- Comp-neuro - lists.cnsorg.org

NEURAL COMPUTATION - May, 2014

by Terry Sejnowski

Neural Computation - Contents -- Volume 26, Number 5 - May 1, 2014 Available online for download now: http://www.mitpressjournals.org/toc/neco/26/5 ----- Article A Transition to Sharp Timing in Stochastic Leaky Integrate-and-Fire Neurons Driven by Frozen Noisy Input Thibaud Taillefumier, Marcelo Magnasco Letters Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness Jason Michael Samonds, Brian Richard Potetz, and Tai Sing Lee Prewhitening High Dimensional fMRI Data Sets Without Eigendecompoistion Abd-Krim Seghouane, Yousef Saad Signal-tuned Gabor Functions as Models for Stimulus-dependent Cortical Receptive Fields Jose R. A. Torreao, Silvia M.C. Victer, and Marcos S. Amaral Energy Complexity of Recurrent Neural Networks Jiri Sima On Some Classes of Sequential Spiking Neural P Systems Xingyi Zhang, Xiangxiang Zeng, Bin Luo, and Linqiang Pan ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2014 - VOLUME 26 - 12 ISSUES USA Others Electronic Only Student/Retired $70 $193 $65 Individual $124 $187 $115 Institution $1,035 $1,098 $926 Canada: Add 5% GST MIT Press Journals, 238 Main Street, Suite 500, Cambridge, MA 02142-9902 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-orders(a)mit.edu ------------

April 11, 2014

PhD opportunities at Imperial College London in the Clopath lab

by Claudia Clopath

PhD opportunities in Computational Neuroscience. Computational Neuroscience Laboratory Headed by Dr. Claudia Clopath Department of Bioengineering Imperial College London -----------------Requirements:----------------- The Computational Neuroscience Laboratory, headed by Dr. Claudia Clopath, is looking for a talented PhD student, interested in working in the field of computational neuroscience, specifically addressing questions of learning and memory. The PhD position is fully funded, and has a flexible starting date. The perfect candidate has a strong mathematical, physical or engineering background (or equivalent), and a keen interest in biological and neural systems. Demonstrated programming skills are a plus. This position is restricted to EU citizens. More information can be found at: http://www.bg.ic.ac.uk/research/c.clopath/ -----------------Research topic:----------------- Learning and memory are among the most fascinating topic of neuroscience, yet our understanding of it is only at the beginning. Learning is thought to change the connections between the neurons in the brain, a process called synaptic plasticity. Using mathematical and computational tools, it is possible to model synaptic plasticity across different time scales, which helps understand how different types of memory are formed. The PhD candidate will be working to build those models of synaptic plasticity, and study the functional role of synaptic plasticity in artificial neural networks. They will have the opportunity to collaborate with experimental laboratories, which study connectivity changes and behavioural learning. -----------------The lab:----------------- The Computational Neuroscience Laboratory is very young and dynamic, and publishes in prestigious journals, such as Nature and Science. It is part of the Department of Bioengineering, which conducts state-of-the-art multidisciplinary research in biomechanics, neuroscience and neurotechnology. The lab is at Imperial College London, the 3rd ranked university in Europe, and is located in the city centre of London. -----------------How to apply:----------------- Candidates should send a single pdf file, consisting of a 1-page motivation letter, CV, and names and contact information of two references, to clopathlab.imperial(a)gmail.com, with the subject containing 'PHD2014'. The position remains open until filled, but applications received first will be first considered.

