AIST is a scientific conference on Analysis of Images, Social Networks, and Texts. The conference is intended for computer scientists and practitioners whose research interests involve Internet mathematics and other related fields of data science. Similar to the previous year, the conference will be focused on applications of data mining and machine learning techniques to various problem domains: image processing, analysis of social networks, and natural language processing. We hope that the participants will benefit from the interdisciplinary nature of the conference and exchange experience.
Conceptual Structures in LEADing and Best Enterprise PracticesSimon Polovina
Polovina, Simon: von Rosing, Mark; Laurier, Wim (2014) "Conceptual Structures in LEADing and Best Enterprise Practices", Graph-Based Representation and Reasoning (21st International Conference on Conceptual Structures, ICCS 2014 Iași, Romania, July 27-30), Hernandez, Nathalie; Jäschke, Robert; Croitoru, Madalina (Eds.), LNAI 8577, Springer Cham Heidelberg New York Dordrecht London, 293-298.
Abstract: Conceptual Structures, namely Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are beginning to make an impact in Industry. This is evidenced in LEAD as it seeks to provide its 3100+ industry practitioners in many Fortune 500 and public organisations with capabilities that can handle ontology and semantics. The existing ontology and semantics work in LEAD, supported by the Global University Alliance, is described and how CGs, FCA and their tools (e.g. CoGui, CG-FCA) enhance this endeavour.
AIST is a scientific conference on Analysis of Images, Social Networks, and Texts. The conference is intended for computer scientists and practitioners whose research interests involve Internet mathematics and other related fields of data science. Similar to the previous year, the conference will be focused on applications of data mining and machine learning techniques to various problem domains: image processing, analysis of social networks, and natural language processing. We hope that the participants will benefit from the interdisciplinary nature of the conference and exchange experience.
Conceptual Structures in LEADing and Best Enterprise PracticesSimon Polovina
Polovina, Simon: von Rosing, Mark; Laurier, Wim (2014) "Conceptual Structures in LEADing and Best Enterprise Practices", Graph-Based Representation and Reasoning (21st International Conference on Conceptual Structures, ICCS 2014 Iași, Romania, July 27-30), Hernandez, Nathalie; Jäschke, Robert; Croitoru, Madalina (Eds.), LNAI 8577, Springer Cham Heidelberg New York Dordrecht London, 293-298.
Abstract: Conceptual Structures, namely Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are beginning to make an impact in Industry. This is evidenced in LEAD as it seeks to provide its 3100+ industry practitioners in many Fortune 500 and public organisations with capabilities that can handle ontology and semantics. The existing ontology and semantics work in LEAD, supported by the Global University Alliance, is described and how CGs, FCA and their tools (e.g. CoGui, CG-FCA) enhance this endeavour.
These are opening slides of the 8th International Conference on Analysis of Images, Social Networks and Texts (AIST 2019). We summarise general facts on AIST conf. series. See http://aistconf.org website for more details.
Developing and PublishingAcademic ProductsSanjay Goel
These lecture slides were used in two lectures delivered on 25th June 2014 at a 3 day workshop organised under the TEQIP (Technical Education Quality Improvement Programme ) scheme by Equate India for the faculty participants from few NITs, Aligarh Muslim University, and Sardar Patel College of Engineering.
Big data impact on society: a research roadmap for Europe (BYTE project resea...Anna Fensel
With its rapid growth and increasing adoption, big data is producing a growing impact in society. Its usage is opening both opportunities such as new business models and economic gains and risks such as privacy violations and discrimination. Europe is in need of a comprehensive strategy to optimise the use of data for a societal benefit and increase the innovation and competitiveness of its productive activities. In this paper, we contribute to the definition of this strategy with a research roadmap that considers the positive and negative externalities associated with big data, maps research and innovation topics in the areas of data management, processing, analytics, protection, visualisation, as well as non-technical topics, to the externalities they can tackle, and provides a time frame to address these topics.
