Publications by Michael Christoph Gastpar

Caching (Bivariate) Gaussians

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

Caching is a technique that alleviates networks during peak hours by transmitting partial information before a request for any is made. In a lossy setting of Gaussian databases, we study a single-user model in which good caching strategies minimize the dat ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Converse for Multi-Server Single-Message PIR with Side Information

Michael Christoph Gastpar, Su Li

Multi-server single-message private information retrieval is studied in the presence of side information. In this problem, K independent messages are replicatively stored at N non-colluding servers. The user wants to privately download one message from the ...

2020

Robust Generalization via f−Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

Given two probability measures P and Q and an event E, we provide bounds on P(E) in terms of Q(E) and f-divergences. In particular, the bounds are instantiated when the measures considered are a joint distribution and the corresponding product of marginals ...

IEEE2020

Common Information Components Analysis

Michael Christoph Gastpar, Erixhen Sula

We give an information-theoretic interpretation of Canonical Correlation Analysis (CCA) via (relaxed) Wyner's common information. CCA permits to extract from two high-dimensional data sets low-dimensional descriptions (features) that capture the commonalit ...

IEEE2020

The Gaussian lossy Gray-Wyner network

Michael Christoph Gastpar, Erixhen Sula

We consider the problem of source coding subject to a fidelity criterion for the Gray-Wyner network that connects a single source with two receivers via a common channel and two private channels. The pareto-optimal trade-offs between the sum-rate of the pr ...

2020

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

Michael Christoph Gastpar, Erixhen Sula

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 ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations

Michael Christoph Gastpar, Sung Hoon Lim, Adriano Pastore, Chen Feng

Algebraic network information theory is an emerging facet of network information theory, studying the achievable rates of random code ensembles that have algebraic structure, such as random linear codes. A distinguishing feature is that linear combinations ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Successive Refinement to Caching for Dynamic Content

Michael Christoph Gastpar, Pinar Sen

To reduce the network load during peak hours, servers deliver partial data to users during the off-peak time of the network before the actual requests are known, which is known as caching. This paper studies a single user caching problem in which the file ...

IEEE2019

Strengthened Information-theoretic Bounds on the Generalization Error

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

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 ...

IEEE2019

Quantifying high-order interdependencies via multivariate extensions of the mutual information

Michael Christoph Gastpar, Fernando Rosas de Andraca

This paper introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information ...

2019

Michael Christoph Gastpar

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Caching (Bivariate) Gaussians

Converse for Multi-Server Single-Message PIR with Side Information

Robust Generalization via f−Mutual Information

Common Information Components Analysis

The Gaussian lossy Gray-Wyner network

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

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations

Successive Refinement to Caching for Dynamic Content

Strengthened Information-theoretic Bounds on the Generalization Error

Quantifying high-order interdependencies via multivariate extensions of the mutual information

Caching (Bivariate) Gaussians

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

Robust Generalization via f−Mutual Information

The Gaussian lossy Gray-Wyner network

Converse for Multi-Server Single-Message PIR with Side Information

Strengthened Information-theoretic Bounds on the Generalization Error

Common Information Components Analysis

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations

Successive Refinement to Caching for Dynamic Content

Quantifying high-order interdependencies via multivariate extensions of the mutual information