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17th IDA 2018: 's-Hertogenbosch, The Netherlands
- Wouter Duivesteijn, Arno Siebes, Antti Ukkonen:
Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, 's-Hertogenbosch, The Netherlands, October 24-26, 2018, Proceedings. Lecture Notes in Computer Science 11191, Springer 2018, ISBN 978-3-030-01767-5
Invited Papers
- Luc De Raedt
, Hendrik Blockeel
Elements of an Automatic Data Scientist. 3-14 - Johannes Fürnkranz
The Need for Interpretability Biases. 15-27
Selected Contributions
- Leo Lahti
Open Data Science. 31-39 - Alexandre Almeida, Ana Alves
Automatic POI Matching Using an Outlier Detection Based Approach. 40-51 - Nouf Bindris, Saatviga Sudhahar, Nello Cristianini:
Fact Checking from Natural Text with Probabilistic Soft Logic. 52-61 - Thomas Bollen, Guillaume Leurquin, Siegfried Nijssen:
ConvoMap: Using Convolution to Order Boolean Data. 62-74 - Christoph Doell, Sarah E. Donohue, Cedrik Pätz, Christian Borgelt:
Training Neural Networks to Distinguish Craving Smokers, Non-craving Smokers, and Non-smokers. 75-86 - Adriana Fonseca Costa, Miriam Seoane Santos, Jastin Pompeu Soares, Pedro Henriques Abreu:
Missing Data Imputation via Denoising Autoencoders: The Untold Story. 87-98 - Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton:
Online Non-linear Gradient Boosting in Multi-latent Spaces. 99-110 - Radhika Gaonkar, Maryam Tavakol, Ulf Brefeld:
MDP-based Itinerary Recommendation using Geo-Tagged Social Media. 111-123 - Anil Goyal
Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization. 124-136 - Babak Hosseini
Non-negative Local Sparse Coding for Subspace Clustering. 137-150 - Saïd Jabbour, Nizar Mhadhbi, Badran Raddaoui, Lakhdar Sais:
Pushing the Envelope in Overlapping Communities Detection. 151-163 - Sen Jia
Right for the Right Reason: Training Agnostic Networks. 164-174 - Maksim Koptelov
Link Prediction in Multi-layer Networks and Its Application to Drug Design. 175-187 - Ville Laitinen
A Hierarchical Ornstein-Uhlenbeck Model for Stochastic Time Series Analysis. 188-199 - Marta Mercier, Miriam Seoane Santos, Pedro H. Abreu, Carlos Soares
Analysing the Footprint of Classifiers in Overlapped and Imbalanced Contexts. 200-212 - Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, Élisa Fromont
Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data. 213-224 - Felix Mohr, Marcel Wever
Reduction Stumps for Multi-class Classification. 225-237 - José Luis Balcázar
Decomposition of Quantitative Gaifman Graphs as a Data Analysis Tool. 238-250 - Jastin Pompeu Soares, Miriam Seoane Santos, Pedro Henriques Abreu, Hélder Araújo, João A. M. Santos
Exploring the Effects of Data Distribution in Missing Data Imputation. 251-263 - Oliver R. Sampson, Christian Borgelt, Michael R. Berthold:
Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors. 264-277 - Zakaria Saoud, Colin Fontaine
Expert Finding in Citizen Science Platform for Biodiversity Monitoring via Weighted PageRank Algorithm. 278-289 - Christine Sinoquet, Kamel Mekhnacha:
Random Forests with Latent Variables to Foster Feature Selection in the Context of Highly Correlated Variables. Illustration with a Bioinformatics Application. 290-302 - Benjamin Strang, Peter van der Putten, Jan N. van Rijn, Frank Hutter:
Don't Rule Out Simple Models Prematurely: A Large Scale Benchmark Comparing Linear and Non-linear Classifiers in OpenML. 303-315 - Saatviga Sudhahar, Nello Cristianini:
Detecting Shifts in Public Opinion: A Big Data Study of Global News Content. 316-327 - Adam Sutton, Thomas Lansdall-Welfare, Nello Cristianini:
Biased Embeddings from Wild Data: Measuring, Understanding and Removing. 328-339 - Bas van Boven, Peter van der Putten, Anders Åström, Hakim Khalafi, Aske Plaat
Real-Time Excavation Detection at Construction Sites using Deep Learning. 340-352 - Toon van Craenendonck, Sebastijan Dumancic, Elia Van Wolputte, Hendrik Blockeel
COBRAS: Interactive Clustering with Pairwise Queries. 353-366 - Gust Verbruggen, Luc De Raedt
Automatically Wrangling Spreadsheets into Machine Learning Data Formats. 367-379 - Patrick Winter, Christian Borgelt, Michael R. Berthold:
Learned Feature Generation for Molecules. 380-391
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