April 10, 2014

Postdoc opportunities at the Queensland Brain Institute

by Geoffrey Goodhill

The University of Queensland is currently offering generous postdoctoral fellowships, some targeted specifically at women, which can be held at the Queensland Brain Institute (QBI, www.qbi.uq.edu.au) a state-of-the-art facility located on The University of Queensland’s (UQ) St Lucia campus, Brisbane, Queensland, Australia. Established in 2003, the QBI's multidisciplinary environment is home to more than 300 staff and approximately 100 PhD students. Key areas of interest include computation and neuronal circuits, cognition and behaviour, neurogenesis and neuronal survival, genetics and epigenetics, neuronal development and connectivity, sensory systems, and synaptic function. QBI researchers have published almost 500 papers in the past two years, including 2 in Science, 4 in Nature, 2 in Neuron, 3 in Nature Neuroscience, 8 in Nature Genetics, 8 in Proceedings of the National Academy of Sciences of the USA, and 18 in Journal of Neuroscience. The period of appointment will be for three years and appointees are expected to commence in early 2015. The salary range is AU$71,528.60 – AU$79,708.50 (currently 1 AU$ = 0.94 US$). Each appointee will be entitled to maintenance funds of AU$20,000 over the term of the Fellowship to support research costs. Appointees relocating from interstate or overseas will be entitled to reimbursement of travel and relocation costs. For more details see http://www.uq.edu.au/research/research-management/uq-postdoctoral-research-… http://www.uq.edu.au/research/research-management/uq-postdoctoral-research-… and then contact the group leader at QBI with whom you are interested in working: http://qbi.uq.edu.au/group-leaders Note these fellowships are highly competitive and a strong publication record is an essential requirement. Professor Geoffrey J Goodhill Queensland Brain Institute and School of Mathematics & Physics University of Queensland St Lucia, QLD 4072, Australia Phone: +61 7 3346 6431 Fax: +61 7 3346 6301 Email: g.goodhill(a)uq.edu.au http://www.qbi.uq.edu.au/professor-geoffrey-goodhill

April 9, 2014

Open post-doc position in Nano-Electronics Design for Embedded NVM-based Cognitive Computing