For more than 10 years, research on service descriptions has mainly studied software-based services and provided languages such as WSDL, OWL-S, WSMO for SOAP, and hREST for REST. Nonetheless, recent developments from service management (e.g., ITIL and COBIT) and cloud computing (e.g. Software-as-a-Service) have brought new requirements to service descriptions languages: the need to also model business services and account for the multi-faceted nature of services. Business-orientation, co- creation, pricing, legal aspects, and security issues are all elements which must also be part of service descriptions. While ontologies such as e  service and e  value provided a first modeling attempt to capture a business perspective, concerns on how to contract services and the agreements entailed by a contract also need to be taken into account. This has for the most part been disregarded by the e-family of ontologies. In this paper, we review the evolution and provide an overview of Linked USDL, a comprehensive language which provides a (multi-faceted) description to enable the commercialization of (business and technical) services over the web.
Slides from 'Stay Calm & Keep Current' - How to filter machine learning related academic papers - introduction of our open source project for this purpose.
SGCI - The Science Gateways Community Institute: International Collaboration ...Sandra Gesing
Science gateways - also called virtual research environments or virtual labs - allow science and engineering communities to access shared data, software, computing services, instruments, and other resources specific to their disciplines. The US Science Gateways Community Institute (SGCI), opened in August 2016, provides free resources, services, experts, and ideas for creating and sustaining science gateways. It offers five areas of services to the science gateway developer and user communities: the Incubator, Extended Developer Support, the Scientific Software Collaborative, Community Engagement and Exchange, and Workforce Development. While all these services are available to US-based communities, the Incubator, the Scientific Software Collaborative and the Community Engagement and Exchange serve also the international communities. SGCI aims at supporting beyond borders on international scale with diverse measures and to form and deepen collaborations with partner organizations and coalitions beneficial and/or related to the science gateways community. Research topics are independent of national borders and researchers spread worldwide can benefit from each other’s research results, software, data and from lessons learned — via online materials and publications or at international events. The gateway community has benefitted from this type of exchange for years and one mission of SGCI is to support the international community. This talk will present related work describing the benefits of international collaborations generally, and specifically as they relate to science gateways. It will go into detail regarding SGCI’s ongoing work on an international scale and SGCI's work planned in the near future to foster collaborations under consideration of challenges such as different timezones and long distances between collaborators.
DSpace-CRIS_An open source solution for Research_EDU15Michele Mennielli
The research area is a complex world to manage. It involves collecting data, supporting researchers and administrators, monitoring results, allocating resources efficiently, enhancing visibility, and strengthening national and international collaborations. RIMs manage these activities, but they might be too expensive. This is why Cineca developed DSpace-CRIS, and released it in open source.
Highlights from the Workshop on Sustainable Software Sustainability 2019Shoaib Sufi
Talk given at the inaugural NL-RSE meeting - NL-RSE 19 (November 2019) https://nl-rse.org/events/NL-RSE19.html on highlights from the the Workshop of Sustainable Software Sustainability 2019 in April (https://www.software.ac.uk/wosss19)
Interpretable Concept-Based Classification with Shapley ValuesDmitrii Ignatov
The slides contain our talk on Shapley values as an interpretable Machine learning technique for JSM-method, a rule-based classification and reasoning technique, for ranking particular attributes of an undetermined example under classification.
https://doi.org/10.1007/978-3-030-57855-8_7
Turning Krimp into a Triclustering Technique on Sets of Attribute-Condition P...Dmitrii Ignatov
Mining ternary relations or triadic Boolean tensors is one of the recent trends in knowledge discovery that allows one to take into account various modalities of input object-attribute data.
