no code implementations • 8 Mar 2024 • Jianzong Wang, Pengcheng Li, xulong Zhang, Ning Cheng, Jing Xiao
After combining the intent from two domains into a joint representation, the integrated intent representation is fed into a decision layer for classification.
1 code implementation • CVPR 2023 • Chuandong Liu, Chenqiang Gao, Fangcen Liu, Pengcheng Li, Deyu Meng, Xinbo Gao
State-of-the-art 3D object detectors are usually trained on large-scale datasets with high-quality 3D annotations.
no code implementations • 7 Dec 2022 • Pengcheng Li, Genshun Wan, Fenglin Ding, Hang Chen, Jianqing Gao, Jia Pan, Cong Liu
Speech pre-training has shown great success in learning useful and general latent representations from large-scale unlabeled data.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 7 Dec 2022 • Fenglin Ding, Genshun Wan, Pengcheng Li, Jia Pan, Cong Liu
Multilingual end-to-end models have shown great improvement over monolingual systems.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 29 Sep 2021 • Pengcheng Li, Yixin Guo, Yawen Zhang, Qinggang Zhou
Mini-batch Stochastic Gradient Descent (SGD) requires workers to halt forward/backward propagations, to wait for gradients synchronized among all workers before the next batch of tasks.
no code implementations • 29 Sep 2021 • Yixin Guo, Pengcheng Li, Yingwei Luo, Xiaolin Wang, Zhenlin Wang
To this end, we explore a generic program embedding approach that aim at solving multiple program analysis tasks.
no code implementations • Pattern Recognition Letters 2021 • Yue Zhao, Lingming Zhang, Chongshi Yang, Yingyun Tan, Yang Liu, Pengcheng Li, Tianhao Huang, Chenqiang Gao
We have evaluated our network on a real-patient dataset of dental models acquired through 3D intraoral scanners, and experimental results show that our method outperforms state-of-the-art deep learning methods for 3D shape segmentation.
no code implementations • 16 Jul 2021 • Shaojun Ma, Pengcheng Li
Predicting intraday trading volume plays an important role in trading alpha research.
no code implementations • 18 Nov 2020 • Yixin Guo, Pengcheng Li, Yingwei Luo, Xiaolin Wang, Zhenlin Wang
To this end, we propose a learning-aided approach to identify unnecessary memory operations intelligently with low overhead.
no code implementations • 13 Nov 2020 • Nan Wu, Pengcheng Li
With data durability, high access speed, low power efficiency and byte addressability, NVMe and SSD, which are acknowledged representatives of emerging storage technologies, have been applied broadly in many areas.
no code implementations • 31 Jul 2020 • Pengcheng Li, Yongbin Gu
Inspired by the high prediction accuracy, we propose a pseudo OPT policy and evaluate it upon 13 real-world storage workloads from Microsoft Research.
no code implementations • 31 May 2020 • Qinggang Zhou, Yawen Zhang, Pengcheng Li, Xiaoyong Liu, Jun Yang, Runsheng Wang, Ru Huang
The state-of-the-art deep learning algorithms rely on distributed training systems to tackle the increasing sizes of models and training data sets.
no code implementations • 28 May 2019 • Pengcheng Li, Jin-Feng Yi, Bo-Wen Zhou, Lijun Zhang
In this paper, we improve the robustness of DNNs by utilizing techniques of Distance Metric Learning.
no code implementations • 13 Sep 2018 • Pengcheng Li, Jin-Feng Yi, Lijun Zhang
To conduct black-box attack, a popular approach aims to train a substitute model based on the information queried from the target DNN.
no code implementations • MediaEval 2015 Workshop 2015 • Jingyong Hou, Van Tung Pham, Cheung-Chi Leung, Lei Wang, HaiHua Xu, Hang Lv, Lei Xie, Zhonghua Fu, Chongjia Ni, Xiong Xiao, Hongjie Chen, Shaofei Zhang, Sining Sun, Yougen Yuan, Pengcheng Li, Tin Lay Nwe, Sunil Sivadas, Bin Ma, Eng Siong Chng, Haizhou Li
This paper describes the system developed by the NNI team for the Query-by-Example Search on Speech Task (QUESST) in the MediaEval 2015 evaluation.
Ranked #9 on Keyword Spotting on QUESST