by BICHLER Olivier

Open Postdoctoral Position in Nano-Electronics Design for Embedded NVM-based Cognitive Computing Novel embedded non-volatile memories, like resistive memory, are a fantastic technology enabler for the low-power chips capable of “cognitive” computing that are necessary for the new Internet of Things. To advance this topic, we are looking for a postdoctoral researcher to join our team in the Nano-Design project of the Campus Paris-Saclay. The goal of the project is to study and design an innovative embedded resistive memory-based neuro-inspired computing architecture, with computer vision as the primary target application. The ability to demonstrate state of the art applicative performance, on a pattern detection or classification problem, with a clear implementation gain, in silicon area or power consumption, is a major challenge for this ambitious project. To this aim, your research will associate high-level computer simulation, HDL modeling and IC design. Your ability to quickly adapt to and master our team simulation frameworks will give you a leading edge in your research. Finally, the realization of a fully integrated hybrid RRAM/CMOS chip demonstrator is a strong objective of the project. You will get to work in interaction with a team of tightly coupled labs of the Campus Paris-Saclay and CEA LETI. Candidates should hold a high-quality PhD in Electrical Engineering, Computer Engineering, Applied Physics or a related field, with experience in analog and/or mixed-signal CMOS electronics, Verilog/VHDL-AMS modeling and software engineering (working knowledge of C++ is a requirement). The candidate should be able to perform schematic capture and spice simulation; knowledge of industry standard tools and flows like Cadence Virtuoso or similar tools would be greatly appreciated. Other relevant subjects (not required for the position) are resistive memory (CBRAM, OXRAM), neuromorphic engineering, deep/convolutional/spiking neural network… Starting month: during 2014 18 months contract. Salary provided along CEA standards. About our team: Our team is composed of the Institut d’Electronique Fondamentale (IEF) in Université Paris-Sud, CNRS, the Laboratory of Innovation in Surface Chemistry and Nanosciences (LICSEN) at CEA IRAMIS and the Laboratory for Enhancing Reliability of Embedded Systems (LFSE) at CEA LIST. We are also working in strong interaction with the CEA LETI in Grenoble. Contacts: Olivier Bichler (olivier.bichler(a)cea.fr<mailto:olivier.bichler@cea.fr>) Christian Gamrat (christian.gamrat(a)cea.fr<mailto:christian.gamrat@cea.fr>) Tel: (+33)1.69.08.28.31 Contexte du projet NanoDesign / NanoDesign Project Context (in french) Les processeurs actuels reposent sur un couple technologie/architecture (CMOS / Von Neumann) ayant fait la preuve de sa remarquable efficacité. Toutefois, plusieurs éléments de contexte incitent à développer des recherches exploratoires, non pour remplacer les technologies existantes mais pour les compléter / les enrichir grâce à des briques de circuits dédiés compétitifs sur certaines gammes de tâches. Parmi ces éléments de contexte, on note en particulier: (i) la problématique de la consommation d'énergie qui s'aggrave avec le scaling, (ii) l'augmentation de la variabilité des dispositifs qui s'aggrave également à l'échelle nanométrique, (iii) l'évolution des domaines d'applications des processeurs avec notamment une augmentation de la demande concernant le traitement de données naturelles (sons, images, signaux biologiques...) et le traitement de très grandes quantités de données (notamment issues de l'internet ou de capteurs massivement distribués). Ces traitements consistent essentiellement en des taches de reconnaissance et de classification, qui nécessitent une quantité très importante de mémoire (constituant la connaissance a priori du système) et pour lesquels l’architecture processeur classique Von Neumann, qui sépare fondamentalement mémoire et unités de calcul, est particulièrement inefficace. Dans ce contexte, le cerveau représente un exemple particulièrement intéressant de système capable de traiter les données naturelles avec une efficacité redoutable, notamment en termes de consommation. Ce traitement d'information est réalisé de façon massivement parallèle, asynchrone et impulsionnelle grâce à un large ensemble de neurones interconnectés via des synapses. Le nombre de synapses par neurone étant de l'ordre de 104, l'implémentation matérielle d'une telle architecture suppose notamment une densité d'intégration extrême des synapses, d'où le lien fort avec les nanotechnologies. En particulier, il a été montré récemment qu’une synapse peut être émulée efficacement par une mémoire analogique à deux terminaux (un memristor). Celle-ci a la propriété de pouvoir se programmer dynamiquement, en impulsionnel, à la manière d’une synapse biologique, ce qui ouvre la voie à l’implémentation de mécanismes d’apprentissage performants et présents dans le vivant, tels que la plasticité synaptique de type STDP (Spike timing-dependent plasticity) [Poo04]. Les équipes du CEA LIST, du CEA IRAMIS et de l’IEF, impliquées dans le projet NanoDesign support de ce post-doc ont travaillé ensemble et séparément sur différents aspects de cette problématique. En particulier, le CEA LIST, dans lequel sera affecté le post-doc, a développé des architectures de circuits adaptées à différentes technologies mémoires (PCM [Bic12a], RRAM [Sur13], mémoires organiques [Bic12b]…) pour réaliser des fonctions de traitement de données neuro-inspirées. Il s’est doté d’une plateforme de simulation, Xnet [Bic13], dédiée à l’étude de ces architectures, intégrant des modèles fonctionnels ou semi-physiques de dispositifs et des méthodes d’apprentissage [Bic12c] (supervisées et non supervisées). Celle-ci a déjà permis de réaliser un certain nombre d’études, dans le cadre de thèses, notamment sur la robustesse de ces circuits vis-à-vis de la variabilité ainsi que sur la co-intégration nano/CMOS [Que13]. Ainsi, avec ce post-doc, dans ce projet, nous proposons notamment : ● De réaliser des assemblées de dispositifs à une échelle suffisante pour la réalisation d’une fonction cognitive de haut niveau (de type détection/classification visuelle). Ceci, dans un schéma d'interconnexion adapté à cette fonction. ● De poursuivre l’étude des modes de codages de l'information impulsionnels et les règles d'apprentissage et/ou de programmation adaptées aux applications et aux dispositifs étudiés. ● De poursuivre le développement de simulations au niveau circuit afin d'évaluer a priori les architectures et d'en comparer les mérites à d'autres formes de traitements des données. ● De réaliser des prototypes de circuits mixtes intégrant des technologies RRAM et des neurones réalisés en électronique conventionnelle. ● De combiner l'ensemble des avancées du projet pour la réalisation d’une fonction cognitive intégrée, de type détection/classification, pour une application réelle de traitement de données visuelles, avec l’ambition de démontrer la viabilité de notre approche à l’échelle d’un prototype pouvant se comparer aux solutions alternatives classiques sur des métriques concrètes (coût, consommation, fiabilité…). References [Bic12a] Bichler, O.; Suri, M.; Querlioz, D.; Gamrat et al., 'Visual Pattern Extraction Using Energy-Efficient ‘2-PCM Synapse’ Neuromorphic Architecture', IEEE Trans on Elec Devices 8, 2206-2214, 2012. [Bic12b] O. Bichler, W. Zhao, F. Alibart, S. Pleutin, S. Lenfant, D. Vuillaume, C. Gamrat, ‘Pavlov's Dog Associative Learning Demonstrated on Synaptic-Like Organic Transistors’, Neural Computation 25(2):549-566, 2012. [Bic12c] O. Bichler, D. Querlioz, S.J. Thorpe, J.-P. Bourgoin, C. Gamrat, ‘Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity’, Neural Networks, 32:339-348, 2012. [Poo04] Y. Dan and M. Ming Poo. ‘Spike timing-dependent plasticity of neural circuits’. Neuron, 44(1):23–30, 2004. [Bic13] O. Bichler, D. Roclin, C. Gamrat, D. Querlioz, ‘Design Exploration Methodology for Memristor-Based Spiking Neuromorphic Architectures with the Xnet Event-Driven Simulator’, Nanoscale Architectures (NANOARCH), 2013 IEEE/ACM International Symposium on, 2013. [Que13] D. Querlioz, O. Bichler, P. Dollfus, C. Gamrat, ‘Immunity to Device Variations in a Spiking Neural Network with Memristive Nanodevices’, Nanotechnology, IEEE Transactions on, 12(3):288-295, 2013. [Sur13] M. Suri, D. Querlioz, O. Bichler, G. Palma, E. Vianello, D. Vuillaume, C. Gamrat, B. DeSalvo, ‘Bio-Inspired Stochastic Computing Using Binary CBRAM Synapses’, Electron Devices, IEEE Transactions on, 60(7):2402-2409, 2013. -- Olivier Bichler CEA, LIST, Laboratory for Enhancing Reliability of Embedded Systems F-91191 Gif-sur-Yvette Cedex, France Ph: (+33)1.69.08.28.31 Fax: (+33)1.69.08.83.95

