活动简介

The International Conference on Machine Learning and Data Science will focus on topics that are of interest to computer and computational scientists and engineers. MLDS-2018 will bring together researchers and practitioners from academia, industry and government to deliberate on the algorithms, systems, applied, and research aspects of Machine Learning and Data Science. The conference will be held in Hyderabad - Telangana, India, and will feature multiple eminent keynote speakers, and presentation of peer reviewed original research papers and exhibits.

组委会

Steering Committee

Deepak Khazanchi, University of Nebraska, USA

Suneet Tuli, Bennett University, India

Arya Kumar Bhattacharya, Mahindra École Centrale, India

Bishnu P Pal, Mahindra École Centrale, India

Yajulu Medury, Mahindra École Centrale, India

General Co-Chairs

Prafulla Kalapatapu, Mahindra École Centrale, India

Deepak Garg, Bennet University, India

Sartaj Sahni, University of Florida, USA

Program Co-Chairs

Sanjay Ranka, University of Florida, USA

Sumeet Dua, Louisiana Tech University, USA

Technical Program Committee / Advisory Committee

Louiqa Raschid, University of Maryland, USA

Cho-Yu Jason Chiang, Applied Communication Sciences, USA

Keith C. C. Chan, The Hong Kong Polytechnic University, Hong Kong

Ramin Yahyapour, GWDG - University Göttingen, Germany

David Kaeli, Northeastern University, USA

Alexey Lastovetsky, University College Dublin, Ireland

Keqin Li, State University of New York at New Paltz, USA

Sharma Chakravarthy, University of Texas, Arlington, USA

Balaji Palanisamy, University of Pittsburgh, USA

Surendra Byna, Lawrence Berkeley National Laboratory, USA

Hidemoto Nakada, National Institute of Advanced Industrial Science and Technology, Japan

Vijay Raghavan, University of Louisiana at Lafayette, USA

Ali Butt, Virginia Tech., USA

Takao Terano, Tokyo Institute of Technology, Japan

Prasenjit Mitra, The Pennsylvania State University, USA

Rajdeep Bhowmik, Cisco Systems, Inc., USA

Alfredo Cuzzocrea, ICAR-CNR and University of Calabria, Italy

Tania Banerjee, University of Florida, USA

Lorenza Saitta, Università del Piemonte Orient, Dip. di Informatica, Italy

Hai Jin, Huazhong University of Science and Technology, P.R. China

Sameh Elnikety, Microsoft Research, USA

Dimitrios Tsoumakos, Ionian University, Greece

Paolo Romano, Inesc-ID, Portugal

Pradeep Chowriappa, Louisiana Tech University, USA

Mukesh Kumar, The Technological Institute of Textile & Sciences, India

Feng Yan, University of Nevada, Reno, USA

Yanghua Xiao, Fudan University, P.R. China

Xingquan Zhu, University of Technology, Sydney, P.R. China

Alexandru Costan, INRIA Rennes, France

Andrea Clematis, CNR, Italy

Aryya Gangopadhyay, University of Maryland Baltimore County (UMBC), USA

Jay Lofstead, Sandia National Laboratories, USA

Aris Gkoulalas-Divanis, IBM Watson Health, USA

Varun Chandola, SUNY Buffalo, USA

Bing Zhu, Peking University, P.R. China

Huan Liu, Arizona State University, USA

Murali Mani, University of Michigan Flint, USA

Linlin You, Singapore University of Technology and Design, Singapore

Aswani Kumar Cherukuri, VIT University, India

Xiaoyong Yuan, University of Florida, USA

Min Li, IBM T J Watson Research, USA

Arnab Basu, Indian Institute of Management Bangalore, India

Chang-Dong Wang, Sun Yat-sen University, P.R. China

Matin Kheirkhahan, University of Florida, USA

Peng Zhang, University of Technology Sydney, P.R. China

Brandeis Marshall, Spelman College, USA

Deepak Garg, Bennett University, India

Sanjay Ranka, University of Florida, USA

Nisansa de Silva, University of Oregon, USA

Dhruv Mahajan, University of Florida, USA

Andrew Sung, University of Southern Mississippi, USA

Taskin Kavzoglu, Gebze Technical University, USA

Xiaofeng He, East China National University, USA

Dhruv Arya, LinkedIn, USA

Naeemul Hassan, University of Mississippi, USA

Patrick Emami, University of Florida, USA

Reda Al-Bahrani, Northwestern University, USA

Hatwib Mugasa, Louisiana Tech University, USA

Yang Zhou, Auburn University, USA

Chengliang Yang, University of Florida, USA

Pan He, University of Florida, USA

Xiaohui Huang, University of Florida, USA

Amnay Amimeur, University of Oregon, USA

Fernando Gutierrez, University of Concepción, Chile

Ioannis Giannakopoulos, NTUA, Greece

Ioannis Mytilinis, NTUA, Greece

Ayesha Akter, Louisiana Tech University, USA

Richard Appiah, Louisiana Tech University, USA

Zijiang Yang, Northwestern University, USA

Girish Rentala, Louisiana Tech University, USA

Andrey Timofeyev, Louisiana Tech University, USA

征稿信息

重要日期

2018-06-30
初稿截稿日期

征稿范围

Topics and Scope of the Conference

Machine Learning

Model Selection

  • Learning using Ensemble and boosting strategies
  • Active Machine Learning
  • Manifold Learning
  • Fuzzy Learning
  • Kernel Based Learning
  • Genetic Learning
  • Hybrid models

