Adaptive and Intelligent Systems
Third International Conference, ICAIS 2014, Bournemouth, UK, September 8-10, 2014. Proceedings
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Abdelhamid Bouchachia
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Article
Randomising the Simple Recurrent Network: a lightweight, energy-efficient RNN model with application to forecasting problems
Multi-variate time-series (MTS) forecasting is the prediction of future for a sequence of data. The process of analysing obtained data can benefit the community financially and securely, for instance observing...
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Article
Open AccessScaling up stochastic gradient descent for non-convex optimisation
Stochastic gradient descent (SGD) is a widely adopted iterative method for optimizing differentiable objective functions. In this paper, we propose and discuss a novel approach to scale up SGD in applications ...
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Article
Online Bayesian shrinkage regression
The present work introduces an original and new online regression method that extends the shrinkage via limit of Gibbs sampler (SLOG) in the context of online learning. In particular, we theoretically show how...
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Chapter and Conference Paper
Asynchronous Stochastic Variational Inference
Stochastic variational inference (SVI) employs stochastic optimization to scale up Bayesian computation to massive data. Since SVI is at its core a stochastic gradient-based algorithm, horizontal parallelism c...
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Chapter and Conference Paper
Model Selection in Online Learning for Times Series Forecasting
This paper discusses the problem of selecting model parameters in time series forecasting using aggregation. It proposes a new algorithm that relies on the paradigm of prediction with expert advice, where onli...
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Chapter and Conference Paper
Deep Online Hierarchical Unsupervised Learning for Pattern Mining from Utility Usage Data
Machine learning approaches for non-intrusive load monitoring (NILM) have focused on supervised algorithms. Unsupervised approaches can be more interesting and of more practical use in real case scenarios. Mor...
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Article
MSAFIS: an evolving fuzzy inference system
In this paper, the problem of learning in big data is considered. To solve this problem, a new algorithm is proposed as the combination of two important evolving and stable intelligent algorithms: the sequenti...
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Article
A review of smart homes in healthcare
The technology of Smart Homes (SH), as an instance of ambient assisted living technologies, is designed to assist the homes’ residents accomplishing their daily-living activities and thus having a better quali...
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Article
Social media for crisis management: clustering approaches for sub-event detection
Social media is getting increasingly important for crisis management, as it enables the public to provide information in different forms: text, image and video which can be valuable for crisis management. Such...
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Chapter
Information Propagation in Social Networks During Crises: A Structural Framework
In crisis situations like riots, earthquakes, storms, etc. information plays a central role in the process of organizing interventions and decision making. Due to their increasing use during crises, social med...
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Article
Online and interactive self-adaptive learning of user profile using incremental evolutionary algorithms
In this contribution, we explore the application of evolutionary algorithms for information filtering. There are two crucial issues we consider in this study: (1) the generation of the user’s profile which is ...
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Book and Conference Proceedings
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Chapter and Conference Paper
Multi-resident Activity Recognition Using Incremental Decision Trees
The present paper proposes the application of decision trees to model activities of daily living in a multi-resident context. An extension of ID5R, called E-ID5R, is proposed. It augments the leaf nodes and allow...
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Chapter
Financial Time Series Processing: A Roadmap of Online and Offline Methods
Because financial information is a vital asset for financial and economic organizations, it requires careful management so that those organizations can enhance and facilitate the decision making process. The f...
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Article
Dynamic Clustering
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Chapter and Conference Paper
Neurodynamical Top-Down Processing during Auditory Attention
Understanding the neural dynamics underlying the fast discrimination of music and speech in noise is a very challenging task for neurocomputational and speech recognition models. In this paper, we present a mo...
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Chapter
Incremental Spectral Clustering
In the present contribution, a novel algorithm for off-line spectral clustering algorithm is introduced and an online extension is derived in order to deal with sequential data. The proposed algorithm aims at ...
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Article
Fuzzy classification in dynamic environments
The persistence and evolution of systems essentially depend on their adaptivity to new situations. As an expression of intelligence, adaptivity is a distinguishing quality of any system that is able to learn a...
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Book and Conference Proceedings
Adaptive and Intelligent Systems
Second International Conference, ICAIS 2011, Klagenfurt, Austria, September 6-8, 2011. Proceedings
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Chapter and Conference Paper
Incremental Semi-automatic Correction of Misclassified Spatial Objects
This paper proposes a decision tree based approach for semi-automatic correction of misclassified spatial objects in the Austrian digital cadastre map. Departing from representative areas, proven to be free of...
