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Michael Christoph Gastpar

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Publications associées (131)

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On conditional Sibson's alpha-Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito

In this work, we analyse how to define a conditional version of Sibson's alpha-Mutual Information. Several such definitions can be advanced and they all lead to different information measures with different (but similar) operational meanings. We will analy ...

IEEE2021

Locally differentially-private distribution estimation

Michael Christoph Gastpar, Adriano Pastore

We consider a setup in which confidential i.i.d. samples X1, ..., Xn from an unknown discrete distribution PX are passed through a discrete memoryless privatization channel (a.k.a. mechanism) which guarantees an epsilon-level of local differential privacy. ...

Ieee2016

Compute–Forward Multiple Access (CFMA): Practical Implementations

Michael Christoph Gastpar, Sung Hoon Lim, Jingge Zhu, Erixhen Sula, Adriano Pastore

We present a practical strategy that aims to attain rate points on the dominant face of the multiple access channel capacity using a standard low complexity decoder. This technique is built upon recent theoretical developments of Zhu and Gastpar on compute ...

2019

Characterising directed and undirected metrics of high-order interdependence

Michael Christoph Gastpar

Systems of interest for theoretical or experimental work often exhibit high-order interactions, corresponding to statistical interdependencies in groups of variables that cannot be reduced to dependencies in subsets of them. While still under active develo ...

Institute of Electrical and Electronics Engineers Inc.2024

Learning, compression, and leakage: Minimising classification error via meta-universal compression principles

Michael Christoph Gastpar

Learning and compression are driven by the common aim of identifying and exploiting statistical regularities in data, which opens the door for fertile collaboration between these areas. A promising group of compression techniques for learning scenarios is ...

IEEE2021

Efficient Algorithms for the Data Exchange Problem

Michael Christoph Gastpar

In this paper, we study the data exchange problem, where a set of users is interested in gaining access to a common file, but where each has only partial knowledge about it as side-information. Assuming that the file is broken into packets, the side-inform ...

Institute of Electrical and Electronics Engineers2016

Polynomially Solvable Instances of the Shortest and Closest Vector Problems With Applications to Compute-and-Forward

Michael Christoph Gastpar, Saeid Sahraei

A particular instance of the shortest vector problem (SVP) appears in the context of compute-and-forward. Despite the NP-hardness of the SVP, we will show that this certain instance can be solved in complexity order O(nψlog(nψ)) , where ψ=sqrt(P ||h||^2+1) ...

Institute of Electrical and Electronics Engineers2017

Fundamental Limits of Prompt Compression: A Rate- Distortion Framework for Black-Box Language Models

Michael Christoph Gastpar, Adway Girish, Ashok Vardhan Makkuva

We formalize the problem of prompt compression for large language models (LLMs) and present a framework to unify token-level prompt compression methods which create hard prompts for black-box models. We derive the distortion-rate function for this setup as ...

Curran Associates, Inc.2024

Integer-forcing Linear Receivers

Michael Christoph Gastpar

Linear receivers are often used to reduce the implementation complexity of multiple-antenna systems. In a traditional linear receiver architecture, the receive antennas are used to separate out the codewords sent by each transmit antenna, which can then be ...

Institute of Electrical and Electronics Engineers2014

Power, Spatio-Temporal Bandwidth, and Distortion in Large Sensor Networks

Martin Vetterli, Michael Christoph Gastpar

For a class of sensor networks, the task is to monitor an underlying physical phenomenon over space and time through an imperfect observation process. The sensors can communicate back to a central data collector over a noisy channel. The key pa- rameters i ...

Institute of Electrical and Electronics Engineers2005

Polar Codes For Broadcast Channels

Michael Christoph Gastpar, Emmanuel Abbé, Naveen Goela

Building on polar code constructions proposed by the authors for deterministic broadcast channels, two theorems are introduced in the present paper for noisy two-user broadcast channels. The theorems establish polar code constructions for two important ...

2013

Lower-bounds on the Bayesian Risk in Estimation Procedures via f–Divergences

Michael Christoph Gastpar, Amedeo Roberto Esposito, Adrien Vandenbroucque

We consider the problem of parameter estimation in a Bayesian setting and propose a general lower-bound that includes part of the family of f-Divergences. The results are then applied to specific settings of interest and compared to other notable results i ...

2022

A Discretization Approach to Compute-Forward

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

We present a novel unified framework of compute- forward achievable rate regions for simultaneous decoding of multiple linear codeword combinations. This framework covers a wide class of discrete and continuous-input channels, and computation over finite f ...

IEEE2021

Relaxed Wyner's Common Information

Michael Christoph Gastpar, Erixhen Sula

In the problem of coded caching for media delivery, two separate coding opportunities have been identified. The first opportunity is a multi-user advantage and crucially hinges on a public broadcast link in the delivery phase. This has been explored in a p ...

IEEE2019

The Optimal Memory-Rate Trade-Off for the Non-Uniform Centralized Caching Problem With Two Files Under Uncoded Placement

Michael Christoph Gastpar, Saeid Sahraei, Pierre Victor Xavier Quinton

A new scheme for the problem of centralized coded caching with non-uniform demands is proposed. The distinguishing feature of the proposed placement strategy is that it admits equal sub-packetization for all files while allowing the users to allocate more ...

2019

Single-server Multi-user Private Information Retrieval with Side Information

Michael Christoph Gastpar, Su Li

In the problem of private information retrieval with side information, a single user wants to recover one of the K independent messages which are stored at one or multiple servers. The user initially has a subset of messages as side information. The goal o ...

2018

Simultaneous Computation and Communication over MAC

Michael Christoph Gastpar

We study communication over a Gaussian multiple-access channel (MAC) with two types of transmitters: Digital transmitters hold a message from a discrete set that needs to be communicated to the receiver. Analog transmitters hold sequences of analog values, ...

Institute of Electrical and Electronics Engineers Inc.2024

A Johnson-Lindenstrauss Framework for Randomly Initialized CNNs

Michael Christoph Gastpar, Jan Hazla, Ido Nachum

How does the geometric representation of a dataset change after the application of each randomly initialized layer of a neural network? The celebrated Johnson-Lindenstrauss lemma answers this question for linear fully-connected neural networks (FNNs), stat ...

2022

Lattice Codes for Many-to-One Interference Channels With and Without Cognitive Messages

Michael Christoph Gastpar, Jingge Zhu

A new achievable rate region is given for the Gaussian cognitive many-to-one interference channel. The proposed novel coding scheme is based on the compute-and-forward approach with lattice codes. Using the idea of decoding sums of codewords, our scheme im ...

Institute of Electrical and Electronics Engineers2015

Computable Bounds on the Exploration Bias

Michael Christoph Gastpar, Ibrahim Issa

Adaptive data analysis is known to introduce bias in reported measurements. Russo and Zou [1] recently introduced an information-theoretic framework to study this problem. Herein, this framework is adopted and new dependence measures are introduced to boun ...

2018