[agents] MLDSA 2014 - Machine learning for sensory data analysis workshop (Co-located with PRICAI/PRIMA in GoldCoast, Australia)

[Tony Savarimuthu]

2nd International workshoop on Machine learning for sensory data analysis (MLSDA - 2014)
Website:http://www.covic.otago.ac.nz/MLSDA14

Description of the Workshop:
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Recent advances in the wireless technology and sensor networks have given both new opportunities and new challenges to data networking and mining. Large amounts of sensory data are being gathered and transmitted for various applications and these need to be analyzed and utilized effectively. On these other hand, the sensory and networking data exchanged between sensing devices can be explored for smart and efficient in-network and application designs. The nature of the sensing environment, however, has a number of constraints that differentiate it from conventional machine learning settings. Sensory data are generated in continuous streams from a dynamic environment, and stored in a distributed manner. Meanwhile, sensing devices are subject to limitation of power, memory, and communication bandwidth. To address these challenges there is a wide range of machine learning techniques that need to be adapted and utilized. Following the successful inaugural MLSDA workshop in 2013 held in Dunedin NZ, MLSDA’14 joins PRICAI'14 and PRIMA'14 in the sunny Gold Coast to provide a golden opportunity for researchers working in relevant fields to share their research progress, and establish potential collaboration for the future.

Topics of this workshop include, but are not limited to, the theory and application of machine learning in:

    Time series analysis
    Motif detection
    Anomaly detection
    Online data stream mining
    Concept drift detection and handling
    Feature extraction and dimension reduction
    Ensemble learning
    Sensory data modeling and prediction
    Smart environment
    Self-organization
    Distributed signal processing and compressed sensing
    Resource management and task scheduling
    Energy efficiency and cloud offloading
    Reinforcement learning in WSNs
    Privacy-preserving data mining
    Multimodal signal processing
    Activity detection and behaviour classification
    Localization
    Intrusion detection
    Multi-agent approach for sensory data analysis
    Applications and real-world deployment issues

MLSDA'14 adopts the same double-blind reviewing process as that of PRICAI'14. It is expected that the conference proceedings will be published by ACM ICPS and hosted by the ACM Digital library as in 2013.

Important Dates

Workshop Papers due:            October 3, 2014
Notification of Acceptance:           October 24, 2014
Workshop Proceedings due:          November 07, 2014
Workshop Dates:                    December 1 or 2, 2014