing query models that are motivated by real-world problems, often
from bioinformatics.
I have also done work on boosting and online learning, and I am interested in many
other areas in machine learning and theoretical computer science.
Dana Angluin, James Aspnes, Jiang Chen, and Lev Reyzin
Learning Large-Alphabet and Analog Circuits with Value Injection Queries
In the
Machine Learning Journal, COLT 2007 Special Issue (MLJ), March 2008
pdf (see conference version)
Lev Reyzin and Nikhil Srivastava
On the Longest Path Algorithm for Reconstructing Trees from Distance Matrices
In Information
Processing Letters, Volume 101, Issue 3 (IPL), February 2007
pdf
bibtex
Dana Angluin, James Aspnes, and Lev Reyzin
Optimally Learning Social Networks with Activations and Suppressions
To appear in In Proceedings of the 19th International Conference
on Algorithmic Learning Theory (ALT), October 2008
pdf (to appear)
Dana Angluin, James Aspnes, Jiang Chen, David Eisenstat,
and Lev Reyzin
Learning Acyclic Probabilistic Circuits Using Test Paths
In
Proceedings of the 21st Annual Conference on Learning Theory (COLT), July 2008
pdf
slides
bibtex
Lev Reyzin and Nikhil Srivastava
Learning and Verifying Graphs Using Queries with a Focus on Edge
Counting
In Proceedings of the 18th International
Conference on Algorithmic Learning Theory (ALT), October 2007.
pdf
(co-author's) slides
bibtex
Dana Angluin, James Aspnes, Jiang Chen, and Lev Reyzin
Learning Large-Alphabet and Analog Circuits with Value Injection Queries
In
Proceedings of the 20th Annual Conference on Learning Theory (COLT), June 2007
won the best student paper award
pdf
slides
bibtex (see journal version)
Lev Reyzin and Robert E. Schapire
How Boosting the Margin Can Also Boost Classifier Complexity
In Proceedings of the 23rd International Conference on Machine Learning
(ICML), June 2006
won the best student paper award
pdf
slides
bibtex
Workshop Papers and Technical Reports
Lev Reyzin
2 Player Tetris is PSPACE Hard
In the Abstracts of the 16th Annual Fall Workshop on Computational
Geometry (FWCG), November 2006.
pdf
bibtex
Lev Reyzin
Lower Bounds on the VC Dimension of Unions of Concept Classes
Yale
University Technical Report YALEU/DCS/TR-1349, April 2006
pdf
bibtex
Undergraduate Research
Lev Reyzin. Advisor: Robert Schapire
Analyzing Margins in Boosting
For the BSE degree in Computer Science, Fall 2004
pdf
Lev Reyzin. Advisor: Moses Charikar
Online Clustering of Linguistic Data
For the Certificate in Applied Mathematics, Spring 2004
pdf
data
Ryan Peterson and Lev Reyzin. Advisor: Brian Kernighan
Visualization of Planet-Lab Network Data
PURE summer research program, Summer 2003
link
Academic Activities
Theoretical Computer Science at Yale
Yale's Graduate Student Theory Group,
The Clique
Princeton's group on
New Directions in
Clustering and Learning
Talks
Summer 2008: COLT 2008. "Learning Acyclic Probabilistic Circuits Using Test
Paths" by Angluin, Aspnes, Chen, Eisenstat, and Reyzin.
slides
Spring 2008: Yahoo! Research, NY. "Learning Hidden Circuits and
(Social) Networks by Injecting Values"
by Angluin, Aspnes, and Reyzin. slides
Fall 2007: Machine Learning Lunch, UMass Amherst. "Learning Hidden Graphs and
Circuits with Query Access" on AACR'07 and RS'07. slides
Summer 2007: COLT 2007. "Learning Large-Alphabet and Analog Circuits with Value
Injection Queries" by Angluin, Aspnes, Chen, and Reyzin. slides
Spring 2007: Clique, Yale University. "Hardness Results for Learning DNF" on papers by Alekhnovich, Braverman, Feldman, Klivans and
Pitassi. slides
Spring 2007: Clique, Yale University. "Boosting the Margin" on 4 papers authored among Freund, Schapire, Bartlett, Lee, Breiman, and Reyzin. slides
Fall 2006: Clique, Yale University. "Learning Graphs with Queries" on works
authored among Angluin, Chen, Reyzin, and Srivastava slides
Summer/Fall 2006: ICML 2006, Princeton, NYAS. "How Boosting the Margin Can Also Boost
Classifier Complexity" by Reyzin and Schapire. slides
Spring 2006: Clique, Yale University. "Go is PSPACE Hard" by Lichtenstein
and Sipser. slides
Fall 2005: Clique, Yale University. A talk on boosting results by Reyzin
and Schapire. slides
Other
I sometimes take photos.
My Erdös number is 3.
My DBLP
entry
vita