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Browse College of Engineering by Contributor "Raginsky, Maxim"
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(20140530)The thesis addresses a problem in networked control systems where quantization is a communication constraint. Control design together with parameter estimation algorithms lead to adaptive control techniques. A first order ...
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(20181203)Blind linear system identification (or recovery) arises in several applications in engineering (e.g. channel equalization, superresolution, MRI and SAR image formation). This is a special case of a bilinear inverse ...
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(201805)This thesis analyzes the Bayesian control law for adaptive control proposed by Ortega and Braun. The problem of concern is as follows: Assume the agent is put into an unknown environment that is sampled from certain ...
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(20151204)Artificial Intelligence (AI) has been a source of great intrigue and has spawned many questions regarding the human condition and the core of what it means to be a sentient entity. The field has bifurcated into socalled ...
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(20150121)This thesis introduces a framework of channel emulation. An emulator is defined as a pair of channels, that converts one channel to another channel with possibly different input and output alphabets. With the concept of ...
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(20140916)The thesis focuses on a few fundamental problems in multiplayer dynamic sequential decision problems  games and teams  with asymmetric information. It is divided into two parts and addresses six broad theoretical ...
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(20180709)A distributed system is composed of independent agents, machines, processing units, etc., where interactions between them are usually constrained by a network structure. In contrast to centralized approaches where all ...
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(20120918)How does uncertainty affect a robot when attempting to generate a control policy to achieve some objective? How sensitive is the obtained control policy to perturbations? These are the central questions addressed in this ...
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(20150121)This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the wellknown distributed averaging dynamics. The second ...
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(20161130)In a generic distributed information processing system, a number of agents connected by communication channels aim to accomplish a task collectively through local communications. The fundamental limits of distributed ...
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(20140530)Nextgeneration embedded devices are expected to pervasively extract information from the world around us. In particular, growing interest in mobile devices beyond the smart phone imply that the need for context awareness ...
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(20150421)Algorithms on graphs are used extensively in many applications and research areas. Such applications include machine learning, artificial intelligence, communications, image processing, state tracking, sensor networks, ...
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(20151204)This thesis studies MMSE estimation on the basis of quantized noisy observations. It presents nonasymptotic bounds on MMSE regret due to quantization for two settings: (1) estimation of a scalar random variable given a ...
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(20190128)In this dissertation, a circuit modeling methodology using recurrent neural networks (RNNs) is developed. The methodology covers model structure selection, data generation, training, and model implementation for circuit ...
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(20150518)We propose a novel group testing framework, termed semiquantitative group testing, motivated by a class of problems arising in genome screening experiments in addition to other applications such as interpretable rule ...
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(20180904)Recent advances in genetics, computer vision, and text mining are accompanied by analyzing data coming from a large domain, where the domain size is comparable or larger than the number of samples. In this dissertation, ...
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(20150121)This thesis poses a general model for optimal control subject to information constraint, motivated in part by recent work on informationconstrained decisionmaking by economic agents. In the averagecost optimal control ...
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(20190225)Rationally inattentive decisionmaking (RIDM) extends general problem of Bayesian decisionmaking under uncertainty to the case when the decision maker (DM) has several options for obtaining extra information about the ...
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(20171203)We investigate robustness and reliability in decisionmaking systems and algorithms based on the tradeoff between cost and performance. We propose two abstract frameworks to investigate robustness and reliability concerns, ...
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(20190115)We apply tools from the classical statistical learning theory to analyze theoretical properties of modern machine learning problems that are typically phrased in the context of generative models. By combining standard ...
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Now showing items 120 of 22