For example, in movie databases like IMBD, an analyst may find not only movies grouped by specific genres but see their common keywords. In the so called folksonomies, users can be grouped according to their shared resources and used tags. In gene expression analysis, genes can be grouped along with samples of tissues and time intervals providing comprehensible patterns. However, pattern explosion effects even with one more dimension are seriously aggravated. In this paper, we continue our previous study on searching for a smaller collection of ``optimal'' patterns in triadic data with respect to a set of quality criteria such as patterns' cardinality, density, diversity, coverage, etc. We show how a simple data preprocessing has enabled us to use the frequent itemset mining algorithm.
More Related Content
Similar to Personal Experiences of Publishing with Springer from both Editor and Author Perspectives
These are opening slides of the 8th International Conference on Analysis of Images, Social Networks and Texts (AIST 2019). We summarise general facts on AIST conf. series. See http://aistconf.org website for more details.
Developing and PublishingAcademic ProductsSanjay Goel
These lecture slides were used in two lectures delivered on 25th June 2014 at a 3 day workshop organised under the TEQIP (Technical Education Quality Improvement Programme ) scheme by Equate India for the faculty participants from few NITs, Aligarh Muslim University, and Sardar Patel College of Engineering.
Big data impact on society: a research roadmap for Europe (BYTE project resea...Anna Fensel
With its rapid growth and increasing adoption, big data is producing a growing impact in society. Its usage is opening both opportunities such as new business models and economic gains and risks such as privacy violations and discrimination. Europe is in need of a comprehensive strategy to optimise the use of data for a societal benefit and increase the innovation and competitiveness of its productive activities. In this paper, we contribute to the definition of this strategy with a research roadmap that considers the positive and negative externalities associated with big data, maps research and innovation topics in the areas of data management, processing, analytics, protection, visualisation, as well as non-technical topics, to the externalities they can tackle, and provides a time frame to address these topics.
For more than 10 years, research on service descriptions has mainly studied software-based services and provided languages such as WSDL, OWL-S, WSMO for SOAP, and hREST for REST. Nonetheless, recent developments from service management (e.g., ITIL and COBIT) and cloud computing (e.g. Software-as-a-Service) have brought new requirements to service descriptions languages: the need to also model business services and account for the multi-faceted nature of services. Business-orientation, co- creation, pricing, legal aspects, and security issues are all elements which must also be part of service descriptions. While ontologies such as e  service and e  value provided a first modeling attempt to capture a business perspective, concerns on how to contract services and the agreements entailed by a contract also need to be taken into account. This has for the most part been disregarded by the e-family of ontologies. In this paper, we review the evolution and provide an overview of Linked USDL, a comprehensive language which provides a (multi-faceted) description to enable the commercialization of (business and technical) services over the web.
Slides from 'Stay Calm & Keep Current' - How to filter machine learning related academic papers - introduction of our open source project for this purpose.
SGCI - The Science Gateways Community Institute: International Collaboration ...Sandra Gesing
Science gateways - also called virtual research environments or virtual labs - allow science and engineering communities to access shared data, software, computing services, instruments, and other resources specific to their disciplines. The US Science Gateways Community Institute (SGCI), opened in August 2016, provides free resources, services, experts, and ideas for creating and sustaining science gateways. It offers five areas of services to the science gateway developer and user communities: the Incubator, Extended Developer Support, the Scientific Software Collaborative, Community Engagement and Exchange, and Workforce Development. While all these services are available to US-based communities, the Incubator, the Scientific Software Collaborative and the Community Engagement and Exchange serve also the international communities. SGCI aims at supporting beyond borders on international scale with diverse measures and to form and deepen collaborations with partner organizations and coalitions beneficial and/or related to the science gateways community. Research topics are independent of national borders and researchers spread worldwide can benefit from each other’s research results, software, data and from lessons learned — via online materials and publications or at international events. The gateway community has benefitted from this type of exchange for years and one mission of SGCI is to support the international community. This talk will present related work describing the benefits of international collaborations generally, and specifically as they relate to science gateways. It will go into detail regarding SGCI’s ongoing work on an international scale and SGCI's work planned in the near future to foster collaborations under consideration of challenges such as different timezones and long distances between collaborators.