April 9, 2014

New Job Posting for Comp-neuro (F9804z)

by Neil Paz-Cruzat

*George Mason University Postdoctoral Research Fellow, Molecular Neuroscience/Computational Neuroscience* The George Mason University, Krasnow Institute seeks a Postdoctoral Research Fellow to develop and use multiscale spatiotemporal models of cardiac mitochondria to understand how mitochondrial structure and function are related. *Qualifications:* The ideal candidate is expected to have expertise in biological modeling, computer programming, and related numerical methods. Programming on parallel architectures is also desirable, as is knowledge of mitochondrial modeling. This project involves close collaboration with experimental collaborators. The duration of the position is subject to available research funding. For full consideration, applicants must apply for position number F9804z at http://jobs.gmu.edu/; complete and submit the online application; and upload a CV, a list of three references with contact information, and a description of research accomplishments.*These three required documents will need to be uploaded to the Other Doc category as a single (multipaged) document.*Questions may be addressed to*sjafri(a)gmu.edu*. AA/EOE

April 9, 2014

Postdoctoral positions in neuroimaging and rapid decision making

by Paul Sajda

The Laboratory for Intelligent Imaging and Neural Computing (LIINC) at Columbia University has immediate openings for several Postdoctoral Research Scientists. Specifically these positions will contribute to our research program focusing on understanding the neural basis for rapid decision making in the human brain and using this understanding to build brain computer interfaces (BCI) for next-generation human-machine interaction. Our approach leverages multi-modal neuroimaging, including a custom designed simultaneous EEG/fMRI system, to identify spatio-temporal cortical and subcortical networks underlying rapid decision making. Our analysis methods are deeply rooted in machine learning techniques, with a focus on using such techniques to enable single-trial analysis for correlating with decision variables. Applicants should have a background in one, and preferably several, of the following area: machine learning, neural signal processing, neuroimaging (EEG and/or fMRI), decision making, cognitive neuroscience and/or BCI. A Ph.D. in Engineering, Computer Science or Neuroscience is preferred. LIINC (liinc.bme.columbia.edu) is in the Department of Biomedical Engineering at Columbia University and interacts closely with other departments at Columbia, including Electrical Engineering, Biological Sciences, Computer Science and Neuroscience. We are also a member lab of the newly formed Center for Neural Engineering and Computation (CNEC) at Columbia University (cnec.columbia.edu) as well as the Institute for Data Sciences and Engineering (idse.columbia.edu) Additionally, we are a member of the Cognition and Neuroergonomics Collaborative Technology Alliance (CaN CTA) which a collaborative research effort between the Army Research Labs, Academia and Industry. Postdoctoral Research Scientists will thus have the opportunity to broadly collaborate will other scientists in academia, industry and government, being part of one of the largest collaborative programs in real-world neuroimaging and brain computer interfaces. Interested candidates should send via email their CV, three representative papers, the names of three references, and cover letter to Prof. Paul Sajda (psajda(a)columbia.edu) Applications will be considered until the positions are filled. The position is for one year, with the option to renew for 2-3 years, given satisfactory performance and available funding. Paul Sajda, Ph.D. Professor Departments of Biomedical Engineering, Electrical Engineering and Radiology Columbia University 351 Engineering Terrace Building, Mail Code 8904 1210 Amsterdam Avenue New York, NY 10027 tel: (212) 854-5279 fax: (212) 854-8725 email: ps629(a)columbia.edu http://liinc.bme.columbia.edu Editor-in-Chief IEEE Transactions on Neural Systems and Rehabilitation Engineering email: editortnsre(a)gmail.com http://tnsre.bme.columbia.edu

