LEAPS 2013

1st International Workshop on Learning stratEgies and dAta Processing in nonStationary environments

The workshop is supported by the EU 7th Framework Program iSense, www.i-sense.org

iSenseLogo

Summary

Most machine learning techniques assume, either explicitly or implicitly, that the data-generating process is stationary. This assumption guarantees that the model learnt during the initial training phase remains valid over time and that its performance is in line with our expectations. Unfortunately, this assumption does not truly hold in the real world representing, in many cases, a simplistic approximation of the reality.

Data from real-world scenarios are often affected by nonstationarities and, during operational life, their describing model (or distribution) diverges from the one that yielded the training set. Among the causes generating nonstationarity we mention natural (and unknown) evolutions of the data-generating process, faults/aging affecting sensing and processing devices and model bias introduced by a poor training set. Learning-based systems have to be up-to-date to be effective, thereby requiring adaptation mechanisms to deal with nonstationary environments.

In machine learning nonstationarity is referred to as concept drift and several techniques to detect and adapt to concept drift have been presented in different application domains e.g., fraud detection in electronic transactions, sensor networks, intelligent vehicles and recommender systems. Other relevant scenarios are classification systems designed to cope with concept drift, such as those addressing email/spam filtering, internet events log analysis, stock market forecasting, context-aware and ubiquitous computing.

The workshop focuses on intelligent solutions to analyze/process data acquired in nonstationary environments. Original contributions in the field of fault detection and diagnosis, as well as cognitive approaches for learning characteristics of the process to handle nonstationarity are particularly welcome.

We encourage submissions presenting novel theoretical, methodological or experimental results.

Topics of interest

Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics:

  • Computational Intelligent solution for Fault Detection/ Isolation/ Identification
  • Change-Detection Tests (or Novelty-Detection Tests)
  • Change Detection exploiting contextual information
  • Adaptive Classifiers for Concept Drift
  • Concepts Drift and Recurring Concept management
  • Embedded systems implementing computational intelligence techniques to achieve intelligent behavior in nonstationary environments
  • Adaptive solutions to operate in evolving/faulty environments
  • Intelligent embedded systems for applications such as:
    • intelligent buildings
    • robotics
    • homeland security
    • environmental monitoring
    • sensor networks
    • water distribution networks
    • Intrusion detection in computer networks
  • Application domains where data are affected by concept drift

Workshop Chairs

Giacomo Boracchi, Politecnico di Milano, Italy giacomo.boracchi@polimi.it
Manuel Roveri, Politecnico di Milano, Italy manuel.roveri@polimi.it

Technical Program Committee

Rami Abielmona, University of Ottawa, Canada
Haibo He, University of Rhode Island, US
Vasso Reppa, KIOS Research Center for Intelligent Systems and Networks, Cyprus
Michalis P. Michaelides, Cyprus University of Technlolgy
Stefano Zanero, Politecnico di Milano, Italy
Peter Tino, University of Birmingham, UK
Vicenç Puig, Universitat Politècnica de Catalunya, Spain
Maurizio Bocca, University of Utah, USA
Vincent Lemaire, Orange Labs, France
Alessandro Lazaric, INRIA Lille, France
Daniele Caltabiano, STMicroelectronics, Milano Italy
Leandro L. Minku, The University of Birmingham, UK

Submission

Authors are invited to submit original, English-language research contributions or experience reports. Papers should be no longer than 10 pages formatted according to the well-known LNCS Springer style. All aspects of the submission and notification process will be handled online via the EasyChair Conference System at:

https://www.easychair.org/conferences/?conf=aiai2013

Please make sure you select the workshop track in the first step of the submission process.

Important Dates

Paper submission:
May 10, 2013 Extended: May 15, 2013

Author notifications:
May 30, 2013 Extended: June 7, 2013

Camera-ready submission:
June 7, 2013 Extended: June 21, 2013

Early registration:
June 7, 2013 Extended: June 14, 2013

Publication

Submitted papers will be refereed for quality, correctness, originality, and relevance. Notification and reviews will be communicated via email. Accepted papers will be presented at the workshop and published in the Proceedings of the main event (by Springer). They will also be considered for potential publication in the Special Issues of the Conference.

Registration fees and benefits for the workshops’ participants are exactly identical with the ones of the main AIAI 2013 event.