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137 results on '"Tsivtsivadze, Evgeni"'

1. Semi-supervised Ranking Pursuit

Author

Tsivtsivadze, Evgeni and Heskes, Tom

Subjects
Statistics - Machine Learning, Computer Science - Information Retrieval, Computer Science - Learning
Abstract

We propose a novel sparse preference learning/ranking algorithm. Our algorithm approximates the true utility function by a weighted sum of basis functions using the squared loss on pairs of data points, and is a generalization of the kernel matching pursuit method. It can operate both in a supervised and a semi-supervised setting and allows efficient search for multiple, near-optimal solutions. Furthermore, we describe the extension of the algorithm suitable for combined ranking and regression tasks. In our experiments we demonstrate that the proposed algorithm outperforms several state-of-the-art learning methods when taking into account unlabeled data and performs comparably in a supervised learning scenario, while providing sparser solutions.

Published
2013

2. Premise Selection for Mathematics by Corpus Analysis and Kernel Methods

Author

Alama, Jesse, Heskes, Tom, Kühlwein, Daniel, Tsivtsivadze, Evgeni, and Urban, Josef

Subjects
Computer Science - Learning, Computer Science - Artificial Intelligence, 68T05, I.2.6, I.2.3
Abstract

Smart premise selection is essential when using automated reasoning as a tool for large-theory formal proof development. A good method for premise selection in complex mathematical libraries is the application of machine learning to large corpora of proofs. This work develops learning-based premise selection in two ways. First, a newly available minimal dependency analysis of existing high-level formal mathematical proofs is used to build a large knowledge base of proof dependencies, providing precise data for ATP-based re-verification and for training premise selection algorithms. Second, a new machine learning algorithm for premise selection based on kernel methods is proposed and implemented. To evaluate the impact of both techniques, a benchmark consisting of 2078 large-theory mathematical problems is constructed,extending the older MPTP Challenge benchmark. The combined effect of the techniques results in a 50% improvement on the benchmark over the Vampire/SInE state-of-the-art system for automated reasoning in large theories., Comment: 26 pages

Published
2011
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6. Multi-view Multi-class Classification for Identification of Pathogenic Bacterial Strains

Author

Tsivtsivadze, Evgeni, Heskes, Tom, Paauw, Armand, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zhou, Zhi-Hua, editor, and Roli, Fabio, editor

Published
2013
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7. Online Co-regularized Algorithms

Author

de Ruijter, Tom, Tsivtsivadze, Evgeni, Heskes, Tom, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Ganascia, Jean-Gabriel, editor, Lenca, Philippe, editor, and Petit, Jean-Marc, editor

Published
2012
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8. Overview and Evaluation of Premise Selection Techniques for Large Theory Mathematics

Author

Kühlwein, Daniel, van Laarhoven, Twan, Tsivtsivadze, Evgeni, Urban, Josef, Heskes, Tom, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Gramlich, Bernhard, editor, Miller, Dale, editor, and Sattler, Uli, editor

Published
2012
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10. Kernels for Text Analysis

Author

Tsivtsivadze, Evgeni, Pahikkala, Tapio, Boberg, Jorma, Salakoski, Tapio, Kacprzyk, Janusz, editor, Liu, Ying, editor, Sun, Aixin, editor, Loh, Han Tong, editor, Lu, Wen Feng, editor, and Lim, Ee-Peng, editor

Published
2008
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12. Locality-Convolution Kernel and Its Application to Dependency Parse Ranking

Author

Tsivtsivadze, Evgeni, Pahikkala, Tapio, Boberg, Jorma, Salakoski, Tapio, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Ali, Moonis, editor, and Dapoigny, Richard, editor

Published
2006
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13. Regularized Least-Squares for Parse Ranking

Author

Tsivtsivadze, Evgeni, Pahikkala, Tapio, Pyysalo, Sampo, Boberg, Jorma, Mylläri, Aleksandr, Salakoski, Tapio, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Famili, A. Fazel, editor, Kok, Joost N., editor, Peña, José M., editor, Siebes, Arno, editor, and Feelders, Ad, editor

