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20152020
most citedResiliency of Deep Neural Networks under Quantization

143 citations · 351 across the 12 of their papers we have counts for

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Showing 2016Show all

5 papers · 1 filter

cs.LG2016★ 1 cited

Quantized neural network design under weight capacity constraint

Sungho Shin, Kyuyeon Hwang, Wonyong Sung

The complexity of deep neural network algorithms for hardware implementation can be lowered either by scaling the number of units or reducing the word-length of weights. Both appro…

cs.CL2016★ 5 cited

FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networks

Minjae Lee, Kyuyeon Hwang, Jinhwan Park +3

In this paper, a neural network based real-time speech recognition (SR) system is developed using an FPGA for very low-power operation. The implemented system employs two recurrent…

cs.LG2016★ 7 cited

Character-Level Language Modeling with Hierarchical Recurrent Neural Networks

Kyuyeon Hwang, Wonyong Sung

Recurrent neural network (RNN) based character-level language models (CLMs) are extremely useful for modeling out-of-vocabulary words by nature. However, their performance is gener…

cs.LG2016★ 8 cited

Generative Knowledge Transfer for Neural Language Models

Sungho Shin, Kyuyeon Hwang, Wonyong Sung

In this paper, we propose a generative knowledge transfer technique that trains an RNN based language model (student network) using text and output probabilities generated from a p…

cs.CL2016★ 62 cited

Character-Level Incremental Speech Recognition with Recurrent Neural Networks

Kyuyeon Hwang, Wonyong Sung

In real-time speech recognition applications, the latency is an important issue. We have developed a character-level incremental speech recognition (ISR) system that responds quick…