activity
20182021
most citedLatency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization

5 citations · 12 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL20211 cited

Noisy Training Improves E2E ASR for the Edge

Dilin Wang, Yuan Shangguan, Haichuan Yang +6

Automatic speech recognition (ASR) has become increasingly ubiquitous on modern edge devices. Past work developed streaming End-to-End (E2E) all-neural speech recognizers that can…

cs.LG20215 cited

Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization

David Eriksson, Pierce I-Jen Chuang, Samuel Daulton +7

When tuning the architecture and hyperparameters of large machine learning models for on-device deployment, it is desirable to understand the optimal trade-offs between on-device l…

cs.CL2021

Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing

Akshat Shrivastava, Pierce Chuang, Arun Babu +4

An effective recipe for building seq2seq, non-autoregressive, task-oriented parsers to map utterances to semantic frames proceeds in three steps: encoding an utterance , predict…

cs.AR20213 cited

F-CAD: A Framework to Explore Hardware Accelerators for Codec Avatar Decoding

Xiaofan Zhang, Dawei Wang, Pierce Chuang +3

Creating virtual avatars with realistic rendering is one of the most essential and challenging tasks to provide highly immersive virtual reality (VR) experiences. It requires not o…

cs.LG20201 cited

One Weight Bitwidth to Rule Them All

Ting-Wu Chin, Pierce I-Jen Chuang, Vikas Chandra +1

Weight quantization for deep ConvNets has shown promising results for applications such as image classification and semantic segmentation and is especially important for applicatio…

cs.CV20202 cited

Improving Efficiency in Neural Network Accelerator Using Operands Hamming Distance optimization

Meng Li, Yilei Li, Pierce Chuang +2

Neural network accelerator is a key enabler for the on-device AI inference, for which energy efficiency is an important metric. The data-path energy, including the computation ener…