Published
2005
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14. Learning2Reason

Author

Kühlwein, Daniel, Urban, Josef, Tsivtsivadze, Evgeni, Geuvers, Herman, Heskes, Tom, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Davenport, James H., editor, Farmer, William M., editor, Urban, Josef, editor, and Rabe, Florian, editor

Published
2011
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24. Correlates of the molecular vaginal microbiota composition of African women

Author

Gautam, Raju, Borgdorff, Hanneke, Jespers, Vicky, Francis, Suzanna C, Verhelst, Rita, Mwaura, Mary, Delany-Moretlwe, Sinead, Ndayisaba, Gilles, Kyongo, Jordan K, Hardy, Liselotte, Menten, Joris, Crucitti, Tania, Tsivtsivadze, Evgeni, Schuren, Frank, van de Wijgert, Janneke HHM, and Vaginal Biomarkers Study Group

Abstract

BACKGROUND: Sociodemographic, behavioral and clinical correlates of the vaginal microbiome (VMB) as characterized by molecular methods have not been adequately studied. VMB dominated by bacteria other than lactobacilli may cause inflammation, which may facilitate HIV acquisition and other adverse reproductive health outcomes. METHODS: We characterized the VMB of women in Kenya, Rwanda, South Africa and Tanzania (KRST) using a 16S rDNA phylogenetic microarray. Cytokines were quantified in cervicovaginal lavages. Potential sociodemographic, behavioral, and clinical correlates were also evaluated. RESULTS: Three hundred thirteen samples from 230 women were available for analysis. Five VMB clusters were identified: one cluster each dominated by Lactobacillus crispatus (KRST-I) and L. iners (KRST-II), and three clusters not dominated by a single species but containing multiple (facultative) anaerobes (KRST-III/IV/V). Women in clusters KRST-I and II had lower mean concentrations of interleukin (IL)-1α (p < 0.001) and Granulocyte Colony Stimulating Factor (G-CSF) (p = 0.01), but higher concentrations of interferon-γ-induced protein (IP-10) (p < 0.01) than women in clusters KRST-III/IV/V. A lower proportion of women in cluster KRST-I tested positive for bacterial sexually transmitted infections (STIs; ptrend = 0.07) and urinary tract infection (UTI; p = 0.06), and a higher proportion of women in clusters KRST-I and II had vaginal candidiasis (ptrend = 0.09), but these associations did not reach statistical significance. Women who reported unusual vaginal discharge were more likely to belong to clusters KRST-III/IV/V (p = 0.05). CONCLUSION: Vaginal dysbiosis in African women was significantly associated with vaginal inflammation; the associations with increased prevalence of STIs and UTI, and decreased prevalence of vaginal candidiasis, should be confirmed in larger studies.

Published
2015

31. OmpU as a biomarker for rapid discrimination between toxigenic and epidemic Vibrio cholerae O1/O139 and non-epidemic Vibrio cholerae in a modified MALDI-TOF MS assay

Author

Paauw, Armand, primary, Trip, Hein, additional, Niemcewicz, Marcin, additional, Sellek, Ricela, additional, Heng, Jonathan ME, additional, Mars-Groenendijk, Roos H, additional, de Jong, Ad L, additional, Majchrzykiewicz-Koehorst, Joanna A, additional, Olsen, Jaran S, additional, and Tsivtsivadze, Evgeni, additional

Published
2014
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40. Locality Kernels for Protein Classification.

