Probabilistic graphical models are a powerful concept for modeling high-dimensional distributions. Besides modeling distributions, probabilistic graphical models also provide an elegant framework for performing statistical inference; because of the high-dimensional nature, however, one must often use approximate methods for this purpose. Belief propagation performs approximate inference, is efficient, and looks back on a long success-story….
The first part of this dissertation considers distributed learning problems over networked agents. The general objective of distributed adaptation and learning is the solution of global, stochastic optimization problems through localized interactions and without information about the statistical properties of the data. Regularization is a useful technique to encourage or enforce structural properties on the…
This thesis addresses security and privacy problems for digital devices and biometrics, where a secret key is generated for authentication, identification, or secure computa- tions. A physical unclonable function (PUF) is a promising solution for local security in digital devices. A low-complexity transform-coding algorithm is developed to make the information-theoretic analysis tractable and motivate a…
The necessity to process signals living in non-Euclidean domains, such as signals de- fined on the top of a graph, has led to the extension of signal processing techniques to the graph setting. Among different approaches, graph signal processing distinguishes it- self by providing a Fourier analysis of these signals. Analogously to the Fourier transform…
We are in the middle of the digital era, with more and more amazing features becoming available even in entry-level consumer devices (smartphones, tablets, wearable devices such as smart watches, etc.). This pervasive almost ubiquitous availability of interconnected devices, unconceivable until only a decade ago, is opening the doors to unprecedented applications, for which location…
Recommender systems provide recommendations about various products and services to their users by using other users? data. These systems depend on personal user preferences on items via ratings and recommend items based on choices of similar users. Their success is imperative for both users and the e-commerce vendors utilizing such systems. Since inaccurate and unreliable…
Wireless sensor networks (WSNs) is a technology with important developments in recent years. Its incursion in areas such as healthcare, industry and services has been steadily increasing, mainly due to the miniaturization of electronics and the growing acceptance of cyber-physical systems. However, a very important subject of research continues to be the development of estimators…
Never before has speech been captured as often by electronic devices equipped with one or multiple microphones, serving a variety of applications. It is the key aspect in digital telephony, hearing devices, and voice-driven human-to-machine interaction. When speech is recorded, the microphones also capture a variety of further, undesired sound components due to adverse acoustic…
The brain is the substrate of a complex dynamic system providing a remarkably varied range of functionalities, going from simple perception to higher-level cognition. Disturbances in its complex dynamics can cause an equally vast variety of mental disorders. One such brain disorder is schizophrenia, a neurodevelopmental disease characterized by abnormal perception of reality that manifests…
SoftCast based Linear Video Coding (LVC) schemes have been emerged in the last decade as a quasi analog joint-source-channel alternative to classical video coding schemes. Theoretical analyses have shown that analog coding is better than digital coding in a multicast scenario when the channel signal-to-noise ratios (C-SNR) differ among receivers. LVC schemes provide in such…
