posted by user: paws || 1149 views || tracked by 2 users: [display]

mtp 2014 : ECML/PKDD 2014 Workshop on Multi-Target Prediction


When Sep 15, 2014 - Sep 15, 2014
Where Nancy, France
Submission Deadline Jun 15, 2014
Notification Due Jul 31, 2014

Call For Papers

Traditional methods in machine learning and statistics provide data-driven models for predicting one-dimensional targets, such as binary outputs in classification and real-valued outputs in regression. In recent years, novel application domains have triggered fundamental research on more complicated problems where multi-target predictions are required. Such problems arise in diverse application domains, such as document categorization, tag recommendation of images, video and music, information retrieval, natural language processing, drug discovery, biology, etc.

Specific multi-target prediction problems have been studied in a variety of subfields of machine learning and statistics, such as multi-label classification, multivariate regression, pairwise learning, structured output prediction, recommender systems, preference learning, multi-task learning, dyadic prediction and collective learning. Despite their commonalities, work on solving problems in the above domains has typically been performed in isolation, without much interaction between the different sub-communities. The main goal of the workshop is to construct a unifying discussion platform for the above-mentioned subfields of machine learning, by focusing on the simultaneous prediction of multiple, mutually dependent output variables. Contributions might concern (but are not limited to) the following topics:

- Multi-label classification
- Multivariate regression / Multi-output regression
- Structured output prediction
- Multi-task learning and transfer learning
- Constructive machine learning
- Pairwise learning / dyadic prediction
- Label ranking
- Matrix factorization and collaborative filtering methods
- Recommender systems
- Sequence learning, time series prediction and data stream mining
- Collective classification and inference
- Conditional random fields, structured SVMs and graphical models
- Evaluation of multi-target prediction systems
- Data sampling in multi-target prediction
- Efficient inference and large-scale learning in multi-target pred.
- Theoretical results on multi-target prediction
- Incorporation of domain knowledge in multi-target prediction

Full papers can take up to 8 pages and they need to report original work that has not been published yet. Extended abstracts have a maximum of 3 pages and can also concern a discussion of a given topic or past published work, if the precise references to the original publication are mentioned. Instructions can be found at the workshop website.

Related Resources

MIWAI 2017   The 11th Multi-disciplinary International Workshop on Artificial Intelligence
SASO 2017   The Eleventh IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2017)
ICAART 2018   10th International Conference on Agents and Artificial Intelligence
PAAMS 2018   PAAMS 2018 - 16th International Conference on Practical Applications of Agents and Multi-Agent Systems
BE 2017   Special Issue on Intelligent Systems for Environmental Applications
BESC 2017   4th International Conference on Behavioural, Economic, and Socio-Cultural Computing - 16-18 October, 2017 (BESC 2017)
SSD 2018   15th Multi-Conference on Systems, Signals and Devices
PredictGIS 2017   1st Workshop on Prediction of Human Mobility at ACM SIGSPATIAL 2017 (PredictGIS 2017)