Author

Istrail, Sorin, Pevzner, Pavel, Waterman, Michael S., Giancarlo, Raffaele, Hannenhalli, Sridhar, Tsivtsivadze, Evgeni, Boberg, Jorma, and Salakoski, Tapio

Abstract

We propose kernels that take advantage of local correlations in sequential data and present their application to the protein classification problem. Our locality kernels measure protein sequence similarities within a small window constructed around matching amino acids. The kernels incorporate positional information of the amino acids inside the window and allow a range of position dependent similarity evaluations. We use these kernels with regularized least-squares algorithm (RLS) for protein classification on the SCOP database. Our experiments demonstrate that the locality kernels perform significantly better than the spectrum and the mismatch kernels. When used together with RLS, performance of the locality kernels is comparable with some state-of-the-art methods of protein classification and remote homology detection. [ABSTRACT FROM AUTHOR]

Published
2007
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42. Regularized Least-Squares for Parse Ranking.

Author

Famili, A. Fazel, Kok, Joost N., Peña, José M., Siebes, Arno, Feelders, Ad, Tsivtsivadze, Evgeni, Pahikkala, Tapio, Pyysalo, Sampo, Boberg, Jorma, Mylläri, Aleksandr, and Salakoski, Tapio

Abstract

We present an adaptation of the Regularized Least-Squares algorithm for the rank learning problem and an application of the method to reranking of the parses produced by the Link Grammar (LG) dependency parser. We study the use of several grammatically motivated features extracted from parses and evaluate the ranker with individual features and the combination of all features on a set of biomedical sentences annotated for syntactic dependencies. Using a parse goodness function based on the F-score, we demonstrate that our method produces a statistically significant increase in rank correlation from 0.18 to 0.42 compared to the built-in ranking heuristics of the LG parser. Further, we analyze the performance of our ranker with respect to the number of sentences and parses per sentence used for training and illustrate that the method is applicable to sparse datasets, showing improved performance with as few as 100 training sentences. [ABSTRACT FROM AUTHOR]

Published
2005
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43. Premise Selection for Mathematics by Corpus Analysis and Kernel Methods.

Author

Alama, Jesse, Heskes, Tom, Kühlwein, Daniel, Tsivtsivadze, Evgeni, and Urban, Josef

Subjects
KERNEL (Mathematics), MATHEMATICAL proofs, MACHINE learning, CONFIRMATION (Logic), PROBLEM solving, AUTOMATIC theorem proving
Abstract

Smart premise selection is essential when using automated reasoning as a tool for large-theory formal proof development. This work develops learning-based premise selection in two ways. First, a fine-grained dependency analysis of existing high-level formal mathematical proofs is used to build a large knowledge base of proof dependencies, providing precise data for ATP-based re-verification and for training premise selection algorithms. Second, a new machine learning algorithm for premise selection based on kernel methods is proposed and implemented. To evaluate the impact of both techniques, a benchmark consisting of 2078 large-theory mathematical problems is constructed, extending the older MPTP Challenge benchmark. The combined effect of the techniques results in a 50 % improvement on the benchmark over the state-of-the-art Vampire/SInE system for automated reasoning in large theories. [ABSTRACT FROM AUTHOR]

Published
2014
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44. Correlates of the molecular vaginal microbiota composition of African women

Author

Gautam, Raju, Borgdorff, Hanneke, Jespers, Vicky, Francis, Suzanna C., Verhelst, Rita, Mwaura, Mary, Delany-Moretlwe, Sinead, Ndayisaba, Gilles, Kyongo, Jordan K., Hardy, Liselotte, Menten, Joris, Crucitti, Tania, Tsivtsivadze, Evgeni, Schuren, Frank, van de Wijgert, Janneke H. H. M., Global Health, Infectious diseases, and Other departments

Subjects
IDENTIFICATION, FLORA, TRANSMISSION, Candidiasis, DIVERSITY, HIV, Bacterial vaginosis, Urinary tract infections, Vaginal microbiome, Lactobacillus, MICROBICIDES, Infectious Diseases, ACCEPTABILITY, SAFETY, Africa, INFECTION, Medicine and Health Sciences, Sexually transmitted infections, Women, Vaginal microbiota
Abstract

