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ORCIDSzymon Jaroszewicz
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2020 – today
- 2024
[j21]Barbara Zogala-Siudem, Szymon Jaroszewicz
:
Variable screening for Lasso based on multidimensional indexing. Data Min. Knowl. Discov. 38(1): 49-78 (2024)- [j20]Nevo Itzhak, Szymon Jaroszewicz, Robert Moskovitch:
Event prediction by estimating continuously the completion of a single temporal pattern's instances. J. Biomed. Informatics 156: 104665 (2024) - [c28]Nevo Itzhak, Szymon Jaroszewicz, Robert Moskovitch:
Early Multiple Temporal Patterns Based Event Prediction in Heterogeneous Multivariate Temporal Data. SDM 2024: 199-207 - 2023
- [j19]Szymon Jaroszewicz, Krzysztof Rudas:
Shrinkage Estimators for the Intercept in Linear and Uplift Regression. Sci. Ann. Comput. Sci. 33(1): 35-52 (2023) - [j18]Nevo Itzhak, Szymon Jaroszewicz, Robert Moskovitch:
Continuous prediction of a time intervals-related pattern's completion. Knowl. Inf. Syst. 65(11): 4797-4846 (2023) - [c27]Nevo Itzhak, Szymon Jaroszewicz, Robert Moskovitch:
Continuously Predicting the Completion of a Time Intervals Related Pattern. PAKDD (1) 2023: 239-251 - [c26]Krzysztof Rudas, Szymon Jaroszewicz:
Regularization for Uplift Regression. ECML/PKDD (1) 2023: 593-608 - [e2]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e1]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - 2021
- [j17]Barbara Zogala-Siudem, Szymon Jaroszewicz:
Fast stepwise regression based on multidimensional indexes. Inf. Sci. 549: 288-309 (2021) - 2020
- [j16]Robin Marco Gubela, Stefan Lessmann, Szymon Jaroszewicz:
Response transformation and profit decomposition for revenue uplift modeling. Eur. J. Oper. Res. 283(2): 647-661 (2020)
2010 – 2019
- 2019
- [c25]Krzysztof Rudas, Szymon Jaroszewicz:
Shrinkage Estimators for Uplift Regression. ECML/PKDD (1) 2019: 607-623 - [i2]Robin Marco Gubela, Stefan Lessmann, Szymon Jaroszewicz:
Response Transformation and Profit Decomposition for Revenue Uplift Modeling. CoRR abs/1911.08729 (2019) - 2018
- [j15]Krzysztof Rudas, Szymon Jaroszewicz:
Linear regression for uplift modeling. Data Min. Knowl. Discov. 32(5): 1275-1305 (2018) - [j14]Oskar Jarczyk, Szymon Jaroszewicz, Adam Wierzbicki, Kamil Pawlak, Michal Jankowski-Lorek:
Surgical teams on GitHub: Modeling performance of GitHub project development processes. Inf. Softw. Technol. 100: 32-46 (2018) - [i1]Michal Soltys, Szymon Jaroszewicz:
Boosting algorithms for uplift modeling. CoRR abs/1807.07909 (2018) - 2017
- [j13]Lukasz Zaniewicz, Szymon Jaroszewicz:
$$L_p$$ L p -Support vector machines for uplift modeling. Knowl. Inf. Syst. 53(1): 269-296 (2017) - [r1]Szymon Jaroszewicz:
Uplift Modeling. Encyclopedia of Machine Learning and Data Mining 2017: 1304-1309 - 2016
- [j12]Michal Jankowski-Lorek, Szymon Jaroszewicz, Lukasz Ostrowski, Adam Wierzbicki:
Verifying social network models of Wikipedia knowledge community. Inf. Sci. 339: 158-174 (2016) - [p2]Szymon Jaroszewicz, Lukasz Zaniewicz:
Székely Regularization for Uplift Modeling. Challenges in Computational Statistics and Data Mining 2016: 135-154 - 2015
- [j11]Michal Soltys, Szymon Jaroszewicz, Piotr Rzepakowski:
Ensemble methods for uplift modeling. Data Min. Knowl. Discov. 29(6): 1531-1559 (2015) - 2014
- [c24]Barbara Zogala-Siudem, Szymon Jaroszewicz:
Fast Stepwise Regression on Linked Data. LD4KD 2014 - [c23]Oskar Jarczyk, Blazej Gruszka, Szymon Jaroszewicz, Leszek Bukowski, Adam Wierzbicki:
GitHub Projects. Quality Analysis of Open-Source Software. SocInfo 2014: 80-94 - 2013
- [j10]Marcin Korzen, Szymon Jaroszewicz, Przemyslaw Klesk:
Logistic regression with weight grouping priors. Comput. Stat. Data Anal. 64: 281-298 (2013) - [c22]Lukasz Zaniewicz, Szymon Jaroszewicz:
Support Vector Machines for Uplift Modeling. ICDM Workshops 2013: 131-138 - [c21]Leszek Bukowski, Michal Jankowski-Lorek, Szymon Jaroszewicz, Marcin Sydow:
What Makes a Good Team of Wikipedia Editors? A Preliminary Statistical Analysis. SocInfo Workshops 2013: 14-28 - 2012
- [j9]Piotr Rzepakowski, Szymon Jaroszewicz:
Decision trees for uplift modeling with single and multiple treatments. Knowl. Inf. Syst. 32(2): 303-327 (2012) - [j8]Szymon Jaroszewicz, Marcin Korzen:
