Hyeji Kim | DeepAI

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Nicholas D. Lane
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∙ 05/24/2023

Task-aware Distributed Source Coding under Dynamic Bandwidth

Efficient compression of correlated data is essential to minimize commun...

0 Po-han Li, et al. ∙

∙ 02/20/2023

Compressed Error HARQ: Feedback Communication on Noise-Asymmetric Channels

In modern communication systems with feedback, there are increasingly mo...

0 Sravan Kumar Ankireddy, et al. ∙

∙ 09/30/2022

TinyTurbo: Efficient Turbo Decoders on Edge

In this paper, we introduce a neural-augmented decoder for Turbo codes c...

0 S Ashwin Hebbar, et al. ∙

∙ 05/21/2022

Neural Augmented Min-Sum Decoding of Short Block Codes for Fading Channels

In the decoding of linear block codes, it was shown that noticeable gain...

0 Sravan Kumar Ankireddy, et al. ∙

∙ 11/22/2021

Turbo Autoencoder with a Trainable Interleaver

A critical aspect of reliable communication involves the design of codes...

0 Karl Chahine, et al. ∙

∙ 08/13/2021

DeepIC: Coding for Interference Channels via Deep Learning

The two-user interference channel is a model for multi one-to-one commun...

0 Karl Chahine, et al. ∙

∙ 07/15/2021

A Channel Coding Benchmark for Meta-Learning

Meta-learning provides a popular and effective family of methods for dat...

0 Rui Li, et al. ∙

∙ 06/05/2021

Neural Distributed Source Coding

Distributed source coding is the task of encoding an input in the absenc...

0 Jay Whang, et al. ∙

∙ 03/17/2021

Gaussian Channels with Feedback: A Dynamic Programming Approach

In this paper, we consider a communication system where a sender sends m...

0 Rajesh Mishra, et al. ∙

∙ 08/18/2020

Deepcode and Modulo-SK are Designed for Different Settings

We respond to [1] which claimed that "Modulo-SK scheme outperforms Deepc...

17 Hyeji Kim, et al. ∙

∙ 08/10/2020

HAPI: Hardware-Aware Progressive Inference

Convolutional neural networks (CNNs) have recently become the state-of-t...

9 Stefanos Laskaridis, et al. ∙

∙ 07/16/2020

BRP-NAS: Prediction-based NAS using GCNs

Neural architecture search (NAS) enables researchers to automatically ex...

0 Thomas Chau, et al. ∙

∙ 07/08/2020

Journey Towards Tiny Perceptual Super-Resolution

Recent works in single-image perceptual super-resolution (SR) have demon...

0 Royson Lee, et al. ∙

∙ 04/29/2020

Stealth UAV through Coanda Effect

This paper uses Coanda Effect to reduce motors, the source of noise, and...

0 Dongyoon Shin, et al. ∙

∙ 04/20/2020

ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers

Automatic speech recognition (ASR) via call is essential for various app...

2 Jung-Woo Ha, et al. ∙

∙ 02/11/2020

Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator

Neural architecture search (NAS) has been very successful at outperformi...

0 Mohamed S. Abdelfattah, et al. ∙

∙ 11/08/2019

Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels

Designing codes that combat the noise in a communication medium has rema...

0 Yihan Jiang, et al. ∙

∙ 03/06/2019

DeepTurbo: Deep Turbo Decoder

Present-day communication systems routinely use codes that approach the ...

0 Yihan Jiang, et al. ∙

∙ 11/30/2018

A Framework for Fast and Efficient Neural Network Compression

Network compression reduces the computational complexity and memory cons...

0 Hyeji Kim, et al. ∙

∙ 11/30/2018

LEARN Codes: Inventing Low-latency Codes via Recurrent Neural Networks

Designing channel codes under low latency constraints is one of the most...

2 Yihan Jiang, et al. ∙

∙ 07/02/2018

Deepcode: Feedback Codes via Deep Learning

The design of codes for communicating reliably over a statistically well...

0 Hyeji Kim, et al. ∙

∙ 06/28/2018

Automatic Rank Selection for High-Speed Convolutional Neural Network

Low-rank decomposition plays a central role in accelerating convolutiona...

0 Hyeji Kim, et al. ∙

∙ 05/23/2018

Communication Algorithms via Deep Learning

Coding theory is a central discipline underpinning wireline and wireless...

2 Hyeji Kim, et al. ∙

∙ 09/12/2017

Discovering Potential Correlations via Hypercontractivity

Discovering a correlation from one variable to another variable is of fu...

0 Hyeji Kim, et al. ∙

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