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106 documents found. Order: date indexed.

Active Learning for Multi-Class Logistic Regression - Schein, Ungar (2005)   (Correct)
Logistic Regression Andrew I. Schein and Lyle H. Ungar 1 Department of Computer and
Multi-Class Logistic Regression Andrew I. Schein, Lyle H. Ungar
Logistic Regression Andrew I. Schein and Lyle H. Ungar 1 Department of Computer and Information

www.cis.upenn.edu/~ais/./publications/snowbird2005abstract.ps.gz

Active Learning for Logistic Regression - Schein (2005)   (Correct)
for the Degree of Doctor of Philosophy 2005 Lyle H. Ungar Supervisor of Dissertation Rajeev Alur
Deborah E. Schein. I thank my dissertation adviser, Lyle H. Ungar, for many years of advice and guidance
for the Degree of Doctor of Philosophy 2005 Lyle H. Ungar Supervisor of Dissertation Rajeev Alur Graduate

www.cis.upenn.edu/~ais/./publications/schein.ps.gz

CROC: A New Evaluation Criterion for Recommender Systems - Andrew Schein Alexandrin   (Correct)
1 Andrew I. Schein 2 Alexandrin Popescul and Lyle H. Ungar University of Pennsylvania Dept. of
multiple observations that are identical (e.g.Lyle saw Memento twice)With each observation we
I. Schein 2 Alexandrin Popescul and Lyle H. Ungar University of Pennsylvania Dept. of Computer &

www.cis.upenn.edu/~ais/./publications/scheinECR.ps.gz

Streaming Feature Selection using IIC - Lyle Ungar And (2005)   (Correct)
Streaming Feature Selection using IIC Lyle H. Ungar and Jing Zhou Computer and Information
2005. Streaming Feature Selection using IIC Lyle Ungar And
Streaming Feature Selection using IIC Lyle H. Ungar and Jing Zhou Computer and Information Science

www.gatsby.ucl.ac.uk/aistats/fullpapers/241.pdf

Integrated Annotation for Biomedical Information Extraction - Seth Kulick And (2004)   (Correct)   (1 citation)
McDonald and Martha Palmer and Andrew Schein and Lyle Ungar University of Pennsylvania Philadelphia, PA
Ryan McDonald Martha Palmer Andrew Schein and Lyle Ungar. 2004. Integrated annotation for biomedical
and Martha Palmer and Andrew Schein and Lyle Ungar University of Pennsylvania Philadelphia, PA

www.cis.upenn.edu/~ais/./publications/BioLink2004.pdf

A Simple Ascending Generalized Vickrey Auction - David Parkes Debasis   (Correct)
Auction #David C. Parkes Debasis Mishra #Lyle H. Ungar December 31, 2004 Abstract We design a
Commerce, Forthcoming. 31] David C. Parkes and Lyle H. Ungar. Iterative Combinatorial Auctions: Theory
# David C. Parkes Debasis Mishra #Lyle H. Ungar December 31, 2004 Abstract We design a simple

www.eecs.harvard.edu/econcs/pubs/newibea.pdf

Exploiting Multiple Secondary Reinforcers in Policy Gradient.. - Grudic, Ungar (2001)   (Correct)
Philadelphia, PA, USA grudic@linc.cis.upenn.edu Lyle Ungar Computer and Information Science University
Policy Gradient Reinforcement Learning Greg Grudic, Lyle Ungar
PA, USA grudic@linc.cis.upenn.edu Lyle Ungar Computer and Information Science University of

www.cs.colorado.edu/~grudic/publications/GrudicUngarIJCAI01.ps

Seventeenth National Conference on Artificial Intelligence .. - Greg Grudic Institute (2000)   (Correct)
Philadelphia, PA, USA grudic@linc.cis.upenn.edu Lyle Ungar Computer and Information Science University
PA, USA grudic@linc.cis.upenn.edu Lyle Ungar Computer and Information Science University of
University of Pennsylvania Philadelphia, PA, USA ungar@cis.upenn.edu Abstract Reinforcement learning

www.cs.colorado.edu/~grudic/publications/GrudicUngarAAAI2000.ps

Using Policy Gradient Reinforcement Learning on Autonomous .. - Controllers Gregory Grudic (2003)   (Correct)
of Pennsylvania Philadelphia, PA 19104-6228 USA Lyle Ungar Computer and Information Science University
Pennsylvania Philadelphia, PA 19104-6228 USA Lyle Ungar Computer and Information Science University of
Morgan Kaufmann, 2002. 17] G. Z. Grudic and L. H. Ungar, Localizing search in reinforcement learning,

