Dear Sir

Please disseminate the following information to the Petri net community.
http://www.icmla-conference.org/icmla15/#

Regards



*Call of papers in the Special Session on:*

*Formal Modeling for Machine Learning Techniques*

*************************************************

*The 14th International Conference on Machine Learning and Applications
(ICMLA'15)*

*Miami, Florida, USA (*http://www.icmla-conference.org/icmla15/#)



Formal methods can simplify the tasks of creating and understanding complex
systems, with concomitant improvements in quality and correctness. Formal
methods have been proved useful in a number of computing sub disciplines.
Indeed, the methods and tools of relevance to modeling and verification of
systems have been studied and developed in various areas: formal approaches
have been recognized to handle the distributed as well as concurrent
scenarios and they are well suited for modeling dynamic systems which have
components working in parallel and in an asynchronous way.

The proposed special session will play an important role in transferring
knowledge in the areas, especially relevant to the research topics, such as
machine learning and intelligent techniques about data and information
fusion, multiple classifier and prediction systems, formal modeling,
modelling and processing of uncertainty in pattern recognition and decision
support systems. Formal approaches can be extended for building models of
cognition for applications in inexact reasoning, learning, refinement of
knowledge and control and co-ordination of tasks.

This special session invites submissions from those working in areas of
formal modeling and verification of machine learning algorithms, systems
and applications. This special session is related to the use of formal
methods in the following topics:

·         knowledge management,

·         Petri nets for Machine Learning

·         brokering & directory services,

·         relaxed transactions and workflows,

·         concurrent O-O & actor programming,

·         mobile computing,

·         business process management,

·         information retrieval,

·         filtering, & browsing,

·         resource discovery,

·         Predictive Modeling and Optimization,

·         Pattern Recognition and Classification,

·         Regression and Forecasting,

·         Models of Data and Measurements,

·         Feature Selection, Soft Computing,

·         Learning Theory.



*Special Session Organizers: *

*1.     **Dr. Farooq Ahmad, Department of Computer Sciences, COMSATS
Institute of Information Technology, Lahore, Pakistan. *

*Email: [email protected] <[email protected]>*



 *2.     **Prof. Sher Afzal Khan, Faculty of Computing and Information
Technology in Rabigh, King Abdul Aziz University Jeddah, KSA,*

*Email: [email protected] <[email protected]>*





*Program Committee members:*



·         Prof. Hejiao Huang, Department of Computer Science and
Technology, Harbin Institute of Technology Shenzhen Graduate School, China

·         Dr. Norma Alias (UTM), Malaysia

·         Prof. Dr. Jose C. Valverde, University of Castilla-La Mancha,
Albacete, SPAIN

·         Prof. Daojing He, Software Engineering Institute, East China
Normal University, Shanghai, China

·         Dr Muhammad Khair Bin Nordin, UTM, Malaysia

·         Dr. Adnan Abid, University of Management and Technology, Lahore,
Pakistan

·         Rana Muhammad Ajmal, COMSATS Institute of Information Technology,
Lahore, Pakistan

·         Dr. Usama Ijaz Bajwa, COMSATS Institute of Information
Technology, Lahore, Pakistan

·         Dr. Ashiq Anjum, University of Derby, UK

·         Dr. Xu Jun, Harbin Institute of Technology, Shenzhen, China.

·         Dr. Selami Yangin, Recep Tayyip Erdogan, University Rize, Turkey

·         Dr. Ümit DENİZ, Department of Mathematics- RTEU Turkey


-- 
*Dr. Farooq Ahmad*
Associate Professor

Cell # +92-332-4655020



-- 
*Dr. Farooq Ahmad*
Associate Professor FIT, UCP
1 - Khayaban-e-Jinnah Road, Johar Town, Lahore, Pakistan
Phone office: +92-42-35880007 Ext. 165
Cell # +92-332-4655020
----
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