April 8, 2014

Bernstein Conference 2014 - Registration is now open

by Kerstin Mosch

*BERNSTEIN CONFERENCE 2014 in Göttingen* Registration is open now! Please register here <http://www.nncn.de/en/bernstein-conference/2014/registration>. Early registration deadline: July 7, 2014 **************************************************************************** Satellite Workshops <http://www.nncn.de/en/bernstein-conference/2014/workshops> September 02-03, 2014 Main Conference <http://www.nncn.de/en/bernstein-conference/2014/program-1> September 03-05, 2014 **************************************************************************** The Bernstein Conference has become the largest annual Computational Neuroscience Conference in Europe and now regularly attracts more than 500 international participants. This year, the Conference is organized by the Bernstein Focus Neurotechnology Goettingen and will take place September 03-05, 2014. In addition, there will be a series of pre-conference satellite workshops on September 02-03, 2014. The Bernstein Conference is a single-track conference, covering all aspects of Computational Neuroscience and Neurotechnology, and sessions for poster presentations are an integral part of the conference. The Bernstein conference will also feature a series of satellite workshops on September 02-03, 2014. The goal is to provide an informal forum for the discussion of timely research questions and challenges. For more information on the conference, please visit: http://www.bernstein-conference.de CONFERENCE DATE AND VENUE: Satellite Workshops September 02-03, 2014 Main Conference September 03-05, 2014 Venue: Central Lecture Hall (ZHG), Platz der Goettinger Sieben 5, 37073 Göttingen, Germany PUBLIC PHD STUDENT EVENT: September 02, 2014 PROGRAM COMMITTEE: Ilka Diester, Daniel Durstewitz, Thomas Euler, Alexander Gail, Matthias Kaschube, Jason Kerr, Roland Schaette, Fred Wolf, Florentin Wörgötter, ORGANIZING COMMITTEE: Florentin Wörgötter, Kerstin Mosch, Yvonne Reimann We look forward to seeing you in Goettingen in September! -- Dr. Kerstin Mosch Bernstein Center for Computational Neuroscience (BCCN) Goettingen Bernstein Focus Neurotechnology (BFNT) Goettingen Max Planck Institute for Dynamics and Self-Organization Am Fassberg 17 D-37077 Goettingen Germany T: +49 (0) 551 5176 - 425 E: kerstin(a)nld.ds.mpg.de I: www.bccn-goettingen.de I: www.bfnt-goettingen.de

April 7, 2014

School J. A. Balseiro 2014: Modeling in Neuroscience

by German Mato

****************************************************************************************** We're pleased to announce the "School J. A. Balseiro 2014: Modeling in Neuroscience" which will take place in Bariloche, Argentina from the 6th to the 31st of October. Additional information in: http://fisica.cab.cnea.gov.ar/escuelaib2014-neurociencias ******************************************************************************************

