Search Results for author: Jun Haeng Lee

Found 4 papers, 0 papers with code

Quantization for Rapid Deployment of Deep Neural Networks

no code implementations ICLR 2019 Jun Haeng Lee, Sangwon Ha, Saerom Choi, Won-Jo Lee, Seungwon Lee

This paper aims at rapid deployment of the state-of-the-art deep neural networks (DNNs) to energy efficient accelerators without time-consuming fine tuning or the availability of the full datasets.

object-detection Object Detection +1

Training Deep Neural Network in Limited Precision

no code implementations12 Oct 2018 Hyunsun Park, Jun Haeng Lee, Youngmin Oh, Sangwon Ha, Seungwon Lee

Energy and resource efficient training of DNNs will greatly extend the applications of deep learning.

Delta Networks for Optimized Recurrent Network Computation

no code implementations ICML 2017 Daniel Neil, Jun Haeng Lee, Tobi Delbruck, Shih-Chii Liu

Similarly, on the large Wall Street Journal speech recognition benchmark even existing networks can be greatly accelerated as delta networks, and a 5. 7x improvement with negligible loss of accuracy can be obtained through training.

speech-recognition Speech Recognition

Training Deep Spiking Neural Networks using Backpropagation

no code implementations31 Aug 2016 Jun Haeng Lee, Tobi Delbruck, Michael Pfeiffer

Deep spiking neural networks (SNNs) hold great potential for improving the latency and energy efficiency of deep neural networks through event-based computation.

Event-based vision

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