Evolutionary Parameter Estimation

  • Fuzzy approaches to parameter estimation
  • Genetic optimization
  • Bayesian estimation approaches
  • Boosting approaches to Transfer learning
  • Heterogeneous information networks
  • Recurrent Neural Networks
  • Influence Maximization
  • Co-evolution of time sequences

Graphs and Social Networks

  • Social group evolution – dynamic modelling
  • Adaptive and dynamic shrinking
  • Pattern summarization
  • Graph embeddings
  • Graph mining methods
  • Structure preserving embedding

Non-parametric models for sparse networks

  • Forecasting
  • Nested Multi-instance learning

Large scale machine learning

  • Large scale item categorization
  • Machine learning over the Cloud
  • Anomaly detection in streaming heterogeneous datasets
  • Signal analysis 
  • Learning Paradigms
    • Clustering, Classification and regression methods
    • Supervised, semi-supervised and unsupervised learning
    • Algebra, calculus, matrix and tensor methods in context of machine learning
    • Reinforcement Learning
    • Optimization methods
    • Parallel and distributed learning

Deep Learning 

  • Inference dependencies on multi-layered networks
  • Recurrent Neural Networks and its applications
  • Tensor Learning
  • Higher-order tensors
  • Graph wavelets
  • Spectral graph theory
  • Self-organizing networks 
  • Multi-scale learning
  • Unsupervised feature learning 

Recommender Systems

  • Automated response
  • Conversational Recommender systems
  • Collaborative deep learning
  • Trust aware collaborative learning
  • Cold-start recommendation systems
  • Multi-contextual behaviours of users

Applications

  • Bioinformatics and biomedical informatics
  • Healthcare and clinical decision support
  • Collaborative filtering
  • Computer vision
  • Human activity recognition
  • Information retrieval
  • Cybersecurity
  • Natural language processing
  • Web search

Evaluation of Learning Systems

  • Computational learning theory
  • Experimental evaluation
  • Knowledge refinement and feedback control
  • Scalability analysis
  • Statistical learning theory
  • Computational metrics

Data Science

  • Algorithms
  • Novel Theoretical Modelsp
  • Novel Computational Models
  • Data and Information Quality
  • Data Integration and Fusion
  • Cloud/Grid/Stream Computing
  • High Performance/Parallel Computing
  • Energy-efficient Computing
  • Software Systems
  • Search and Mining
  • Data Acquisition, Integration, Cleaning
  • Data Visualizations
  • Semantic-based Data Mining
  • Data Wrangling, Data Cleaning, Data Curation, Data Munching
  • Data Analysis, , Statistical Insights
  • Decision making from insights, Hidden patterns
  • Data Science technologies, tools, frameworks, platforms and APIs
  • Link and Graph Mining
  • Efficiency, scalability, security, privacy and complexity issues in Data Science
  • Labelling, Collecting, Surveying, Interviewing and other tools for Data Collection
  • Applications in Mobility, Multimedia, Science, Technology, Engineering, Medicine, Healthcare, Finance, Business, Law, Transportation, Retailing, Telecommunication

作者指南

Authors are requested to submit their file in the format specified in the IEEE Paper Template Prospective authors are invited to submit original technical papers for publication in the ICMLDS 2018 Important IEEE Policy Announcement The IEEE reserves the right to exclude a paper from distribution after the conference (including its removal from IEEE Xplore) if the paper is not presented at the conference. Papers are reviewed on the basis that they do not contain plagiarised material and have not been submitted to any other conference at the same time (double submission). These matters are taken very seriously and the IEEE will take action against any author who engages in either practice. 
To be submitted in IEEE Xplore for consideration, an author of an accepted paper is required to register for the conference and present the paper at the conference. Non-refundable registration fees must be paid prior to the due date of registration. For authors with multiple accepted papers, one registration for each paper is required Paper Submission Prospective authors are invited to submit papers of four (4) to eight (8) A4 pages (including tables, figures and references) in standard IEEE double-column format (it is absolutely necessary to respect the Styleguide for Papers). A blind peer-review process will be used to evaluate all submitted papers. Each full registration for the conference will cover a maximum of one paper; each student registration will cover a single paper only. Extra paper, 2nd paper and onwards, must be registered separately. The format instructions in the template must be followed, it is notably important to use the right paper format: A4 to have the right margins not to use page numbering (page footer must be empty)
The IEEE Citation Reference may help you with the references in your paper. Get the list of IEEE recommended keywords from https://www.ieee.org/documents/taxonomy_v101.pdf or send an empty e-mail to keywords@ieee.org with "IEEE Keywords" in the subject line.
All submissions should be written in English with a maximum paper length of eight (8) printed pages including figures, without incurring additional page charges. One (1) additional page is allowed with a charge of USD 20 or INR 500, if accepted

留言
验证码 看不清楚,更换一张
全部留言
重要日期
  • 会议日期

    12月21日

    2018

    12月22日

    2018

  • 06月30日 2018

    初稿截稿日期

  • 12月22日 2018

    注册截止日期

联系方式
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询