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09:30 to 10:20 |
Souvik Dhara (Purdue University, USA) |
Modern methods in Network Science - I |
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10:30 to 11:20 |
Souvik Dhara (Purdue University, USA) |
Modern methods in Network Science - II |
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14:10 to 14:30 |
Ananya Lahiri (IIT Tirupati, India) |
Dynamic portfolio optimization using extreme value theory We will discuss a methodology for dynamic portfolio optimization while accessing extreme value behaviors of stocks in the portfolio and its limitations. In the talk we will focus the future opportunities based on a work jointly done with MS student Sushhma from IISER Tirupati.
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14:30 to 14:50 |
Krishanu Maulik (ISI Kolkata, India) |
Berry-Esseen bounds for two colour urns We shall consider Berry-Esseen bounds for the normal limits in case of subcritical and critical two colour urns. We shall compare the bounds when the replacement matrix is doubly stochastic with the case when it is only balanced. This is joint work with Aritra Majumdar.
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16:30 to 16:50 |
Vivek Borkar (IIT Bombay, India) |
In search of Markov solutions The talk will describe some recent work with Anugu Sumith Reddy and K. Suresh Kumar on an alternative approach to selecting a Markov solution for degenerate diffusions using small noise limits.
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16:50 to 17:10 |
Manikandan Rangaswamy (Central University of Kerala, Kasaragod, India) |
Comparisons between Parallel and Series Models in a Reliability-Queueing-Inventory System- a Concise Discussion In this talk, we consider an integrated Reliability-Queueing-Inventory (RQI) system; and briefly discuss a comparative study between a parallel system (Model I) and a series system (Model II) concerning the repair and replenishment of failed components. These systems are composed of inde- pendent and identical components. In Model I, we investigate a parallel system (1-out-of-n: G), where the repair of failed components precedes the placing of the replenishment order. Failed components form a queue awaiting for repair, where the repair starts when the number of operational components reaches L (L < n). Upon further reduction to N (N < L), an order of n units is placed for replenishment. Whereas, in Model II, we analyze a series system (n-out-of-n: G), assuming that repair commences immediately when the number of working components decreases to n−1. Here, the replenishment order ensures precisely n operational and 1 spare components in the system. We explicitly derive the steady-state probabilities using Chapman-Kolmogrov difference-differential equations. Various key performance measures are calculated for both models, facilitating a comprehensive comparison to determine the most reliable system. Optimization problems are thoroughly explored, with achieved results facilitating the identification of the model that optimally balances reliability and cost efficiency.
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17:10 to 17:30 |
Anand Deo (IIM Bengaluru, India) |
Efficient Importance Scenario Generation for Optimisation with Rare Events |
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