Track in
June 16-18, 2021, Krakow, Polland
Our time could be defined as the age of Data. With the availability of large amount of data and massive computational resources, the main challenge before data scientists is to get insightful information from the data. Naturally, AI (Artificial Intelligence) and ML (Machine Learning) are two main vehicles in getting the insights. The main type of recently available data is indeed a new, modern and unprecedented form of data. “Modern Data” has unique characteristics such as, extreme sparsity, high correlation, high dimensionality and massive size. Modern data is very prevalent in all different areas of science such as Medicine, Environment, Finance, Marketing, Vision, Imaging, Text, Web, etc.
A major difficulty in dealing with modern data is that many of the old methods that have been developed for analyzing data during the last decades cannot be applied directly to modern data. One major solution, to overcome this challenge, is to effectively use ensemble methods such as deep artificial neural networks. These types of ensemble models are heavily reliant on the deployment of efficient computational methods. Thus, it's even more imperative to deploy faster, more accurate and robust computational techniques for AI and ML models.
This track covers the application of computational methods for Artificial Intelligence and Machine Learning models.
Cybersecurity
Theoretical Aspects of AI and Machine Learning
History of Computational Methods in AI and ML
Deep Learning
Auto ML
Computer Vision
Video-to-Video Synthesis
NLP and NLU (Text Analytics)
Automatic Speech Recognition (ASR)
Matrix Factorization Methods
Recommender Systems
Computational Cognition
Computational Finance
Singular Value Decomposition in “Modern Data”
Dimension Reduction and Feature Learning
AI Conversational Assistant
Biostatistics and Computational Biology
AI in Health Science
Kourosh Modarresi (Sr Principal AI Research Scientist, Trend Micro)
kouroshm@alumni.stanford.edu
Meeting sessions co-chair:
Raja P Velu (Syracuse University)
Paul Hofmann (Accenture)
Ram Akella (UC Santa Cruz)
Michael Burkhart (Adobe)
Jamie Diner (Discovery)
David Gal (UIC)
Walter Gander (ETH)
Susanne Halstead (Apple)
Paul Hofmann (Accenture)
Tze L Lai (Stanford University)
Roy Lettieri (CPG IND)
Ajaykumar Rajasekharan (Avero)
Ulises Robles (Salesforce)
Diana Sima (Icometrix)
Bongwon Suh (Seoul National University)
Ray Sun (Google)
Zaid Tashman (Accenture)
Ka Wai Tsang (The Chinese University of Hong Kong)
Raja P Velu (Syracuse University)
Peter Woehrmann (Stanford University)
Yoshifumi Yamamoto (Guidewire)
Submit your paper via Easychair
Submission deadline is February 12, 2021. Please submit a short abstract now to indicate your interest.
"Authors are invited to submit manuscripts reporting original, unpublished research and recent developments in Computational Sciences. All accepted papers will be included in the Springer Lecture Notes in Computer Science (LNCS) series and indexed by Scopus, EI Engineering Index, Thomson Reuters Conference Proceedings Citation Index (included in ISI Web of Science), and several other indexing services. The papers will contain linked references, XML versions and citable DOI numbers.."
"You may select either a “Full/Short Paper” or a “Abstract Only” publication. By default, it would be an oral presentation. If you prefer to present a poster, please check the “Poster Presentation” option in the submission page. While we encourage full paper submissions, the “Abstract Only” option caters to researchers who can only publish in specific journals or work for companies in circumstances such that they cannot publish at all, but still want to present their work and discuss it with their peers at ICCS. In the “Abstract Only” option, a short abstract is published in a book of abstracts, but not in LNCS. "
"The manuscripts of up to 14 pages, written in English and formatted according to the Springer LNCS templates, should be submitted electronically via EasyChair. You also have the option of submitting a short paper of up to 7 pages. Both Full and Short Papers use the same templates and are published in LNCS.
The most recent versions of the Templates are available for download from this link.
The LaTeX2e Proceedings Templates are also available in the scientific authoring platform Overleaf.
Please also make sure to follow Springer’s authors’ guidelines.
Papers must be based on unpublished original work and must be submitted to ICCS only. Submission implies the willingness of at least one of the authors to register and present the paper."
Deadlines for draft paper submission, notification of acceptance, camera-ready paper submission and registration may be found in the "Important Dates" section below.
Please submit your paper via the conference website at Easychair . Do Not Forget to select the "Applications of Computational Methods in Artificial Intelligence and Machine Learning" track when submitting. "
Paper submission: 12 February 2021 (Final Extension)
Notification to authors: 15 March 2021
Camera-ready papers: 5 April 2021
Author registration: 15 March – 5 April 2021
Non-author early registration: 15 March – 23 April 2021
Non-author late registration: from 24 April 2021
Conference sessions: 16-18 June 2021