About the Information Theory Society
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Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt.Upcoming Events
IEEE International Symposium on Information Theory (ISIT) 2024
Ottawa, ON, Canada
IEEE North American School of Information Theory (NASIT) 2024
IEEE East Asian School of Information Theory (EASIT) 2024
Deadline Extension: IEEE-ITW'24
2024 IEEE Information Theory Workshop (ITW)
IEEE International Symposium on Information Theory (ISIT) 2025
News
Recipients of the 2024 IEEE Communication Society and Information Theory Society Joint Paper Award: Justin Singh Kang and Wei Yu
The Joint Paper Award recognizes outstanding papers that lie at the intersection of communications…
2024 James L. Massey Research & Teaching Award for Young Scholars awarded to Flavio du Pin Calmon
The James L. Massey Research & Teaching Award for Young Scholars recognizes outstanding…
2024 Thomas M. Cover Dissertation Award awarded to Sophie H. Yu
The Thomas M. Cover Dissertation Award award is granted annually to the author of an outstanding…
Call for nominations for the next Editor-in-Chief of the IEEE Journal on Selected Areas in Information Theory (JSAIT)
The JSAIT Steering Committee requests nominations for the next EiC with deadline June 15, 2024.
Conferences
BOG Meeting - Hybrid Meeting @ ISIT 2024, Athens, Greece
This will be a hybrid meeting in person room and on zoom in conjunction with ISIT 2024.
ISIT Workshop: NeurIT: Information theory in neuroscience and neuroengineering CFP
Neuroscience + Neuroengineering + IT = new theory and revolutionary applications.
…
ISIT 2024 Workshop on Information-Theoretic Methods for Trustworthy Machine Learning
The ISIT 2024 Workshop on Information-Theoretic Methods for Trustworthy Machine Learning is…
Jobs
Postdoctoral Research Associate Position on Quantum Information and Security at King's College London
Postdoctoral Researcher position at the Technical University of Munich
The TUM chair of communications engineering has an opening for a post-doc position at the…
Postdoc position in machine learning over wireless networks
Join Prof. Durisi's team at Chalmers (Gothenburg, Sweden) as a postdoc, to work on an exciting…
Call to Action
IEEE BITS the Information Theory Magazine
IEEE BITS the Information Theory Magazine publishes content that includes tutorials and review articles, historical surveys, and columns. The tutorial and review articles cover both traditional and emerging areas associated with Information Theory research and are written in a style accessible to readers outside the specialty of the article. The historical surveys are intended to highlight technological advances of current interest that have been significantly impacted by past Information Theory research.
Recent Journal Issues
IEEE Journal on Selected Areas in Information Theory
The IEEE Transactions on Information Theory publishes papers concerned with the transmission, processing, and utilization of information.
Videos on Information Theory
Research In Information Theory
Shannon, Euler, and Mazes
One of Claude Shannon’s best remembered “toys” was his maze-solving machine, created by partitions on a rectangular grid. A mechanical mouse was started at one point in the maze with the task of finding cheese at another point. Relays under the board guided successive moves, each of which were taken in the first open counterclockwise direction from the previous move. In belated honor of Shannon’s centenary and of amnesia in the mouse at age 70, we compare this deterministic search strategy with ...
6G: The Personal Tactile Internet—And Open Questions for Information Theory
The initial vision of cellular communications was to deliver ubiquitous voice communications to anyone anywhere. In a simplified view, 1G delivered voice services for business customers, and only 2G for consumers. Next, this also initiated the appetite for cellular data, for which 3G was designed. However, Blackberry delivered business smartphones, and 4G made smartphones a consumer device. The promise of 5G is to start the Tactile Internet, to control real and virtual objects in real-time via c...
Function Load Balancing Over Networks
Using networks as a means of computing can reduce the communication flow over networks. We propose to distribute the computation load in stationary networks and formulate a flow-based delay minimization problem that jointly captures the costs of communications and computation. We exploit the distributed compression scheme of Slepian-Wolf that is applicable under any protocol information. We introduce the notion of entropic surjectivity as a measure of function’s sparsity and to understand the li...
Reed–Muller Codes: Theory and Algorithms
Reed-Muller (RM) codes are among the oldest, simplest and perhaps most ubiquitous family of codes. They are used in many areas of coding theory in both electrical engineering and computer science. Yet, many of their important properties are still under investigation. This paper covers some of the recent developments regarding the weight enumerator and the capacity-achieving properties of RM codes, as well as some of the algorithmic developments. In particular, the paper discusses the recent conn...
Deep Neural Network Approximation Theory
This paper develops fundamental limits of deep neural network learning by characterizing what is possible if no constraints are imposed on the learning algorithm and on the amount of training data. Concretely, we consider Kolmogorov-optimal approximation through deep neural networks with the guiding theme being a relation between the complexity of the function (class) to be approximated and the complexity of the approximating network in terms of connectivity and memory requirements for storing t...
Quantum Blahut-Arimoto Algorithms
We generalize alternating optimization algorithms of Blahut-Arimoto type to the quantum setting. In particular, we give iterative algorithms to compute the mutual information of quantum channels, the thermodynamic capacity of quantum channels, the coherent information of less noisy quantum channels, and the Holevo quantity of classical-quantum channels. Our convergence analysis is based on quantum entropy inequalities and leads to a priori additive eps-approximations after O(eps^(-1)*log N) iter...
A Universal Low Complexity Compression Algorithm for Sparse Marked Graphs
Many modern applications involve accessing and processing graphical data, i.e. data that is naturally indexed by graphs. Examples come from internet graphs, social networks, genomics and proteomics, and other sources. The typically large size of such data motivates seeking efficient ways for its compression and decompression. The current compression methods are usually tailored to specific models, or do not provide theoretical guarantees. In this paper, we introduce a low-complexity lossless com...
Asymptotics of MAP Inference in Deep Networks
Deep generative priors are a powerful tool for reconstruction problems with complex data such as images and text. Inverse problems using such models require solving an inference problem of estimating the input and hidden units of the multi-layer network from its output. Maximum a priori (MAP) estimation is a widely-used inference method as it is straightforward to implement, and has been successful in practice. However, rigorous analysis of MAP inference in multi-layer networks is difficult. Thi...
Channel Coding Techniques for Network Communication
Next-generation wireless networks aim to enable order-of-magnitude increases in connectivity, capacity, and speed. Such a goal can be achieved in part by utilizing larger frequency bandwidth or by deploying denser base stations. As the number of wireless devices is exploding, however, it is inevitable that multiple devices communicate over the same time and same spectrum. Consequently, improving the spectral efficiency in wireless networks with multiple senders and receivers becomes the key chal...
Distinguished Lecturers
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IEEE International Symposium on Information Theory (ISIT) 2024
Ottawa, ON, Canada