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 Michal Rosen-Zvi

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Average citations per article42.93
Citation Count644
Publication count15
Publication years2004-2017
Available for download6
Average downloads per article1,447.83
Downloads (cumulative)8,687
Downloads (12 Months)717
Downloads (6 Weeks)84
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15 results found Export Results: bibtexendnoteacmrefcsv

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1
March 2017 Annals of Mathematics and Artificial Intelligence: Volume 79 Issue 1-3, March 2017
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 0

In the standard agnostic multiclass model, pairs are sampled independently from some underlying distribution. This distribution induces a conditional probability over the labels given an instance, and our goal in this paper is to learn this conditional distribution. Since even unconditional densities are quite challenging to learn, ...
Keywords: 65C50, Boosting, Conditional density

2 published by ACM
August 2015 KDD '15: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 8,   Downloads (12 Months): 58,   Downloads (Overall): 320

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Reading is a complex cognitive process, errors in which may assume diverse forms. In this study, introducing a novel approach, we use two families of probabilistic graphical models to analyze patterns of reading errors made by dyslexic people: an LDA-based model and two Naëve Bayes models which differ by their ...
Keywords: latent dirichlet allocation, naëve bayes, probabilistic graphical models, diagnosis, dyslexia

3
September 2011 IBM Journal of Research and Development: Volume 55 Issue 5, September/October 2011
Publisher: IBM Corp.
Bibliometrics:
Citation Count: 1

Modern computer systems generate an enormous number of logs. IBM Mining Effectively Large Output Data Yield (MELODY) is a unique and innovative solution for handling these logs and filtering out the anomalies and failures. MELODY can detect system errors early on and avoid subsequent crashes by identifying the root causes ...

4
September 2011 IBM Journal of Research and Development: Volume 55 Issue 5, September/October 2011
Publisher: IBM Corp.
Bibliometrics:
Citation Count: 1

Rising costs, decreasing quality of care, diminishing productivity, and increasing complexity have all contributed to the present state of the healthcare industry. The interactions between payers (e.g., insurance companies and health plans) and providers (e.g., hospitals and laboratories) are growing and are becoming more complicated. The constant upsurge in and ...

5 published by ACM
August 2011 KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 6,   Downloads (12 Months): 69,   Downloads (Overall): 641

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Chronic diseases constitute the leading cause of mortality in the western world, have a major impact on the patients' quality of life, and comprise the bulk of healthcare costs. Nowadays, healthcare data management systems integrate large amounts of medical information on patients, including diagnoses, medical procedures, lab test results, and ...
Keywords: survival analysis, machine learning

6 published by ACM
January 2010 ACM Transactions on Information Systems (TOIS): Volume 28 Issue 1, January 2010
Publisher: ACM
Bibliometrics:
Citation Count: 48
Downloads (6 Weeks): 17,   Downloads (12 Months): 130,   Downloads (Overall): 1,818

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We propose an unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a two-stage stochastic process. An author is represented by a probability distribution over topics, and each topic is represented as a probability distribution over ...
Keywords: Gibbs sampling, author models, unsupervised learning, perplexity, Topic models

7
May 2009 Similarity-Based Clustering: Recent Developments and Biomedical Applications
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

This chapter provides a review of the challenges machine-learning specialists face when trying to assist virologists by generating an automatic prediction of an outcome of HIV therapy. Optimizing HIV therapies is crucial since the virus rapidly develops mutations to evade drug pressures. Modern anti-HIV regimens comprise multiple drugs in order ...

8
July 2008 UAI'08: Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence
Publisher: AUAI Press
Bibliometrics:
Citation Count: 0

Latent topic models have been successfully applied as an unsupervised topic discovery technique in large document collections. With the proliferation of hypertext document collection such as the Internet, there has also been great interest in extending these approaches to hypertext [6, 9]. These approaches typically model links in an analogous ...

9
July 2008 Bioinformatics: Volume 24 Issue 13, July 2008
Publisher: Oxford University Press
Bibliometrics:
Citation Count: 9

Motivation: Optimizing HIV therapies is crucial since the virus rapidly develops mutations to evade drug pressure. Recent studies have shown that genotypic information might not be sufficient for the design of therapies and that other clinical and demographical factors may play a role in therapy failure. This study is designed ...

10
October 2005 Neural Networks - Special issue on neural networks and kernel methods for structured domains: Volume 18 Issue 8, October 2005
Publisher: Elsevier Science Ltd.
Bibliometrics:
Citation Count: 7

Machine learning methods that can handle variable-size structured data such as sequences and graphs include Bayesian networks (BNs) and Recursive Neural Networks (RNNs). In both classes of models, the data is modeled using a set of observed and hidden variables associated with the nodes of a directed acyclic graph. In ...
Keywords: Belief propagation, Constraint networks, Graphical models, Recurrent neural networks, Recursive neural networks, Bayesian networks

11
July 2005 UAI'05: Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence
Publisher: AUAI Press
Bibliometrics:
Citation Count: 1

We propose a hierarchy for approximate inference based on the Dobrushin, Langford, Ruelle (DLR) equations. This hierarchy includes existing algorithms, such as belief propagation, and also motivates novel algorithms such as factorized neighbors (FN) algorithms and variants of mean field (MF) algorithms. In particular, we show that extrema of the ...

12
December 2004 NIPS'04: Proceedings of the 17th International Conference on Neural Information Processing Systems
Publisher: MIT Press
Bibliometrics:
Citation Count: 31

Directed graphical models with one layer of observed random variables and one or more layers of hidden random variables have been the dominant modelling paradigm in many research fields. Although this approach has met with considerable success, the causal semantics of these models can make it difficult to infer the ...

13 published by ACM
August 2004 KDD '04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Publisher: ACM
Bibliometrics:
Citation Count: 182
Downloads (6 Weeks): 12,   Downloads (12 Months): 121,   Downloads (Overall): 2,354

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We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic process. Each author is represented by a probability distribution over topics, and each topic is represented as a probability distribution over words for that ...
Keywords: Gibbs sampling, unsupervised learning, text modeling

14
July 2004 UAI '04: Proceedings of the 20th conference on Uncertainty in artificial intelligence
Publisher: AUAI Press
Bibliometrics:
Citation Count: 355
Downloads (6 Weeks): 42,   Downloads (12 Months): 337,   Downloads (Overall): 3,371

Full text available: PDFPDF
We introduce the author-topic model, a generative model for documents that extends Latent Dirichlet Allocation (LDA; Blei, Ng, & Jordan, 2003) to include authorship information. Each author is associated with a multinomial distribution over topics and each topic is associated with a multinomial distribution over words. A document with multiple ...

15 published by ACM
July 2004 ICML '04: Proceedings of the twenty-first international conference on Machine learning
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 0,   Downloads (12 Months): 3,   Downloads (Overall): 182

Full text available: PDFPDF
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distribution. Since the number of configurations in this space grows exponentially with the number of random variables we often need to represent the ...



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