Search Results for author: Yuwei Hu

Found 8 papers, 4 papers with code

An Asynchronous Updating Reinforcement Learning Framework for Task-oriented Dialog System

1 code implementation4 May 2023 Sai Zhang, Yuwei Hu, Xiaojie Wang, Caixia Yuan

The errors from DST might misguide the dialog policy, and the system action brings extra difficulties for the DST module.

dialog state tracking reinforcement-learning

Analysis and Optimization of GNN-Based Recommender Systems on Persistent Memory

no code implementations25 Jul 2022 Yuwei Hu, Jiajie Li, Zhongming Yu, Zhiru Zhang

To understand whether persistent memory is a good fit for GNNRecSys training, we perform an in-depth characterization of GNNRecSys workloads and a comprehensive analysis of their performance on a persistent memory device, namely, Intel Optane.

Link Prediction Recommendation Systems

A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots

1 code implementation Findings (ACL) 2022 Sai Zhang, Yuwei Hu, Yuchuan Wu, Jiaman Wu, Yongbin Li, Jian Sun, Caixia Yuan, Xiaojie Wang

We find some new linguistic phenomena and interactive manners in SSTOD which raise critical challenges of building dialog agents for the task.

 Ranked #1 on SSTOD on SSD_NAME

SSTOD

Dense Pruning of Pointwise Convolutions in the Frequency Domain

no code implementations16 Sep 2021 Mark Buckler, Neil Adit, Yuwei Hu, Zhiru Zhang, Adrian Sampson

Our key insights are that 1) pointwise convolutions commute with frequency transformation and thus can be computed in the frequency domain without modification, 2) each channel within a given layer has a different level of sensitivity to frequency domain pruning, and 3) each channel's sensitivity to frequency pruning is approximately monotonic with respect to frequency.

FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems

no code implementations26 Aug 2020 Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang

FeatGraph provides a flexible programming interface to express diverse GNN models by composing coarse-grained sparse templates with fine-grained user-defined functions (UDFs) on each vertex/edge.

Improving Neural Network Quantization without Retraining using Outlier Channel Splitting

3 code implementations28 Jan 2019 Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang

The majority of existing literature focuses on training quantized DNNs, while this work examines the less-studied topic of quantizing a floating-point model without (re)training.

Language Modelling Neural Network Compression +1

Building Efficient Deep Neural Networks with Unitary Group Convolutions

no code implementations CVPR 2019 Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang

UGConvs generalize two disparate ideas in CNN architecture, channel shuffling (i. e. ShuffleNet) and block-circulant networks (i. e. CirCNN), and provide unifying insights that lead to a deeper understanding of each technique.

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

1 code implementation12 Feb 2018 Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Meghan Cowan, Haichen Shen, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

Experimental results show that TVM delivers performance across hardware back-ends that are competitive with state-of-the-art, hand-tuned libraries for low-power CPU, mobile GPU, and server-class GPUs.

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