DSpace-CRIS_An open source solution for Research_EDU15Michele Mennielli
The research area is a complex world to manage. It involves collecting data, supporting researchers and administrators, monitoring results, allocating resources efficiently, enhancing visibility, and strengthening national and international collaborations. RIMs manage these activities, but they might be too expensive. This is why Cineca developed DSpace-CRIS, and released it in open source.
Highlights from the Workshop on Sustainable Software Sustainability 2019Shoaib Sufi
Talk given at the inaugural NL-RSE meeting - NL-RSE 19 (November 2019) https://nl-rse.org/events/NL-RSE19.html on highlights from the the Workshop of Sustainable Software Sustainability 2019 in April (https://www.software.ac.uk/wosss19)
Interpretable Concept-Based Classification with Shapley ValuesDmitrii Ignatov
The slides contain our talk on Shapley values as an interpretable Machine learning technique for JSM-method, a rule-based classification and reasoning technique, for ranking particular attributes of an undetermined example under classification.
https://doi.org/10.1007/978-3-030-57855-8_7
Turning Krimp into a Triclustering Technique on Sets of Attribute-Condition P...Dmitrii Ignatov
Mining ternary relations or triadic Boolean tensors is one of the recent trends in knowledge discovery that allows one to take into account various modalities of input object-attribute data.
For example, in movie databases like IMBD, an analyst may find not only movies grouped by specific genres but see their common keywords. In the so called folksonomies, users can be grouped according to their shared resources and used tags. In gene expression analysis, genes can be grouped along with samples of tissues and time intervals providing comprehensible patterns. However, pattern explosion effects even with one more dimension are seriously aggravated. In this paper, we continue our previous study on searching for a smaller collection of ``optimal'' patterns in triadic data with respect to a set of quality criteria such as patterns' cardinality, density, diversity, coverage, etc. We show how a simple data preprocessing has enabled us to use the frequent itemset mining algorithm.
On the Family of Concept Forming Operators in Polyadic FCADmitrii Ignatov
Triadic Formal Concept Analysis (3FCA) was introduced by Lehman and Wille almost two decades ago. And many researchers work in Data Mining and Formal Concept Analysis using the notions of closed sets, Galois and closure operators, closure systems. However, up-to-date even though that different researchers actively work on mining triadic and n-ary relations, a proper closure operator for enumeration of triconcepts, i.e. maximal triadic cliques of tripartite hypergaphs, was not introduced. In this talk we show that the previously introduced operators for obtaining triconcepts are not always consistent, describe their family and study their properties. We also introduce the notion of maximal switching generator to explain why such concept-forming operators are not closure operators due to violation of monotonicity property.
A short introduction into Sequential Pattern Mining in Russia. We consider frequent and frequent closed sequences along with two algorithms (SPADE and PrefixSpan). A demographic case study is provided as well. One can find links and references to relevant literature and software. We mainly follow Han & Kamber Data Mining book (2nd edition, Chapter 8.3).
Краткое введение в Sequential Pattern Mining на русском языке. Рассматриваются алгоритмы для поиска частых и частых замкнутых последовательностей (SPADE и PrefixSpan) Кейс-стади на примере демографических последовательностей. Приведены ссылки на библиотеки и реализации некоторых базовых алгоритмов. Основное изложение по мотивам учебника Джиавея Хана и Мишелин Камбер.
NIPS 2016, Tensor-Learn@NIPS, and IEEE ICDM 2016Dmitrii Ignatov
Some photo impressions from NIPS & ICDM 2016 in Barcelona mixed with workshops like Learning with Tensors (http://tensor-learn.org/) and related stuff.
Searching for optimal patterns in Boolean tensorsDmitrii Ignatov
This is our slides for a spotlight talk at Learning with Tensors workshop at NIPS 2016. We have shortly summarise comparison of five different triclustering algorithms (TRIAS, TriBox, OACPrime, OACBox, and SpecTric).
