ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning

8 July 2019

Papers citing "ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning"

7 / 7 papers shown

Title
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition Samuel Horváth Stefanos Laskaridis Shashank Rajput Hongyi Wang BDL 32 4 0 28 Aug 2023
Mixed Precision Low-bit Quantization of Neural Network Language Models for Speech Recognition Junhao Xu Jianwei Yu Shoukang Hu Xunying Liu Helen Meng MQ 27 13 0 29 Nov 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 189 268 0 26 Feb 2021
A Survey on Deep Reinforcement Learning for Audio-Based Applications S. Latif Heriberto Cuayáhuitl Farrukh Pervez Fahad Shamshad Hafiz Shehbaz Ali Min Zhang OffRL 47 73 0 01 Jan 2021
Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator Mohamed S. Abdelfattah L. Dudziak Thomas C. P. Chau Royson Lee Hyeji Kim Nicholas D. Lane 17 79 0 11 Feb 2020
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 271 5,327 0 05 Nov 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 218 7,925 0 17 Aug 2015