Michael Christoph Gastpar

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Compute-and-Forward is an emerging technique to deal with interference. It allows the receiver to decode a suitably chosen integer linear combination of the transmitted messages. The integer coefficients should be adapted to the channel fading state. Optim ...

We prove that every online learnable class of functions of Littlestone dimension d admits a learning algorithm with finite information complexity. Towards this end, we use the notion of a globally stable algorithm. Generally, the information complexity of ...

The Karhunen-Loeve transform is a key element of many signal processing tasks, including classification and compression. In this paper, we consider distributed signal processing scenarios with limited communication between correlated sources, and we investigate a distributed Karhunen-Loeve transform (KLT). In particular, a partial KLT (where only a subset of sources are observed) and a conditional KLT (where some sources act as side information) are posed and solved in a rate-distortion sense. The partial K

High-order phenomena are pervasive across complex systems, yet their formal characterisation remains a formidable challenge. The literature provides various information-theoretic quantities that capture high-order interdependencies, but their conceptual fo ...

We consider a setup in which confidential i.i.d. samples X1, . . . , Xn from an unknown finite-support distribution p are passed through n copies of a discrete privatization chan- nel (a.k.a. mechanism) producing outputs Y1, . . . , Yn. The channel law gua ...

Successive refinement is a technique to encode a source iteratively, improving the distortion at each step. If the code rates of all steps combined can be as efficient as coding only for the final distortion in one go, then the source is said to be success ...

Shannon's separation theorem gives a conceptually and practically appealing way to construct an optimal communication system in two independent steps, namely source compression and channel coding. However, sometimes it is worth considering {\em joint} source/ channel coding instead. In fact, for certain source/channel pairs, not using any code at all already achieves the optimum performance. For a larger class

{\mathbb S}

of source/channel pairs, there exists a single-letter code with optimal performance.

Providing adaptive shared control for Brain- Computer Interfaces (BCIs) can result in better performance while reducing the user’s mental workload. In this respect, online estimation of accuracy and speed of command delivery are important factors. This stu ...

Compute–forward is a coding technique that enables receiver(s) in a network to directly decode one or more linear combinations of the transmitted codewords. Initial efforts focused on Gaussian channels and derived achievable rate regions via nested lattice ...

Despite significant progress in the caching literature concerning the worst case and uniform average case regimes, the algorithms for caching with nonuniform demands are still at a basic stage and mostly rely on simple grouping and memory-sharing technique ...

In this work, we consider the problem of parameter estimation in a Bayesian setting. We propose a new approach to lower-bounding the Bayesian risk, based on Sibson's alpha-Mutual Information. The results are then applied to specific settings of interest. A ...

Consider the important special case of the K-user distributed source coding problem where the decoder only wishes to recover one or more linear combinations of the sources. The work of Körner and Marton demonstrated that, in some cases, the optimal rate re ...

The Compute-and-Forward approach has been proven to be very beneficial for communication over Gaussian networks. While the theoretical results are promising, it is still not completely understood how to best apply this scheme in practice. The objective of this work is to provide a low complexity scheme suitable for Compute-and-Forward. The scheme is based on utilizing linear codes over ℤq where q is not restricted to be prime and allows to achieve high transmission rates following Ungerboeck's set partition

In wireless sensor networks, various applications involve learning one or multiple functions of the measurements observed by sensors, rather than the measurements themselves. This paper focuses on the computation of type-threshold functions which include t ...

We study the problem of coded caching when the server has access to several libraries and each user makes independent requests from every library. The single-library scenario has been well studied and it has been proved that coded caching can significantly ...

Lattice codes used under the compute-and-forward paradigm suggest an alternative strategy for the standard Gaussian multiple-access channel (MAC): the receiver succes- sively decodes the integer linear combinations of the messages until it can invert and r ...

This paper focuses on parameter estimation and introduces a new method for lower bounding the Bayesian risk. The method allows for the use of virtually any information measure, including Rényi's α, φ-divergences, and Sibson's α-Mutual Information. The appr ...

An information-theoretic lower bound is developed for the caching system studied by Maddah-Ali and Niesen. By comparing the proposed lower bound with the decentralized coded caching scheme of Maddah-Ali and Niesen, the optimal memory--rate tradeoff is char ...

We consider the cooperative data exchange problem, in which nodes are fully connected with each other. Each node initially only has a subset of the K packets making up a file and wants to recover the whole file. Node i can make a broadcast transmission, wh ...

The theory and practice of digital communication during the past 50 years has been strongly influenced by Shannon's separation theorem. While it is conceptually and practically appealing to separate source from channel coding, either step requires infinite delay in general for optimal performance. On the other extreme is uncoded transmission, which has no delay but is suboptimal in general. In this paper, necessary and sufficient conditions for the optimality of uncoded transmission are shown. These conditi

Michael Christoph Gastpar

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Compute-and-Forward: Finding the Best Equation

Finite Littlestone Dimension Implies Finite Information Complexity

The distributed Karhunen-Loeve transform

Characterising high-order interdependence via entropic conjugation

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Successive Refinement of Gaussian Projections

On optimal low-complexity source/channel coding

Real-time Prediction of Fast and Slow Delivery of Mental Commands in a Motor Imagery BCI: An Entropy-based Approach

A Unified Discretization Approach to Compute–Forward: From Discrete to Continuous Inputs

A Novel Centralized Strategy for Coded Caching with Non-uniform Demands

Lower-bounds on the Bayesian Risk in estimation procedures via Sibson's alpha-Mutual Information

Towards an Algebraic Network Information Theory: Distributed Lossy Computation of Linear Functions

Practical code design for compute-and-forward

Multi-round computation of type-threshold functions in collocated Gaussian networks

Multi-Library Coded Caching

Gaussian Multiple Access via Compute-and-Forward

Lower Bounds on the Bayesian Risk via Information Measures

A New Converse Bound for Coded Caching

Cooperative Data Exchange with Weighted Cost based on d-Basis Construction

To code or not to code