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ORCIDMario Boley
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- affiliation: University of Bonn, Germany
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2020 – today
- 2024
[c41]Fan Yang, Pierre Le Bodic, Michael Kamp, Mario Boley:
Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles. AISTATS 2024: 1117-1125- [c40]Yun Zhao, David B. Grayden, Mario Boley, Yueyang Liu, Philippa J. Karoly, Mark J. Cook, Levin Kuhlmann:
Inference-based time-resolved chaos analysis of brain models: application to focal epilepsy. FUSION 2024: 1-8 - [i14]Fan Yang, Pierre Le Bodic, Michael Kamp, Mario Boley:
Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles. CoRR abs/2402.15691 (2024) - 2023
- [j9]Yun Zhao
, Felix Luong, Simon Teshuva, Andria Pelentritou, William Woods, David T. J. Liley, Daniel F. Schmidt, Mario Boley, Levin Kuhlmann:
Improved Neurophysiological Process Imaging Through Optimization of Kalman Filter Initial Conditions. Int. J. Neural Syst. 33(5): 2350024:1-2350024:20 (2023) - [j8]Yiwen Lu, Dilek Yalcin, Paul J. Pigram, Lewis D. Blackman, Mario Boley:
Interpretable Machine Learning Models for Phase Prediction in Polymerization-Induced Self-Assembly. J. Chem. Inf. Model. 63(11): 3288-3306 (2023) - [c39]Yun Zhao, Mario Boley, Andria Pelentritou, William Woods, David T. J. Liley, Levin Kuhlmann:
Inference-based time-resolved stability analysis of nonlinear whole-cortex modeling: application to Xenon anaesthesia. EMBC 2023: 1-4 - [c38]Shu Yu Tew, Mario Boley, Daniel F. Schmidt:
Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization. NeurIPS 2023 - [i13]Shu Yu Tew, Mario Boley, Daniel F. Schmidt:
Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization. CoRR abs/2310.18860 (2023) - [i12]Mario Boley, Felix Luong, Simon Teshuva, Daniel F. Schmidt, Lucas Foppa, Matthias Scheffler:
From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery. CoRR abs/2311.15549 (2023) - 2022
- [j7]Yun Zhao, Mario Boley, Andria Pelentritou, Philippa J. Karoly, Dean R. Freestone, Yueyang Liu, Suresh D. Muthukumaraswamy, William Woods, David T. J. Liley, Levin Kuhlmann:
Space-time resolved inference-based neurophysiological process imaging: Application to resting-state alpha rhythm. NeuroImage 263: 119592 (2022) - [c37]Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi:
Enhanced Extra Trees Classifier for Epileptic Seizure Prediction. ICSPIS 2022: 175-179 - 2021
- [c36]Henning Petzka, Michael Kamp, Linara Adilova, Cristian Sminchisescu, Mario Boley:
Relative Flatness and Generalization. NeurIPS 2021: 18420-18432 - [c35]Kailash Budhathoki, Mario Boley, Jilles Vreeken:
Discovering Reliable Causal Rules. SDM 2021: 1-9 - [c34]Mario Boley, Simon Teshuva, Pierre Le Bodic, Geoffrey I. Webb:
Better Short than Greedy: Interpretable Models through Optimal Rule Boosting. SDM 2021: 351-359 - [i11]Mario Boley, Simon Teshuva, Pierre Le Bodic, Geoffrey I. Webb:
Better Short than Greedy: Interpretable Models through Optimal Rule Boosting. CoRR abs/2101.08380 (2021) - 2020
- [j6]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering dependencies with reliable mutual information. Knowl. Inf. Syst. 62(11): 4223-4253 (2020) - [c33]Panagiotis Mandros, David Kaltenpoth, Mario Boley, Jilles Vreeken:
Discovering Functional Dependencies from Mixed-Type Data. KDD 2020: 1404-1414 - [i10]Kailash Budhathoki, Mario Boley, Jilles Vreeken:
Discovering Reliable Causal Rules. CoRR abs/2009.02728 (2020)
2010 – 2019
- 2019
