In this dissertation, we study several Markovian problems of optimal sequential decisions by focusing on research questions that are driven by probabilistic and operations-management considerations. Our probabilistic interest is in understanding the distribution of the total reward that one obtains when implementing a policy that maximizes its expected value. With this respect, we study the sequential selection of unimodal and alternating subsequences from a random sample, and we prove accurate bounds for the expected values and exact asymptotics. In the unimodal problem, we also note that the variance of the optimal total reward can be bounded in terms of its expected value. This fact then motivates a much broader analysis that characteriz...
In this document, we give an overview of recent contributions to the mathematics of statistical sequ...
One of the goals of Artificial Intelligence (AI) is to enable multiple agents to interact, co-ordina...
This survey is focused on certain sequential decision-making problems that involve optimizing over p...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
This dissertation focuses on sequential learning and inference under unknown models. In this class o...
This volume contains the proceedings of the AMS-IMS-SIAM Joint Summer Research Conference on Strateg...
The Sequential Stochastic Assignment Problem (SSAP) deals with assigning sequentially arriving tasks...
Sequential decision making is a fundamental task faced by any intelligent agent in an extended inter...
In the first part of this dissertation, we consider two problems in sequential decision making. The ...
In this dissertation we study concentration properties of Markov chains,and sequential decision maki...
PhD ThesesThis thesis deals with several closely related, but subtly di erent problems in the area ...
In this work we consider probabilistic approaches to sequential decision making. The ultimate goal i...
Sequential decision-making is a natural model for machine learning applications where the learner mu...
We consider an extension of the classical secretary problem where a decision maker observes only the...
In this document, we give an overview of recent contributions to the mathematics of statistical sequ...
One of the goals of Artificial Intelligence (AI) is to enable multiple agents to interact, co-ordina...
This survey is focused on certain sequential decision-making problems that involve optimizing over p...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
This dissertation focuses on sequential learning and inference under unknown models. In this class o...
This volume contains the proceedings of the AMS-IMS-SIAM Joint Summer Research Conference on Strateg...
The Sequential Stochastic Assignment Problem (SSAP) deals with assigning sequentially arriving tasks...
Sequential decision making is a fundamental task faced by any intelligent agent in an extended inter...
In the first part of this dissertation, we consider two problems in sequential decision making. The ...
In this dissertation we study concentration properties of Markov chains,and sequential decision maki...
PhD ThesesThis thesis deals with several closely related, but subtly di erent problems in the area ...
In this work we consider probabilistic approaches to sequential decision making. The ultimate goal i...
Sequential decision-making is a natural model for machine learning applications where the learner mu...
We consider an extension of the classical secretary problem where a decision maker observes only the...
In this document, we give an overview of recent contributions to the mathematics of statistical sequ...
One of the goals of Artificial Intelligence (AI) is to enable multiple agents to interact, co-ordina...
This survey is focused on certain sequential decision-making problems that involve optimizing over p...