April 7, 2014

ANNPR 2014: Call for papers

by Dr. Schwenker

Please note the extended deadlines. Sixth IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition October 6-8, 2014 Concordia University, Montreal, Canada ANNPR 2014 invites papers that present original work in areas of neural networks, machine learning and pattern recognition, focusing on both theoretical and applied aspects. Topics of interest include, but not limited to: Methodological Issues - Supervised learning - Unsupervised learning - Combination of supervised and unsupervised learning - Feed-forward, recurrent, and competitive neural nets - Kernel machines - Hierarchical modular architectures and hybrid systems - Combination of neural networks and Hidden Markov models - Multiple classifier systems and ensemble methods - Probabilistic graphical models - Kernel methods - Deep architectures Applications in Pattern Recognition - Image processing and segmentation - Handwritten recognition and Document analysis - Sensor-fusion and multi-modal processing - Feature extraction, dimension reduction - Clustering and vector quantization - Speech and speaker recognition - Data, text, and web mining - Bioinformatics/Cheminformatics Note: A PDF of the Call for Papers may be downloaded at: http://users.encs.concordia.ca/~annpr14/ANNPR2014-CFP.pdf Invited Speakers ANNPR 2014 is proud to announce the following invited speakers: Dr. Yoshua Bengio, Canada Full Professor of the Department of Computer Science and Operations Research, University of Montreal Research Areas: Machine learning (ML), neural computation and adaptive perception, statistical learning algorithms Dr. Zhi-Hua Zhou, China Professor in the Department of Computer Science & Technology, Nanjing University, China Research Areas: Machine learning, data mining, pattern recognition, multimedia information retrieval Dr. Michael Herrmann, U.K. Lecturer at The University of Edinburgh School of Informatics Research Areas: Neurocomputation, neural nets, learning theory in autonomous agents & behavioral neuroscience, ML, dynamics of neural systems More information can be found on our homepage (see below) Special Sessions Fellow scientists wishing to organize a special session should submit a proposal to the ANNPR chairs (annpr2014(a)encs.concordia.ca) Proposals should include the session title, a list of topics covered by the session and a list of 3-6 papers for possible presentation in the session. Proposals must be received by March 15th, 2014. Important Dates Proposals of special sessions: March 15th, 2014 Paper submission: April 28th, 2014 Notification of acceptance: June 30th, 2014 Camera ready due: July 18, 2014 Workshop: October 6-8, 2014 General Chairs Ching Suen, Concordia University Canada Friedhelm Schwenker, Ulm University, Germany Neamat El Gayar, Cairo University, Egypt/Canada For more information, please visit or contact us: Homepage: http://www.annpr2014.com/ PDF CFP: http://users.encs.concordia.ca/~annpr14/ANNPR2014-CFP.pdf email: annpr2014(a)encs.concordia.ca -- Sixth IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition ANNPR 2014 October 6-8, 2014 Concordia University, Montreal, Canada Web: http://www.annpr2014.com/ eMail: annpr14(a)encs.concordia.ca

