Categories and Subject Descriptors (2008)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
Probability And Statistics—Contingency table analysis We have developed a method for recommending items that combines content and collaborative data under a single probabilistic framework. We...
CROC: A New Evaluation Criterion for Recommender Systems 1 (2008)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
Evaluation of a recommender system algorithm is a challenging task due to the many possible scenarios in which such systems may be deployed. We have designed a new performance plot called the CROC...
Probability And Statistics—Contingency table analysis (2008)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
We have developed a method for recommending items that combines content and collaborative data under a single probabilistic framework. We benchmark our algorithm against a naïve Bayes classifier on...
Notes on the CROC Curve (2008)
These are some brief notes on the CROC curve for those who wish to employ it in evaluation of recommender systems. We prove some statistical properties of the CROC curve and discus its...
CROC: A New Evaluation Criterion for Recommender Systems (2008)
Andrew Schein Alexandrin, Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
Evaluation of a recommender system algorithm is a challenging task due to the many possible scenarios in which such systems may be deployed. We have designed a new performance plot called the CROC...
Categories and Subject Descriptors (2007)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
]: Probability And Statistics---Contingency table analysis We have developed a method for recommending items that combines content and collaborative data under a single probabilistic framework. We...
These are some brief notes on the CROC curve for those who wish to employ it in evaluation of recommender systems. We prove some statistical properties of the CROC curve and discus its...
]: Probability And Statistics Contin.qency table anal- (2007)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
ysis Ve have developed a method for recommending items that combines content and collaborative data under a single probabifistic framework. We benchmark our algorithm against a naYve Bayes classifier...
1 A (Very Brief) Introduction to the Two-Way Aspect Model (2007)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar
The two-way aspect model is a latent class statistical mixture model for performing soft clustering of co-occurrence data observations. It acts on data such as document/word pairs (words occurring in...
Active Learning for Logistic Regression: An Evaluation (2007)
Schein, Andrew I, Ungar, Lyle H.
Which active learning methods can we expect to yield good performance in learning binary and multi-category logistic regression classifiers? Addressing this question is a natural first step in...
Automatic term list generation for entity tagging (2006)
Sandler, Ted, Schein, Andrew I., Ungar, Lyle H.
Motivation: Many entity taggers and information extraction systems make use of lists of terms of entities such as people, places, genes or chemicals. These lists have traditionally been constructed...
Ted S, Andrew I. Schein, Lyle H. Ungar
Motivation: Many entity taggers and information extraction systems make use of lists of terms of entities such as people, places, genes or chemicals. These lists have traditionally been constructed...
Automatic term list generation for entity tagging (2005)
Ted Sandler, Andrew I. Schein, Lyle H. Ungar
Entity tagging is perhaps the most basic tasks in information extraction. Consequently, if any sophisticated information extraction is to be done, this task must be done well. Currently, state of the...
Automatic term list generation for entity tagging (2005)
Sandler, Ted, Schein, Andrew I., Ungar, Lyle H.
Motivation: Many entity-taggers and information extraction systems make use of lists of terms of entities such as people, places, genes or chemicals. These lists have traditionally been constructed...
A-Optimality for Active Learning of Logistic Regression Classifiers (2004)
Over the last decade there has been growing interest in pool-based active learning techniques, where instead of receiving an i.i.d. sample from a pool of unlabeled data, a learner may take an active...
Bayesian Example Selection using BaBiES (2004)
Schein, Andrew I, Sandler, S. Ted, Ungar, Lyle H
Active learning is widely used to select which examples from a pool should be labeled to give best results when learning predictive models. It is, however, sometimes desirable to choose examples...
A generalized linear model for principal component analysis of binary data (2003)
Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar
We investigate a generalized linear model for dimensionality reduction of binary data. The model is related to principal component analysis (PCA) in the same way that logistic regression is related...
A Generalized Linear Model for Principal Component Analysis of Binary Data (2003)
Andrew I. Schein, Andrew I. Lawrence, Lawrence K. Saul, Lyle H. Ungar
VVe investigate a generalized linear model fbr dimensionality reduction of binary data. The model is related to principal component anal- ysis (PCA) in the same way that logistic regression is...
A generalized linear model for principal component analysis of binary data (2003)
Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar
We investigate a generalized linear model for dimensionality reduction of binary data. The model is related to principal component analysis (PCA) in the same way that logistic regression is related...
Methods and Metrics for Cold-Start Recommendations (2002)
Schein, Andrew I, Popescul, Alexandrin, Ungar, Lyle H, Pennock, David M
We have developed a method for recommending items that combines content and collaborative data under a single probabilistic framework. We benchmark our algorithm against a naive Bayes classifier on...
Methods and metrics for cold-start recommendations (2002)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
We have developed a method for recommending items that combines content and collaborative data under a single probabilistic framework. We benchmark our algorithm against a nave Bayes classifier on...
PennAspect: Two-Way Aspect Model Implementation (2001)
Schein, Andrew I, Popescul, Alexandrin, Ungar, Lyle H
The two-way aspect model is a latent class statistical mixture model for performing soft clustering of co-occurrence data observations. It acts on data such as document/word pairs (words occurring in...
Generative models for cold-start recommendations (2001)
Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
Systems for automatically recommending items (e.g., movies, products, or information) to users are becoming increasingly important in e-commerce applications, digital libraries, and other domains...
Generative Models for Cold-Start Recommendations (2001)
Andrew Schein Alexandrin, Andrew I. Schein, Rin Popescul, Lyle H. Ungar, David M. Pennock
Systems for automatically recommending items (e.g., movies, products, or information) to users are becoming increasingly important in e-commerce applications, digital libraries, and other domains...
Chloroplast transit peptide prediction: a peek inside the black box (2001)
Schein, Andrew I., Kissinger, Jessica C., Ungar, Lyle H.
Previous work in predicting protein localization to the chloroplast organelle in plants led to the development of an artificial neural network-based approach capable of remarkable accuracy in its...
Chloroplast transit peptide prediction: a peek inside the black box
Schein, Andrew I., Kissinger, Jessica C., Ungar, Lyle H.
Previous work in predicting protein localization to the chloroplast organelle in plants led to the development of an artificial neural network-based approach capable of remarkable accuracy in its...
Chloroplast transit peptide prediction: a peek inside the black box
Schein, Andrew I., Kissinger, Jessica C., Ungar, Lyle H.
Previous work in predicting protein localization to the chloroplast organelle in plants led to the development of an artificial neural network-based approach capable of remarkable accuracy in its...