Background: Sociodemographic, behavioral and clinical correlates of the vaginal microbiome (VMB) as characterized by molecular methods have not been adequately studied. VMB dominated by bacteria other than lactobacilli may cause inflammation, which may facilitate HIV acquisition and other adverse reproductive health outcomes. Methods: We characterized the VMB of women in Kenya, Rwanda, South Africa and Tanzania (KRST) using a 16S rDNA phylogenetic microarray. Cytokines were quantified in cervicovaginal lavages. Potential sociodemographic, behavioral, and clinical correlates were also evaluated. Results: Three hundred thirteen samples from 230 women were available for analysis. Five VMB clusters were identified: one cluster each dominated by Lactobacillus crispatus (KRST-I) and L. iners (KRST-II), and three clusters not dominated by a single species but containing multiple (facultative) anaerobes (KRST-III/IV/V). Women in clusters KRST-I and II had lower mean concentrations of interleukin (IL)-1 alpha (p < 0.001) and Granulocyte Colony Stimulating Factor (G-CSF) (p = 0.01), but higher concentrations of interferon-gamma-induced protein (IP-10) (p < 0.01) than women in clusters KRST-III/IV/V. A lower proportion of women in cluster KRST-I tested positive for bacterial sexually transmitted infections (STIs; p(trend) = 0.07) and urinary tract infection (UTI; p = 0.06), and a higher proportion of women in clusters KRST-I and II had vaginal candidiasis (p(trend) = 0.09), but these associations did not reach statistical significance. Women who reported unusual vaginal discharge were more likely to belong to clusters KRST-III/IV/V (p = 0.05). Conclusion: Vaginal dysbiosis in African women was significantly associated with vaginal inflammation; the associations with increased prevalence of STIs and UTI, and decreased prevalence of vaginal candidiasis, should be confirmed in larger studies.

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45. Flow-Based Bayesian Estimation of Nonlinear Differential Equations for Modeling Biological Networks

Author

Brunel, Nicolas J. -B., d’Alché-Buc, Florence, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Dijkstra, Tjeerd M. H., editor, Tsivtsivadze, Evgeni, editor, Marchiori, Elena, editor, and Heskes, Tom, editor

Published
2010
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46. Revisiting the Voronoi Description of Protein-Protein Interfaces: Algorithms

Author

Cazals, Frederic, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Dijkstra, Tjeerd M. H., editor, Tsivtsivadze, Evgeni, editor, Marchiori, Elena, editor, and Heskes, Tom, editor

Published
2010
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47. SFFS-MR: A Floating Search Strategy for GRNs Inference

Author

Lopes, Fabrício M., Martins, David C., Jr., Barrera, Junior, Cesar, Roberto M., Jr., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Dijkstra, Tjeerd M. H., editor, Tsivtsivadze, Evgeni, editor, Marchiori, Elena, editor, and Heskes, Tom, editor

Published
2010
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48. MC4: A Tempering Algorithm for Large-Sample Network Inference

Author

Barker, Daniel James, Hill, Steven M., Mukherjee, Sach, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Dijkstra, Tjeerd M. H., editor, Tsivtsivadze, Evgeni, editor, Marchiori, Elena, editor, and Heskes, Tom, editor

Published
2010
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49. Employing Publically Available Biological Expert Knowledge from Protein-Protein Interaction Information

Author

Pattin, Kristine A., Gui, Jiang, Moore, Jason H., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Dijkstra, Tjeerd M. H., editor, Tsivtsivadze, Evgeni, editor, Marchiori, Elena, editor, and Heskes, Tom, editor

Published
2010
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50. Biological Protein-Protein Interaction Prediction Using Binding Free Energies and Linear Dimensionality Reduction

Author

Rueda, L., Garate, Carolina, Banerjee, Sridip, Mominul Aziz, Md., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Dijkstra, Tjeerd M. H., editor, Tsivtsivadze, Evgeni, editor, Marchiori, Elena, editor, and Heskes, Tom, editor

Published
2010
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