April 6, 2014

Last Mile, April 18 || DATA ANALYTICS 2014 || August 24 - 28, 2014 - Rome, Italy

by Cristina Pascual

INVITATION: ================= Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to DATA ANALYTICS 2014. The submission deadline is April 18, 2014. Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: http://www.iariajournals.org ================= ============== DATA ANALYTICS 2014 | Call for Papers =============== CALL FOR PAPERS, TUTORIALS, PANELS DATA ANALYTICS 2014, The Third International Conference on Data Analytics August 24 - 28, 2014 - Rome, Italy General page: http://www.iaria.org/conferences2014/DATAANALYTICS14.html Call for Papers: http://www.iaria.org/conferences2014/CfPDATAANALYTICS14.html Submission page: http://www.iaria.org/conferences2014/SubmitDATAANALYTICS14.html Contributions: - regular papers - short papers (work in progress) - posters - ideas - presentations - demos - doctoral forum submissions Proposals for: - symposia - workshops Submission deadline: April 18, 2014 Sponsored by IARIA, www.iaria.org Extended versions of selected papers will be published in IARIA Journals: http://www.iariajournals.org Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/9769.html Articles will be archived in the free access ThinkMind Digital Library: http://www.thinkmind.org The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas. All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels. Before submission, please check and conform with the Editorial rules: http://www.iaria.org/editorialrules.html DATA ANALYTICS 2014 Topics (topics and submission details: see CfP on the site) Fundamentals for data analytics Tools, frameworks and mechanisms for data analytics; Open API for data analytics; In-database analytics; Pre-built analytics (pattern, time-series, clustering, graph, statistical analysis, etc.); Analytics visualization; Multi-modal support for data analytics; Google/FaceBook/Twitter/etc. analytics; High-performance data analytics Mechanisms and features Scalable data analytics; Big data analytics; Deep data analytics; Mass data analytics; Storing, dropping and filtering data; Relevant/redundant/obsolete data analytics; Volume vs. semantics analytics; Nomad analytics; Predictive analytics; Trust in data analytics; Legal issues analytics; Failure on data analytics Sentiment/opinion analysis Architectures for generic sentiment analysis systems; Sentiment analysis techniques on social media; Document-level analysis; Sentence-level analysis; Aspect-based analysis; Comparative-sentiment analysis; Sentiment lexicon acquisition; Optimizing sentiment analysis algorithms; Applications of sentiment analysis. Application-oriented analytics Statistical applications; Simulation applications; Crawling web services; Cross-database analytics; Forecast analytics; Financial risk management; ROI analytics Target analytics Business analytics; Malware analytics; Cyber-threats analytics; Mining user logs; Reputation analytics; User choice analytics; Branding analytics; Utility proximity-search analytics; Survey-based online asset analytics; Online employment analytics; Geology analytics; Global climate analytics; Remote learning analytics; Homecare analytics; Population growth and migration analytics; Food-borne illness outbreaks analytics Big Data Foundational models for Big Data; Big Data Analytics and Metrics; Big Data processing and management; Big Data search and mining; Big Data platforms; Big Data persistence and preservation; Big Data and social networks; Big Data economics Huge data Knowledge Discovery from Huge Data; Computational Intelligence for Huge Data; Linked Huge Data; Security Intelligence with Huge Data -------------------- Committee: http://www.iaria.org/conferences2014/ComDATAANALYTICS14.html DATA ANALYTICS Advisory Chairs Fritz Laux, Reutlingen University, Germany Lina Yao, The University of Adelaide, Australia Eiko Yoneki, University of Cambridge, UK Takuya Yoshihiro, Wakayama University, Japan Felix Heine, University of Applied Sciences & Arts Hannover, Germany Dominik Slezak, University of Warsaw & Infobright Inc., Poland Panos M. Pardalos, University of Florida, USA Michele Melchiori, Universit� degli Studi di Brescia, Italy Rudolf Berrendorf, Bonn-Rhein-Sieg University, Germany Kerstin Lemke-Rust, Hochschule Bonn-Rhein-Sieg, Germany Sergio Ilarri, University of Zaragoza, Spain Les Sztandera, Philadelphia University, USA Prabhat Mahanti, University of New Brunswick, Canada Dominique Laurent, University of Cergy Pontoise, France Ryan G. Benton, University of Louisiana at Lafayette, USA Erik Buchmann, Karlsruhe Institute of Technology, Germany Stratos Idreos, Harvard University, USA Andrew Rau-Chaplin, Dalhousie University, Canada Takuya Yoshihiro, Wakayama University, Japan DATA ANALYTICS Industry/Research Liaison Chairs Qiming Chen, HP Labs - Palo Alto, USA Alain Crolotte, Teradata Corporation - El Segundo, USA Tiziana Guzzo, National Research Council/Institute of Research on Population and Social Policies - Rome, Italy Shlomo Geva, Queensland University of Technology - Brisbane, Australia Farhana Kabir, Intel, USA Prabhanjan Kambadur, IBM TJ Watson Research Center, USA Serge Mankovski, CA Technologies, Spain Sumit Negi, IBM Research, India Vedran Sabol, Know-Center - Graz, Austria George Tambouratzis, Institute for Language and Speech Processing - Athena Research Centre, Greece Yanchang Zhao, RDataMining.com, Australia Masahiro Terabe, Mitsubishi Research Institute, Inc., Japan Marina Santini, Santa Anna IT Research Institute AB, Sweden Mario Zechner, Know-Center, Austria DATA ANALYTICS Publicity Chairs Johannes Leveling, Dublin City University, Ireland Tim Weninger, University of Illinois in Urbana-Champaign, USA Roberto Zicari, Johann Wolfgang Goethe - University of Frankfurt, Germany Shandian Zhe, Purdue University, USA Michael Schaidnagel, Reutlingen University, Germany ================================================

April 4, 2014