www.cs.colorado.edu/~grudic/publications/iros2003.pdf

An Auction-Based Method for Decentralized Train - Scheduling David Parkes   (Correct)
Decentralized Train Scheduling David C. Parkes and Lyle H. Ungar Computer and Information Science
Train Scheduling David C. Parkes and Lyle H. Ungar Computer and Information Science Department
Philadelphia, PA 1910 dparkes@unagi.cis.upenn.edu, ungar@cis.upenn.edu ABSTRACT We present a

www.eecs.harvard.edu/econcs/bib/./cache/parkes01a.pdf

Unknown -   (Correct)
University of Pennsylvania, Philadelphia, PA Lyle H. Ungar ungar@cis.upenn.edu Computer and
of Pennsylvania, Philadelphia, PA Lyle H. Ungar ungar@cis.upenn.edu Computer and Information
of Pennsylvania, Philadelphia, PA Lyle H. Ungar ungar@cis.upenn.edu Computer and Information Science,

www.cs.colorado.edu/~grudic/publications/GrudicUngarICML2K.ps

Learning and Adaption in Multiagent Systems - David Parkes And   (Correct)
Adaption in Multiagent Systems David C. Parkes and Lyle H. Ungar Computer and Information Science
in Multiagent Systems David C. Parkes and Lyle H. Ungar Computer and Information Science Department
Philadelphia, PA 19104 dparkes@unagi.cis.upenn.edu ungar@cis.upenn.edu Abstract The goal of a

www.eecs.harvard.edu/econcs/pubs/learning.pdf

Rates of Convergence of Performance Gradient Estimates Using.. - Grudic, Ungar   (Correct)
of Colorado, Boulder grudic@cs.colorado.edu Lyle H. Ungar University of Pennsylvania
Bias in Reinforcement Learning Gregory Z. Grudic, Lyle H. Ungar
Colorado, Boulder grudic@cs.colorado.edu Lyle H. Ungar University of Pennsylvania ungar@cis.upenn.edu

www.cs.colorado.edu/~grudic/publications/GrudicUngarNIPS01.pdf

A-Optimality for Active Learning of Logistic Regression.. - Schein, Ungar (2004)   (Correct)
Regression Classifiers #Andrew I. Schein and Lyle H. Ungar Department of Computer and Information
[36] Andrew I. Schein and Lyle H. Ungar. A-Optimality for Active Learning of
Classifiers #Andrew I. Schein and Lyle H. Ungar Department of Computer and Information Science

www.cis.upenn.edu/~ais/./publications/aactive.ps.gz

Bayesian Example Selection using BaBiES - Andrew Schein Ted (2004)   (Correct)
using BaBiES Andrew I. Schein, S. Ted Sandler and Lyle H. Ungar Department of Computer and Information
[35] Andrew I. Schein, S. Ted Sandler, and Lyle H. Ungar. Bayesian Example Selection using BaBiES.
BaBiES Andrew I. Schein, S. Ted Sandler and Lyle H. Ungar Department of Computer and Information Science

www.cis.upenn.edu/~ais/./publications/babies.ps.gz

In Proc. of 22nd Annual Conference of the IEEE Computer and .. - Static And Dynamic   (Correct)
@research.nj.nec.com C. Lee Giles 1,2,3 Lyle H. Ungar 4 4 Department of Computer and
C. Lee Giles 1,2,3 Lyle H. Ungar 4 4 Department of Computer and Information
Building, 200 S. 33rd St Philadelphia, PA 19104 USA ungar@cis.upenn.edu Abstract-We analyze the

www.neci.nec.com/~lawrence/papers/network-infocom03/network-infocom03.ps.gz

Andrew McCallum - Home Address Cottage   (Correct)
with Thorsten Joachims, Mehran Sahami and Lyle Ungar. 1999. Co-Organizer of NIPS*98 Workshop
Andrew Schein, University of Pennsylvania. Advisor, Lyle Ungar. Kamal Nigam, Carnegie Mellon University.
Schein, University of Pennsylvania. Advisor, Lyle Ungar. Kamal Nigam, Carnegie Mellon University.

www.cs.umass.edu/~mccallum/mccallum-vita.pdf

Generative Models for Cold-Start Recommendations - Andrew Schein Alexandrin (2001)   (Correct)
Andrew I. Schein, Alexandrin Popescul, and Lyle H. Ungar University of Pennsylvania Dept. of
multiple observations that are identical (e.g.Lyle saw Memento twice)With each observation we
Andrew I. Schein, Alexandrin Popescul, and Lyle H. Ungar University of Pennsylvania Dept. of Computer

web.engr.oregonstate.edu/~herlock/rsw2001/final/full_length_papers/3_schein+.ps

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