Experimental Economics and Machine Learning workshopDmitrii Ignatov
This presentation summarises recent activities on EEML workshop organisation. In fact, this is a successful event which attracts economists and computers scientists who would like to use recent advances in machine learning and data mining to understand human behavior in different domains related to Economics and Social Science.
Pattern-based classification of demographic sequencesDmitrii Ignatov
We have proposed prefix-based gapless sequential patterns for classification of demographic sequences. In comparison to black-box machine learning techniques, this one provides interpretable patterns suitable for treatment by professional demographers. As for the language, we have used Pattern Structures as an extension of Formal Concept Analysis for the case of complex data like sequences, graphs, intervals, etc.
This paper presents an interesting idea how to compute a consensus of several k-partitions of a set by means of finding an antichain in the concept lattice of an appropriate formal context.
In our previous work an efficient one-pass online algorithm for triclustering of binary data (triadic formal contexts) was proposed. This algorithm is a modified version of the basic algorithm for OAC- triclustering approach; it has linear time and memory complexities. In this paper we parallelise it via map-reduce framework in order to make it suitable for big datasets. The results of computer experiments show the efficiency of the proposed algorithm; for example, it outperforms the online counterpart on Bibsonomy dataset with ≈ 800, 000 triples.
Context-Aware Recommender System Based on Boolean Matrix FactorisationDmitrii Ignatov
In this work we propose and study an approach for collaborative filtering, which is based on Boolean matrix factorisation and exploits additional (context) information about users and items. To avoid similarity loss in case of Boolean representation we use an adjusted type of projection of a target user to the obtained factor space.
We have compared the proposed method with SVD-based approach on the MovieLens dataset. The experiments demonstrate that the proposed method has better MAE and Precision and comparable Recall and F-measure. We also report an increase of quality in the context information presence.
Pattern Mining and Machine Learning for Demographic SequencesDmitrii Ignatov
In this talk, we present the results of our first studies in application of pattern mining and machine learning to analysis of demographic sequences in Russia based on data of 11 generations from 1930 till 1984. The main goal is not prediction and data mining methods themselves, but rather extraction of interesting patterns and knowledge acquisition from substantial datasets of demographic data. We use decision trees as techniques for demographic events prediction and emerging patterns for searching significant and potentially useful sequences.
RAPS: A Recommender Algorithm Based on Pattern StructuresDmitrii Ignatov
We propose a new algorithm for recommender systems with numeric
ratings which is based on Pattern Structures (RAPS). As the input the algorithm
takes rating matrix, e.g., such that it contains movies rated by users. For a target
user, the algorithm returns a rated list of items (movies) based on its previous ratings
and ratings of other users.We compare the results of the proposed algorithm
in terms of precision and recall measures with Slope One, one of the state-of-the-art
item-based algorithms, on Movie Lens dataset and RAPS demonstrates the
best or comparable quality.
Поиск частых множеств признаков (товаров) и ассоциативные правилаDmitrii Ignatov
Краткое введение в анализ ассоциативных правил в терминах Анализа Формальных Понятий. Примеры задач: поиск документов почти-дубликатов, анализ посещаемости сайтов, контекстная реклама.
A One-Pass Triclustering Approach: Is There any Room for Big Data?Dmitrii Ignatov
An efficient one-pass online algorithm for triclustering of binary data (triadic formal contexts) is proposed. This algorithm is a modified version of the basic algorithm for OAC-triclustering approach, but it has linear time and memory complexities with respect to the cardinality
of the underlying ternary relation and can be easily parallelized in order to be applied for the analysis of big datasets. The results of computer experiments show the efficiency of the proposed algorithm.
