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The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain.

The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.



2017 | OriginalPaper | Buchkapitel

Towards Integrative Machine Learning and Knowledge Extraction

Andreas Holzinger, Randy Goebel, Vasile Palade, Massimo Ferri

2017 | OriginalPaper | Buchkapitel

Machine Learning and Knowledge Extraction in Digital Pathology Needs an Integrative Approach

Andreas Holzinger, Bernd Malle, Peter Kieseberg, Peter M. Roth, Heimo Müller, Robert Reihs, Kurt Zatloukal

2017 | OriginalPaper | Buchkapitel

Comparison of Public-Domain Software and Services For Probabilistic Record Linkage and Address Standardization

Sou-Cheng T. Choi, Yongheng Lin, Edward Mulrow

2017 | OriginalPaper | Buchkapitel

Better Interpretable Models for Proteomics Data Analysis Using Rule-Based Mining

Fahrnaz Jayrannejad, Tim O. F. Conrad

2017 | OriginalPaper | Buchkapitel

Probabilistic Logic Programming in Action

Arnaud Nguembang Fadja, Fabrizio Riguzzi

2017 | OriginalPaper | Buchkapitel

Persistent Topology for Natural Data Analysis — A Survey

Massimo Ferri

2017 | OriginalPaper | Buchkapitel

Predictive Models for Differentiation Between Normal and Abnormal EEG Through Cross-Correlation and Machine Learning Techniques

Jefferson Tales Oliva, João Luís Garcia Rosa

2017 | OriginalPaper | Buchkapitel

A Brief Philosophical Note on Information

Vincenzo Manca

2017 | OriginalPaper | Buchkapitel

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

Keith Feldman, Louis Faust, Xian Wu, Chao Huang, Nitesh V. Chawla

2017 | OriginalPaper | Buchkapitel

A Fast Semi-Automatic Segmentation Tool for Processing Brain Tumor Images

Andrew X. Chen, Raúl Rabadán

2017 | OriginalPaper | Buchkapitel

Topological Characteristics of Oil and Gas Reservoirs and Their Applications

V. A. Baikov, R. R. Gilmanov, I. A. Taimanov, A. A. Yakovlev

2017 | OriginalPaper | Buchkapitel

Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment

Deepika Singh, Erinc Merdivan, Sten Hanke, Johannes Kropf, Matthieu Geist, Andreas Holzinger


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