Complex networks: new trends for the analysis of brain connectivity

Today, the human brain can be studied as a whole. Electroencephalography, magnetoencephalography, or functional magnetic resonance imaging techniques provide functional connectivity patterns between different brain areas, and during different pathological and cognitive neuro-dynamical states. In this Tutorial we review novel complex networks approaches to unveil how brain networks can efficiently manage local processing and global integration for the transfer of information, while being at the same time capable of adapting to satisfy changing neural demands.Comment: Tutorial paper to appear in the Int. J. Bif. Chao

Dynamical Systems on Networks: A Tutorial

We give a tutorial for the study of dynamical systems on networks. We focus especially on "simple" situations that are tractable analytically, because they can be very insightful and provide useful springboards for the study of more complicated scenarios. We briefly motivate why examining dynamical systems on networks is interesting and important, and we then give several fascinating examples and discuss some theoretical results. We also briefly discuss dynamical systems on dynamical (i.e., time-dependent) networks, overview software implementations, and give an outlook on the field.Comment: 39 pages, 1 figure, submitted, more examples and discussion than original version, some reorganization and also more pointers to interesting direction

Neural Networks for Information Retrieval

Machine learning plays a role in many aspects of modern IR systems, and deep learning is applied in all of them. The fast pace of modern-day research has given rise to many different approaches for many different IR problems. The amount of information available can be overwhelming both for junior students and for experienced researchers looking for new research topics and directions. Additionally, it is interesting to see what key insights into IR problems the new technologies are able to give us. The aim of this full-day tutorial is to give a clear overview of current tried-and-trusted neural methods in IR and how they benefit IR research. It covers key architectures, as well as the most promising future directions.Comment: Overview of full-day tutorial at SIGIR 201

Mining local staircase patterns in noisy data

Most traditional biclustering algorithms identify biclusters with no or little overlap. In this paper, we introduce the problem of identifying staircases of biclusters. Such staircases may be indicative for causal relationships between columns and can not easily be identified by existing biclustering algorithms. Our formalization relies on a scoring function based on the Minimum Description Length principle. Furthermore, we propose a first algorithm for identifying staircase biclusters, based on a combination of local search and constraint programming. Experiments show that the approach is promising

Genetic Algorithms and Local Search

The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem

Mobile IP

The Internet is growing exponentially, both in the amount of traffic carried, and in the amount of hosts connected. IP technology is becoming more and more important, in company networks (Intranets), and also in the core networks for the next generation mobile networks. Further, wireless access to IP networks is becoming mature (e.g., IEEE 802.11 networks, Irda, Bluetooth). At the same time, the existing generation of mobile (cellular) networks is evolving from voice services to networks with a rich mixture of services (e.g., GPRS and 3rd generation networks). These developments demand for mobility in IP-based networks. A first solution to this problem has been proposed as Mobile IP. This solution makes use of Home Agents and Foreign Agents to allow mobile hosts to move freely between subnetworks while communicating.\ud \ud The tutorial will describe and explain the approaches taken to provide mobility for hosts in the Internet and IP-based networks. The tutorial will start with expanding on the need for Mobile IP. It will briefly explain the main Internet principles relevant to Mobile IP. The problems Mobile IP is trying to solve will be explained. After an overview of the general operation of Mobile IP, the principal mechanisms will be discussed in more detail. The tutorial will describe the operation of advertising care-of addresses, mobile host registration, tunneling, and proxy- and gratuitous ARP. Special attention will be paid to the main problems related to Mobile IP, such as triangle routing and smooth hand-off. The tutorial will finally explain how mobility can be supported in IPv6.\u

Viral Networks: Connecting Digital Humanities and Medical History

This volume of original essays explores the power of network thinking and analysis for humanities research. Contributing authors are all scholars whose research focuses on a medical history topic—from the Black Death in fourteenth-century Provence to psychiatric hospitals in twentieth-century Alabama. The chapters take readers through a variety of situations in which scholars must determine if network analysis is right for their research; and, if the answer is yes, what the possibilities are for implementation. Along the way, readers will find practical tips on identifying an appropriate network to analyze, finding the best way to apply network analysis, and choosing the right tools for data visualization. All the chapters in this volume grew out of the 2018 Viral Networks workshop, hosted by the History of Medicine Division of the National Library of Medicine (NIH), funded by the Office of Digital Humanities of the National Endowment for the Humanities, and organized by Virginia Tech