Task-oriented communication for multidevice cooperative edge inference
This paper investigates task-oriented communication for multi-device cooperative edge
inference, where a group of distributed low-end edge devices transmit the extracted features …
inference, where a group of distributed low-end edge devices transmit the extracted features …
Distributed compression in the era of machine learning: A review of recent advances
E Özyılkan, E Erkip - 2024 58th Annual Conference on …, 2024 - ieeexplore.ieee.org
Many applications from camera arrays to sensor networks require efficient compression and
processing of correlated data, which in general is collected in a distributed fashion. While …
processing of correlated data, which in general is collected in a distributed fashion. While …
Importance matching lemma for lossy compression with side information
We propose two extensions to existing importance sampling based methods for lossy
compression. First, we introduce an importance sampling based compression scheme that is …
compression. First, we introduce an importance sampling based compression scheme that is …
Neural distributed compressor discovers binning
We consider lossy compression of an information source when the decoder has lossless
access to a correlated one. This setup, also known as the Wyner-Ziv problem, is a special …
access to a correlated one. This setup, also known as the Wyner-Ziv problem, is a special …
Neural distributed image compression with cross-attention feature alignment
We consider the problem of compressing an information source when a correlated one is
available as side information only at the decoder side, which is a special case of the …
available as side information only at the decoder side, which is a special case of the …
Learned Wyner–Ziv compressors recover binning
We consider lossy compression of an information source when the decoder has lossless
access to a correlated one. This setup, also known as the Wyner-Ziv problem, is a special …
access to a correlated one. This setup, also known as the Wyner-Ziv problem, is a special …
Task-aware distributed source coding under dynamic bandwidth
Efficient compression of correlated data is essential to minimize communication overload in
multi-sensor networks. In such networks, each sensor independently compresses the data …
multi-sensor networks. In such networks, each sensor independently compresses the data …
LDMIC: Learning-based distributed multi-view image coding
Multi-view image compression plays a critical role in 3D-related applications. Existing
methods adopt a predictive coding architecture, which requires joint encoding to compress …
methods adopt a predictive coding architecture, which requires joint encoding to compress …
Neural distributed image compression using common information
We present a novel deep neural network (DNN) architecture for compressing an image
when a correlated image is available as side information only at the decoder, a special case …
when a correlated image is available as side information only at the decoder, a special case …
Interpreting deep-learned error-correcting codes
Deep learning has been used recently to learn error-correcting encoders and decoders
which may improve upon previously known codes in certain regimes. The encoders and …
which may improve upon previously known codes in certain regimes. The encoders and …