Michael Christoph Gastpar

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When a delivery agency persuades a bicycle courier worker to accept a certain job, it does so by revealing the right amount and kind of information. The goal is to reward both the agent as well as the worker accordingly. In this paper, we model the act of ...

Inspired by the compute-and-forward scheme from Nazer and Gastpar, a novel multiple-access scheme introduced by Zhu and Gastpar makes use of nested lattice codes and sequential decoding of linear combinations of codewords to recover the individual messages ...

Sibson's α-mutual information has received renewed attention recently in several contexts: concentration of measure under dependence, statistical learning, hypothesis testing, and estimation theory. In this work, we introduce several variational representa ...

The capacity scaling laws of two overlaid networks are investigated, which are located in the same area sharing the same wireless resources with different priorities. The primary network can be regarded as an existing communication system operated in a lic ...

An important notion of common information between two random variables is due to Wyner. In this paper, we derive a lower bound on a relaxed variant of Wyner's common information for continuous random variables. The new bound reduces to the lower bound on W ...

The following problem is considered: given a joint distribution P XY and an event E, bound P XY (E) in terms of P X P Y (E) (where P X P Y is the product of the marginals of P XY ) and a measure of dependence of X and Y. Such bounds have direct application ...

In recent years, there has been rapid progress on understanding Gaussian networks with multiple unicast connections, and new coding techniques have emerged. The essence of multi-source networks is how to efficiently manage interference that arises from the transmission of other sessions. Classically, interference is removed by orthogonalization (in time or frequency). This means that the rate per session drops inversely proportional to the number of sessions, suggesting that interference is a strong limitin

Recent progress in brain-machine interfaces (BMIs) has shown tremendous improvements in task complexity and degree of control. In particular, closed-loop decoder adaptation (CLDA) has emerged as an effective paradigm for both improving and maintaining the performance of BMI systems. Here, we demonstrate the first reported use of a CLDA algorithm to rapidly achieve high-performance control of a BMI based on local field potentials (LFPs). We trained a non-human primate to control a 2-D computer cursor by modu

Consider a receiver that observes multiple interfering codewords. The compute-and-forward technique makes it possible for the receiver to directly decode linear combinations of the codewords. Previous work has focused on compute-and-forward for linear Gaus ...

The capacity of a particular large Gaussian relay network is determined in the limit as the number of relays tends to infinity. Upper bounds are derived from cut-set arguments, and lower bounds follow from an argument involving uncoded transmission. It is ...

The Karhunen-Loeve transform (KLT) is a key element of many signal processing tasks, including approximation, compression, and classification. Many recent applications involve {\em distributed} signal processing where it is not generally possible to apply the KLT to the signal; rather, the KLT must be approximated in a distributed fashion. This paper investigates such distributed approximations to the KLT. First, we present explicit solutions to special cases, including a partial KLT (where only a subset of

Caching is an approach to smoothen the variability of traffic over time. Recently it has been proved that the local memories at the users can be exploited for reducing the peak traffic in a much more efficient way than previously believed. In this work we ...

The problem of successive refinement in distributed source coding and in joint source-channel coding is considered. The emphasis is placed on the case where the sources have to be recovered losslessly in the second stage. In distributed source coding, it i ...

We derive a conditional version of the classical regret-capacity theorem. This result can be used in universal prediction to find lower bounds on the minimal batch regret, which is a recently introduced generalization of the average regret, when batches of training data are available to the predictor. As an example, we apply this result to the class of binary memoryless sources. Finally, we generalize the theorem to Rényi information measures, revealing a deep connection between the conditional Rényi diverg

The feedback sum-rate capacity is established for the symmetric

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-user Gaussian multiple-access channel (GMAC). The main contribution is a converse bound that combines the dependence-balance argument of Hekstra and Willems (1989) with a variant of the f ...

Large language models (LLMs) have recently gained much popularity due to their surprising ability at generating human-like English sentences. LLMs are essentially predictors, estimating the probability of a sequence of words given the past. Therefore, it i ...

Experience a guided tour of the key information-theoretic principles that underpin the design of next-generation cellular systems with this invaluable reference. Written by experts in the field, the text encompasses principled theoretical guidelines for the design and performance analysis of network architectures, coding and modulation schemes, and communication protocols. Presenting an extensive overview of the most important ideas and topics necessary for the development of future wireless systems, as wel

Computation codes in network information theory are designed for scenarios where the decoder is not interested in recovering the information sources themselves, but only a function thereof. Körner and Marton showed for distributed source coding (DSC) that ...

We investigate how the network connectivity can affect the degrees of freedom (DoF) of wireless networks. We consider a network of n source-destination (SD) pairs and assume that any two nodes are connected with a positive probability p, independent of other node pairs. We show that, for any arbitrarily small p, a constant DoF is achievable for every SD pair with probability approaching one as n tends to infinity. The achievability is based on the two-hop transmission with decode-and-forward relaying and ov

In this paper, we present information theoretic inner and outer bounds on the fundamental tradeoff between cache memory size and update rate in a multi-user cache network. Each user is assumed to have individual caches, while upon users’ requests, an updat ...

Michael Christoph Gastpar

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The Persuasion Bottleneck

Compute-forward multiple access (CFMA) with nested LDPC codes

Variational Characterizations of Sibson's α-Mutual Information

Capacity Scaling of Cognitive Networks: Beyond Interference-Limited Communication

Lower bound on relaxed Wyner's Common Information

Strengthened Information-theoretic Bounds on the Generalization Error

A Survey on Interference Networks: Interference Alignment and Neutralization

Brain-machine interface control using broadband spectral power from local field potentials

Compute-and-forward for discrete memoryless networks

On the Capacity of Large Gaussian Relay Networks

The distributed Karhunen-Loeve transform

K Users Caching Two Files: An Improved Achievable Rate

On Distributed Successive Refinement with Lossless Recovery

The Conditional Regret-Capacity Theorem for Batch Universal Prediction

Sum-Rate Capacity for Symmetric Gaussian Multiple Access Channels With Feedback

Batch Universal Prediction

Compute–Forward Strategies for Next–Generation Wireless Systems

Communication Versus Computation: Duality for Multiple-Access Channels and Source Coding

Degrees of freedom of sparsely connected wireless networks

Information Theoretic Caching: The Multi-User Case