Publications by Chen Feng | EPFL Graph Search

Distributed Lossy Computation with Structured Codes: From Discrete to Continuous Sources

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

This paper considers the problem of distributed lossy compression where the goal is to recover one or more linear combinations of the sources at the decoder, subject to distortion constraints. For certain configurations, it is known that codes with algebra ...

2023

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

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

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 ...

Institute of Electrical and Electronics Engineers (IEEE)2023

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

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations

Michael Christoph Gastpar, Adriano Pastore, Sung Hoon Lim, 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

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

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

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 ...

2019

A Joint Typicality Approach to Compute–Forward

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

This paper presents a joint typicality framework for encoding and decoding nested linear codes in multi-user networks. This framework provides a new perspective on compute–forward within the context of discrete memoryless networks. In particular, it establ ...

2018

Towards an algebraic network information theory: Simultaneous joint typicality decoding

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

Recent work has employed joint typicality encoding and decoding of nested linear code ensembles to generalize the compute-forward strategy to discrete memoryless multiple-access channels (MACs). An appealing feature of these nested linear code ensembles is ...

2017

A joint typicality approach to compute-forward

Michael Christoph Gastpar, Sung Hoon Lim, Chen Feng

A general framework for analyzing linear codes with joint typicality encoders and decoders is presented. Using this approach, we provide a new perspective on the compute-forward framework. In particular, an achievable rate region for computing the weighted ...

2015

Near-Infrared Guided Color Image Dehazing

Sabine Süsstrunk, Chen Feng

Near-infrared (NIR) light has stronger penetration capability than visible light due to its long wavelength, thus being less scattered by particles in the air. This makes it desirable for image dehazing to unveil details of distant objects in landscape pho ...

2013