Boolean matrix factorisation for collaborative filteringDmitrii Ignatov
We propose a new approach for Collaborative filtering which
is based on Boolean Matrix Factorisation (BMF) and Formal Concept
Analysis. In a series of experiments on real data (MovieLens dataset) we
compare the approach with an SVD-based one in terms of Mean Average
Error (MAE). One of the experimental consequences is that it is enough
to have a binary-scaled rating data to obtain almost the same quality
in terms of MAE by BMF as for the SVD-based algorithm in case of
non-scaled data.
Online Recommender System for Radio Station Hosting: Experimental Results Rev...Dmitrii Ignatov
We present a new recommender system developed for the Russian interactive radio network FMhost based on a previously proposed model. The underlying model combines a collaborative user-based approach with information from tags of listened tracks in order to match user and radio station profiles.
It follows an adaptive online learning strategy based on the user history. We compare the proposed algorithms and an industry standard technique based on singular value decomposition (SVD)
in terms of precision, recall, and NDCG measures; experiments show that in our case the fusion-based approach shows the best results.
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Neutral nucleophiles can also add to carbonyls, although their additions are generally slower and more reversible. Acid catalysis is sometimes employed to increase the rate of addition.
BREEDING METHODS FOR DISEASE RESISTANCE.pptxRASHMI M G
Plant breeding for disease resistance is a strategy to reduce crop losses caused by disease. Plants have an innate immune system that allows them to recognize pathogens and provide resistance. However, breeding for long-lasting resistance often involves combining multiple resistance genes
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hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
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Personal Experiences of Publishing with Springer from both Editor and Author Perspectives
1. Personal Experiences of Publishing with
Springer from both Editor and Author
Perspectives
Dmitry Ignatov
Faculty of Computer Science @ HSE
Data Analysis and AI Dept. &
Intelligent Systems and Structural Analysis Lab
2. Outline
● Publishing proceedings of reputed conferences in LNCS/LNAI
series
– ICCS 2013, ICFCA 2012
– PReMI & RSFDGrC 2011
– ECIR 2013
● Young conferences and summer schools in CCIS
– AIST (since 2014)
– RuSSIR (since 2014)
● Publishing in journals
● Future prospects (EEML workshop)
3. Formal Concept
Analysis
● R. Wille, Restructuring lattice theory: An approach based on
hierarchies of concepts, 1982
● B. Ganter, R. Wille, Formale Begriffsanalyse, Springer, 1996
● B. Ganter, R. Wille, Formal Concept Analysis, Springer, 1999
● Chapter in B. Davey, H. Priestly, Introduction to Order and
Lattices, 1990.
● Chapter in G. Grätzer (Ed.), General Lattice Theory.
● Concept Data Analysis, C. Carpineto, G. Romano, 2004.
● Galois Connections and Applications, K. Denecke, M. Erné, S.
L. Wismath (Eds.), Springer Science & Business Media, 2004
13. How to Submit a Proposal?
● https://www.springer.com/gp/computer-science/lncs/editor-guidelines-for-springer-
proceedings
14. How to Submit a Proposal?
● https://www.springer.com/gp/computer-science/lncs/editor-guidelines-for-springer-
proceedings
15. AIST 2016
Mikhail Yu. Khachay
Natalia V. Loukachevitch
Valeri G. Labunets
Sergei I. Nikolenko
Alexander I. Panchenko
Konstantin V. Vorontsov
Dmitry I. Ignatov
ANALYSIS OF IMAGES, SOCIAL NETWORKS, AND
TEXTS
April, 7-9th, Yekaterinburg
THE 5th
INTERNATIONAL DATA SCIENCE CONFERENCE
16. Outline
• General facts
• Paper selection procedure & proceedings
• Sponsors and partners
• Conference program highlights
• Best paper and best poster awards
17. AIST in numbers
• AIST 2012 – 49 submissions
• AIST 2013 – 40
• AIST 2014 – 74
• AIST 2015 – 140
• AIST 2016 – 142
• AIST’16 authors & speakers: Russia – 237, Austria
– 5, Vietnam – 3 , UK – 3, Australia – 2, Norway – 2,
US – 2, France – 1, Hungary – 1, India – 1, Italy – 1,
Mexico – 1, Sweden – 1
• Are we slightly growing or just stable?
