Mario Boley

发表

Effective Parallelisation for Machine Learning

Thomas Gärtner, Michael Kamp, Mario Boley, 2017, NIPS.

Discovering Reliable Correlations in Categorical Data

Jilles Vreeken, Mario Boley, Panagiotis Mandros, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Instant Exceptional Model Mining Using Weighted Controlled Pattern Sampling

Mario Boley, Sandy Moens, Mario Boley, 2014, IDA.

Efficient Discovery of Interesting Patterns Based on Strong Closedness

Stefan Wrobel, Tamás Horváth, Mario Boley, 2009, SDM.

On the Complexity of Constraint-Based Theory Extraction

Thomas Gärtner, Mario Boley, Mario Boley, 2009, Discovery Science.

Probabilistic Structured Predictors

Thomas Gärtner, Shankar Vembu, Mario Boley, 2009, UAI.

Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms

Jilles Vreeken, Mario Boley, Panagiotis Mandros, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

Direct local pattern sampling by efficient two-step random procedures

Daniel Paurat, Thomas Gärtner, Claudio Lucchese, 2011, KDD.

Providing concise database covers using recursive tile sampling

Bart Goethals, Mario Boley, Sandy Moens, 2014, IFIP Working Conference on Database Semantics.

Providing Concise Database Covers Instantly by Recursive Tile Sampling

Bart Goethals, Mario Boley, Sandy Moens, 2014, Discovery Science.

The Efficient Discovery of Interesting Closed Pattern Collections

Mario Boley, Mario Boley, 2010 .

Evaluation of Machine Learning Methods for the Prediction of Key Properties for Novel Transparent Semiconductors

Mario Boley, Matthias Scheffler, Matthias Rupp, 2018 .

Communication-Efficient Distributed Online Learning with Kernels

Michael Kamp, Michael Mock, Mario Boley, 2016, ECML/PKDD.

Parallelizing randomized convex optimization

Mario Boley, Michael Kamp, 2015 .

One click mining: interactive local pattern discovery through implicit preference and performance learning

Stefan Wrobel, Bo Kang, Mario Boley, 2013, IDEA@KDD.

Direct Pattern Sampling with Respect to Pattern Frequency

Daniel Paurat, Thomas Gärtner, Claudio Lucchese, 2011, LWA.

Listing closed sets of strongly accessible set systems with applications to data

Stefan Wrobel, Tamás Horváth, Mario Boley, 2010, LWA.

Radon Machines: Effective Parallelisation for Machine Learning

Thomas Gärtner, Mario Boley, Olana Missura, 2017, NIPS 2017.

Discovering Functional Dependencies from Mixed-Type Data

Jilles Vreeken, Mario Boley, Panagiotis Mandros, 2020, KDD.

Efficient discovery of interesting patterns based on strong closedness

Stefan Wrobel, Tamás Horváth, Mario Boley, 2009, Stat. Anal. Data Min..

Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization

Assaf Schuster, Daniel Keren, Michael Kamp, 2014, ECML/PKDD.

Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms

Jilles Vreeken, Mario Boley, Panagiotis Mandros, 2019, IJCAI.

Approximating the number of frequent sets in dense data

Henrik Grosskreutz, Mario Boley, H. Grosskreutz, 2009, Knowledge and Information Systems.

On the intuitiveness of common discretization methods

Mario Boley, Ankit Kariryaa, 2016, KDD 2016.

Rule Discovery for Exploratory Causal Reasoning

Kailash Budhathoki, Jilles Vreeken, Mario Boley, 2018 .

A Randomized Approach for Approximating the Number of Frequent Sets

Henrik Grosskreutz, Mario Boley, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Efficient Closed Pattern Mining in Strongly Accessible Set Systems

Stefan Wrobel, Tamás Horváth, Mario Boley, 2007, MLG.

Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features

Thomas Gärtner, Michael Kamp, Mario Boley, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Efficiently Discovering Locally Exceptional Yet Globally Representative Subgroups

Jilles Vreeken, Mario Boley, Janis Kalofolias, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

Mining Interesting Patterns in Multi-relational Data with N-ary Relationships

Tijl De Bie, Eirini Spyropoulou, Mario Boley, 2013, Discovery Science.

Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings

Michael Kamp, Michael Mock, Michael May, 2013, ECML/PKDD.

Finding Patterns, Correlations, and Descriptors in Materials Data Using Subgroup Discovery and Compressed Sensing

Mario Boley, Runhai Ouyang, Matthias Scheffler, 2018 .

Formal Concept Sampling for Counting and Threshold-Free Local Pattern Mining

Thomas Gärtner, Henrik Grosskreutz, Mario Boley, 2010, SDM.

Subgroup Discovery for Election Analysis: A Case Study in Descriptive Data Mining

Henrik Grosskreutz, Mario Boley, Maike Krause-Traudes, 2010, Discovery Science.

On Approximating Minimum Infrequent and Maximum Frequent Sets

Mario Boley, 2007, Discovery Science.

Interesting pattern mining in multi-relational data

Tijl De Bie, Eirini Spyropoulou, Mario Boley, 2013, Data Mining and Knowledge Discovery.

Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features

Thomas Gärtner, Michael Kamp, Mario Boley, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Adaptive Communication Bounds for Distributed Online Learning pdf

Assaf Schuster, Michael Mock, Mario Boley, 2019, ArXiv.

Discovering Reliable Approximate Functional Dependencies

Jilles Vreeken, Mario Boley, Panagiotis Mandros, 2017, KDD.

In-Stream Frequent Itemset Mining With Output Proportional Memory Footprint

Tamás Horváth, Michael Mock, Mario Boley, 2015, LWA.

Discovering Robustly Connected Subgraphs with Simple Descriptions

Jilles Vreeken, Mario Boley, Janis Kalofolias, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Linear space direct pattern sampling using coupling from the past

Thomas Gärtner, Mario Boley, Sandy Moens, 2012, KDD.

Communication-Efficient Distributed Online Prediction using Dynamic Model Synchronizations

Assaf Schuster, Daniel Keren, Michael Kamp, 2013, BD3@VLDB.

Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery

Jilles Vreeken, Mario Boley, Luca M. Ghiringhelli, 2017, Data Mining and Knowledge Discovery.

Discovering dependencies with reliable mutual information

Jilles Vreeken, Mario Boley, Panagiotis Mandros, 2020, Knowledge and Information Systems.

Non-redundant Subgroup Discovery Using a Closure System

Henrik Grosskreutz, Mario Boley, H. Grosskreutz, 2009, ECML/PKDD.

Identifying domains of applicability of machine learning models for materials science

Jilles Vreeken, Matthias Rupp, Mario Boley, 2020, Nature communications.

Efficient discovery of interesting patterns based on strong closedness

Stefan Wrobel, Tamás Horváth, Mario Boley, 2009 .