Title : Approximate Bayesian inference & model learning using particle filtering
Speaker : Saikat Saha, Linkoping University, Sweden
Time and Date : 4:00 pm, January 24, 2011
Title: Fast Convergence of Natural Dynamics in Bargaining Networks
Time: 3.30 pm, 7/1/11
Venue: Room 217, Mechanical Engg. Building
IEOR announces the following seminar. The details are as follows:
Title: The Concert Queuing Game: To Wait or To be Late
Speaker: Prof. Sandeep Juneja, TIFR, Bombay
Venue: Room 217, Mechanincal Engineering Building,
Time and Date: 11.30AM, 4th November, 2010.
Title: Binary code upper bounds based on semidefinite programming and
explicit block diagonalization.
Speaker: Prof. Murali. K. Srinivasan, Mathematics, IITB
Time: 3.15pm, 22/10/10, Friday
Venue: 208, First floor, Mech Engg. Building
Industrial Engineering and Operations Research - seminar announcement
Title of talk: When do IT Investments Pay? Proposal for a way ahead in strategic ICT projects
Speaker: Dr Siddhartha Sengupta (Principal Scientist & Head, TCS Innovation Labs Complex Decision Support Systems Group)
Date and time: Wednesday, 22 September, 2010, 4 p.m.
Title: Digital Engineering Visualization in Automotive Product Creation Processes
Speaker: Dr. Reinhold Klass (Mercedes-Benz Research and Development India)
Seminar on 27th August, 2010, Friday, at 3.00 p.m.
Venue: Room 217, Mechanical Engg Department
Prof Mokshay Madiman, Yale University, will be giving a IEOR Seminar on this friday, 27th August at 16.15PM.
Topic: Fundamental Limits of Distributed Estimation and Multiuser Information-Theoretic Games
Abstract: The first part of the talk focuses on fundamental limits of distributed estimation, motivated by a toy model for sensor networks. In distributed estimation, it is of interest to relate the minimax risks of estimating a parameter for users who have
Title: Bivariate exponential distribution: Properties, Estimation and Applications.
Speaker: Prof Alladi Subramanyam, Mathematics, IITB
Time: 4pm, 20/8/10
Venue: 217, Mech Engg. Building
Abstract: The Pickands bivariate exponential distribution is first defined. The distribution is characterised by a function, say A(\cdot),
called the dependence function (along with the marginal means). One may specify a parametric model for A or take A itself as a parameter.
Title: How can data mining help to understand what makes an optimization problem hard, which algorithm will perform best, and why?
Speaker: Prof Kate Smith-Miles, School of Mathematical Sciences, Monash University, Australia
Date and venue: Tuesday, 17 August, 4 p.m., Room 205, Mechanical Engineering Department
Abstract: