We present a solution to the MoReBikeS challenge in ECML PKDD 2015 conference by analysing data from different aspects, by visualising latent patterns, by building a set of featur...
The goal of domain adaptation is to solve the problem of di↵erent joint distribution of observation and labels in the training and testing data sets. This problem happens in many...
Real-time estimation of destination and travel time for taxis is of great importance for existing electronic dispatch systems. We present an approach based on trip matching and ens...
Sensors and Internet-of-Things scenarios promise a wealth of interaction data that can be naturally represented by means of timevarying graphs. This brings forth new challenges for...
Our aim is to extend standard principal component analysis for non-time series data to explore and highlight the main structure of multiple sets of multivariate time series. To thi...
There has been extensive research on social networks and methods for specific tasks such as: community detection, link prediction, and tracing information cascades; and a recent e...
Abstract. This work is in the context of kernel-based learning algorithms for sequence data. We present a probabilistic approach to automatically extract, from the output of such s...
Abstract. Machine learning processes consist in collecting data, obtaining a model and applying it to a given task. Given a new task, the standard approach is to restart the learni...