18. AIST in numbers
Section Submitted Accepted
(Springer)
Accepted
(CEUR-WS)
Data Analysis, Graphs &
Complex Data
39 7 17
Natural Language Processing 32 12 8
Analysis of Images and Video 52 11 17
Here the total number of submissions is 123, not 142 due to technical rejects of some
papers.
20. Main Volume
• Communications in Computer and Information
Science series
Series Editors: Diniz Junqueira Barbosa, S., Chen, P., Du, X.,
Filipe, J., Kara, O., Kotenko, I., Liu, T.,
Sivalingam, K.M., Washio, T. (Eds.)
CCIS is abstracted/indexed in DBLP, Google Scholar, EI-Compendex,
Mathematical Reviews, SCImago, Scopus. CCIS volumes are also submitted for
the inclusion in ISI Proceedings.
And the last two editions have been indexed in WoS.
21. Companion volume
• CEUR Workshop Proceedings (CEUR-WS.org)
Online Proceedings for Scientific Workshops
http://ceur-ws.org/Vol-1710/
see also:
Vol-1452
Vol-1197
Supplementary Proceedings of the 4th International Conference on
Analysis of Images, Social Networks and Texts (AIST-SUP 2015),
Yekaterinburg, Russia, April 9-11, 2015.
Edited by: Mikhail Yu. Khachay, Natalia Konstantinova, Alexander
Panchenko, Radhakrishnan Delhibabu, Nikita Spirin, Valeri G. Labunets
Submitted by: Nikita Spirin, Dmitry Ignatov
Published on CEUR-WS: 15-Oct-2015
ONLINE: http://ceur-ws.org/Vol-1452/
URN: urn:nbn:de:0074-1452-7
ARCHIVE:
ftp://SunSITE.Informatik.RWTH-Aachen.DE/pub/publications/CEUR-WS/
Vol-1452.zip
22. Program Committee in 2016
• 130 members
• From 28 countries: Austria, Bangladesh, Belgium, Brazil,
Croatia, Cyprus, Egypt, Estonia, Finland, France, Germany,
Greece, India, Ireland, Israel, Italy, Lithuania, Netherlands,
Norway, Portugal, Qatar, Russian Federation, Spain,
Switzerland, Ukraine, United Kingdom, United States
• From Academia: Carnegie Mellon University,
• KU Leuven, TU Eindhoven, INRIA-CNRS, HSE, UrFU,
Skoltech, TU Darmstadt, INSA Lyon…
• From Industry: IBM Research, HP Labs, Yandex, Kontur
Labs, Intel, Xerox Research Center, …
23. Conference Chairs in 2016
• Machine Learning and Pattern Recognition
– Mikhail Khachay, co-chair, IMM UB RAS & Ural Federal University,
Yekaterinburg, Russia
– Konstantin Vorontsov, co-chair, MIPT & Computer Center of RAS, Russia
• Natural Language Processing
– Natalia Loukashevitch, co-chair, Moscow State University, Russia
– Alexander Panchenko, co-chair, Technische Universität Darmstadt, Darmstadt,
Germany
• Images and Video
– Valeri Labunets, co-chair, Ural Federal University, Yekaterinburg, Russia
– Andrey Savchenko, co-chair & Proceedings Chair, Higher School of Economics,
Nizhniy Novgorod, Russia
• Data Analysis and Complex Networks
– Sergei Nikolenko, co-chair, Steklov Mathematical Institute of RAS, Higher
School of Economics, St. Petersburg, Russia
– Dmitry Ignatov, co-chair & Proceedings Chair, Higher School of Economics,
Moscow, Russia