Arithmetic Operations on Independent Random Variables: A Numerical Approach. SIAM J. Sci. Comput. 34(3) (2012) - 2010
- [j7]Szymon Jaroszewicz:
Using interesting sequences to interactively build Hidden Markov Models. Data Min. Knowl. Discov. 21(1): 186-220 (2010) - [c20]Piotr Rzepakowski, Szymon Jaroszewicz:
Decision Trees for Uplift Modeling. ICDM 2010: 441-450
2000 – 2009
- 2009
- [j6]Szymon Jaroszewicz, Tobias Scheffer, Dan A. Simovici:
Scalable pattern mining with Bayesian networks as background knowledge. Data Min. Knowl. Discov. 18(1): 56-100 (2009) - 2008
- [j5]Szymon Jaroszewicz, Lenka Ivantysynova, Tobias Scheffer:
Schema matching on streams with accuracy guarantees. Intell. Data Anal. 12(3): 253-270 (2008) - [c19]Szymon Jaroszewicz:
Minimum Variance Associations - Discovering Relationships in Numerical Data. PAKDD 2008: 172-183 - 2007
- [c18]Toon Calders, Szymon Jaroszewicz:
Efficient AUC Optimization for Classification. PKDD 2007: 42-53 - [c17]Szymon Jaroszewicz, Marcin Korzen:
Approximating Representations for Large Numerical Databases. SDM 2007: 521-526 - 2006
- [j4]Dan A. Simovici, Szymon Jaroszewicz:
A new metric splitting criterion for decision trees. Int. J. Parallel Emergent Distributed Syst. 21(4): 239-256 (2006) - [c16]Szymon Jaroszewicz, Marcin Korzen:
Comparison of Information Theoretical Measures for Reduct Finding. ICAISC 2006: 518-527 - [c15]Toon Calders, Bart Goethals, Szymon Jaroszewicz:
Mining rank-correlated sets of numerical attributes. KDD 2006: 96-105 - [c14]Szymon Jaroszewicz:
Polynomial association rules with applications to logistic regression. KDD 2006: 586-591 - [c13]Dan A. Simovici, Szymon Jaroszewicz:
Generalized Conditional Entropy and a Metric Splitting Criterion for Decision Trees. PAKDD 2006: 35-44 - 2005
- [c12]Marcin Korzen, Szymon Jaroszewicz:
Finding Reducts Without Building the Discernibility Matrix. ISDA 2005: 450-455 - [c11]Szymon Jaroszewicz, Tobias Scheffer:
Fast discovery of unexpected patterns in data, relative to a Bayesian network. KDD 2005: 118-127 - 2004
- [j3]Szymon Jaroszewicz, Dan A. Simovici, Ivo G. Rosenberg:
Measures on Boolean polynomials and their applications in data mining. Discret. Appl. Math. 144(1-2): 123-139 (2004) - [j2]Szymon Jaroszewicz, Dan A. Simovici, Winston Patrick Kuo, Lucila Ohno-Machado:
The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer. IEEE Trans. Biomed. Eng. 51(7): 1095-1102 (2004) - [c10]Szymon Jaroszewicz, Dan A. Simovici:
Interestingness of frequent itemsets using Bayesian networks as background knowledge. KDD 2004: 178-186 - [c9]Dan A. Simovici, Szymon Jaroszewicz:
A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index. PAKDD 2004: 181-190 - 2003
- [c8]Dan A. Simovici, Szymon Jaroszewicz:
Generalized Conditional Entropy and Decision Trees. EGC 2003: 369-380 - 2002
- [j1]Dan A. Simovici, Szymon Jaroszewicz:
An axiomatization of partition entropy. IEEE Trans. Inf. Theory 48(7): 2138-2142 (2002) - [c7]Ivo G. Rosenberg, Dan A. Simovici, Szymon Jaroszewicz:
On Functions Defined on Free Boolean Algebras. ISMVL 2002: 192-201 - [c6]Szymon Jaroszewicz, Dan A. Simovici:
Pruning Redundant Association Rules Using Maximum Entropy Principle. PAKDD 2002: 135-147 - [c5]Szymon Jaroszewicz, Dan A. Simovici:
Support Approximations Using Bonferroni-Type Inequalities. PKDD 2002: 212-224 - 2001
- [c4]Dan A. Simovici, Szymon Jaroszewicz:
An Axiomatization of Generalized Entropy of Partitions. ISMVL 2001: 259-266 - [c3]Szymon Jaroszewicz, Dan A. Simovici:
A General Measure of Rule Interestingness. PKDD 2001: 253-265 - 2000
- [c2]Szymon Jaroszewicz, Dan A. Simovici:
Data Mining of Weak Functional Decompositions. ISMVL 2000: 77-82 - [p1]Dan A. Simovici, Szymon Jaroszewicz:
On Information-Theoretical Aspects of Relational Databases. Finite Versus Infinite 2000: 301-322
1990 – 1999
- 1999
- [c1]Szymon Jaroszewicz, Dan A. Simovici:
On Axiomatization of Conditional Entropy of Functions Between Finite Sets. ISMVL 1999: 24-28
Coauthor Index
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last updated on 2024-12-08 01:30 CET by the dblp team
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