- [c32]Janis Kalofolias, Mario Boley, Jilles Vreeken:
Discovering Robustly Connected Subgraphs with Simple Descriptions. ICDM 2019: 1150-1155 - [c31]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Correlations in Categorical Data. ICDM 2019: 1252-1257 - [c30]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms. IJCAI 2019: 6206-6210 - [i9]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Correlations in Categorical Data. CoRR abs/1908.11682 (2019) - [i8]Michael Kamp, Mario Boley, Michael Mock, Daniel Keren, Assaf Schuster, Izchak Sharfman:
Adaptive Communication Bounds for Distributed Online Learning. CoRR abs/1911.12896 (2019) - [i7]Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock:
Communication-Efficient Distributed Online Learning with Kernels. CoRR abs/1911.12899 (2019) - 2018
- [c29]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms. ICDM 2018: 317-326 - [i6]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms. CoRR abs/1809.05467 (2018) - [i5]Michael Kamp, Mario Boley, Olana Missura, Thomas Gärtner:
Effective Parallelisation for Machine Learning. CoRR abs/1810.03530 (2018) - 2017
- [j5]Mario Boley, Bryan R. Goldsmith, Luca M. Ghiringhelli, Jilles Vreeken:
Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery. Data Min. Knowl. Discov. 31(5): 1391-1418 (2017) - [c28]Janis Kalofolias, Mario Boley, Jilles Vreeken:
Efficiently Discovering Locally Exceptional Yet Globally Representative Subgroups. ICDM 2017: 197-206 - [c27]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Approximate Functional Dependencies. KDD 2017: 355-363 - [c26]Michael Kamp, Mario Boley, Olana Missura, Thomas Gärtner:
Effective Parallelisation for Machine Learning. NIPS 2017: 6477-6488 - [i4]Mario Boley, Bryan R. Goldsmith, Luca M. Ghiringhelli, Jilles Vreeken:
Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery. CoRR abs/1701.07696 (2017) - [i3]Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Approximate Functional Dependencies. CoRR abs/1705.09391 (2017) - [i2]Janis Kalofolias, Mario Boley, Jilles Vreeken:
Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups. CoRR abs/1709.07941 (2017) - 2016
- [c25]Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock:
Communication-Efficient Distributed Online Learning with Kernels. ECML/PKDD (2) 2016: 805-819 - 2015
- [c24]Daniel Trabold, Mario Boley, Michael Mock, Tamás Horváth:
In-Stream Frequent Itemset Mining With Output Proportional Memory Footprint. LWA 2015: 93-104 - 2014
- [j4]Eirini Spyropoulou, Tijl De Bie, Mario Boley:
Interesting pattern mining in multi-relational data. Data Min. Knowl. Discov. 28(3): 808-849 (2014) - [c23]Sandy Moens, Mario Boley, Bart Goethals:
Providing Concise Database Covers Instantly by Recursive Tile Sampling. Discovery Science 2014: 216-227 - [c22]Sandy Moens, Mario Boley:
Instant Exceptional Model Mining Using Weighted Controlled Pattern Sampling. IDA 2014: 203-214 - [c21]Michael Kamp, Mario Boley, Daniel Keren, Assaf Schuster, Izchak Sharfman:
Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization. ECML/PKDD (1) 2014: 623-639 - [c20]Michael Kamp, Mario Boley, Thomas Gärtner:
Beating Human Analysts in Nowcasting Corporate Earnings by using Publicly Available Stock Price and Correlation Features. SDM 2014: 641-649 - 2013
- [c19]Eirini Spyropoulou, Tijl De Bie, Mario Boley:
Mining Interesting Patterns in Multi-relational Data with N-ary Relationships. Discovery Science 2013: 217-232 - [c18]Michael Kamp, Mario Boley, Thomas Gärtner:
Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features. ICDM Workshops 2013: 384-390 - [c17]Mario Boley, Michael Mampaey, Bo Kang, Pavel Tokmakov, Stefan Wrobel:
One click mining: interactive local pattern discovery through implicit preference and performance learning. IDEA@KDD 2013: 27-35 - [c16]Michael Kamp, Christine Kopp, Michael Mock, Mario Boley, Michael May:
Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings. ECML/PKDD (3) 2013: 370-386 - [c15]Mario Boley, Michael Kamp, Daniel Keren, Assaf Schuster, Izchak Sharfman:
Communication-Efficient Distributed Online Prediction using Dynamic Model Synchronizations. BD3@VLDB 2013: 13-18 - 2012
- [c14]Mario Boley, Sandy Moens, Thomas Gärtner:
Linear space direct pattern sampling using coupling from the past. KDD 2012: 69-77 - [i1]Shankar Vembu, Thomas Gärtner, Mario Boley:
Probabilistic Structured Predictors. CoRR abs/1205.2610 (2012) - 2011
- [c13]Mario Boley, Claudio Lucchese, Daniel Paurat, Thomas Gärtner:
Direct local pattern sampling by efficient two-step random procedures. KDD 2011: 582-590 - [c12]Mario Boley, Claudio Lucchese, Daniel Paurat, Thomas Gärtner:
Direct Pattern Sampling with Respect to Pattern Frequency. LWA 2011: 114-121 - 2010
- [b1]Mario Boley:
The Efficient Discovery of Interesting Closed Pattern Collections. University of Bonn, 2010 - [j3]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Listing closed sets of strongly accessible set systems with applications to data mining. Theor. Comput. Sci. 411(3): 691-700 (2010) - [c11]Henrik Grosskreutz, Mario Boley, Maike Krause-Traudes:
Subgroup Discovery for Election Analysis: A Case Study in Descriptive Data Mining. Discovery Science 2010: 57-71 - [c10]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Listing closed sets of strongly accessible set systems with applications to data. LWA 2010: 33 - [c9]Mario Boley, Thomas Gärtner, Henrik Grosskreutz:
Formal Concept Sampling for Counting and Threshold-Free Local Pattern Mining. SDM 2010: 177-188
2000 – 2009
- 2009
- [j2]Mario Boley, Henrik Grosskreutz:
Approximating the number of frequent sets in dense data. Knowl. Inf. Syst. 21(1): 65-89 (2009) - [j1]Mario Boley, Tamás Horváth, Stefan Wrobel:
Efficient discovery of interesting patterns based on strong closedness. Stat. Anal. Data Min. 2(5-6): 346-360 (2009) - [c8]Mario Boley, Thomas Gärtner:
On the Complexity of Constraint-Based Theory Extraction. Discovery Science 2009: 92-106 - [c7]Mario Boley, Henrik Grosskreutz:
Non-redundant Subgroup Discovery Using a Closure System. ECML/PKDD (1) 2009: 179-194 - [c6]Mario Boley, Tamás Horváth, Stefan Wrobel:
Efficient Discovery of Interesting Patterns Based on Strong Closedness. SDM 2009: 1002-1013 - [c5]Shankar Vembu, Thomas Gärtner, Mario Boley:
Probabilistic Structured Predictors. UAI 2009: 557-564 - 2008
- [c4]Mario Boley, Henrik Grosskreutz:
A Randomized Approach for Approximating the Number of Frequent Sets. ICDM 2008: 43-52 - 2007
- [c3]Mario Boley:
On Approximating Minimum Infrequent and Maximum Frequent Sets. Discovery Science 2007: 68-77 - [c2]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Efficient Closed Pattern Mining in Strongly Accessible Set Systems. MLG 2007 - [c1]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Efficient Closed Pattern Mining in Strongly Accessible Set Systems (Extended Abstract). PKDD 2007: 382-389
Coauthor Index
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last updated on 2024-10-25 20:13 CEST by the dblp team
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