Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers

Ahlame Douzal-Chouakria, José A. Vilar, Pierre-François Marteau
Springer, 3 août 2016 - 173 pages
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This book constitutes the refereed proceedings of the First ECML PKDD Workshop, AALTD 2015, held in Porto, Portugal, in September 2016.
The 11 full papers presented were carefully reviewed and selected from 22 submissions. The first part focuses on learning new representations and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on classification and clustering with challenging applications on medicine or earth observation data. These works show different ways to consider temporal dependency in clustering or classification processes. The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.


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Table des matières

A Hierarchical Coclustering Formalization
Dense BagofTemporalSIFTWords for Time Series Classification
Dimension Reduction in Dissimilarity Spaces for Time Series Classification
Time Series Classification and Clustering
Fuzzy Clustering of Series Using Quantile Autocovariances
A Reservoir Computing Approach for Balance Assessment
Learning Structures in Earth Observation Data with Gaussian Processes
Monitoring Short Term Changes of Infectious Diseases in Uganda with Gaussian Processes
Recent Methods and Results
Metric Learning for Time Series Comparison
A Multimodal Metric Learning Framework for Time Series kNN Classification
A Comparison of Progressive and Iterative Centroid Estimation Approaches Under Time Warp
CoarseDTW for Sparse Time Series Alignment
Author Index
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