1 code implementation • 11 Apr 2016 • Xundong Wu, Yong Wu, Yong Zhao
We trained Binarized Neural Networks (BNNs) on the high resolution ImageNet ILSVRC-2102 dataset classification task and achieved a good performance.
no code implementations • 23 Nov 2019 • Di Wu, Chao Wang, Yong Wu, De-Shuang Huang
Besides, most of the multi-scale models embedding the multi-scale feature learning block into the feature extraction deep network, which reduces the efficiency of inference network.
no code implementations • 4 Jun 2020 • Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang
Modern deep neural networks increasingly make use of features such as dynamic control flow, data structures and dynamic tensor shapes.
1 code implementation • 22 Jan 2021 • Gongyang Li, Zhi Liu, Ran Shi, Zheng Hu, Weijie Wei, Yong Wu, Mengke Huang, Haibin Ling
In this paper, we focus on Personal Fixations-based Object Segmentation (PFOS) to address issues in previous studies, such as the lack of appropriate dataset and the ambiguity in fixations-based interaction.
2 code implementations • 6 Mar 2021 • Shabnam Daghaghi, Nicholas Meisburger, Mengnan Zhao, Yong Wu, Sameh Gobriel, Charlie Tai, Anshumali Shrivastava
Our work highlights several novel perspectives and opportunities for implementing randomized algorithms for deep learning on modern CPUs.
no code implementations • 18 Oct 2022 • Yong Wu, Shekhor Chanda, Mehrdad Hosseinzadeh, Zhi Liu, Yang Wang
In this paper, we propose task-specific meta distillation that simultaneously learns two models in meta-learning: a large teacher model and a small student model.
no code implementations • 29 Apr 2023 • Mei Yang, Gao Qiu, Yong Wu, Junyong Liu, Nina Dai, Yue Shui, Kai Liu, Lijie Ding
The increasing scale of alternating current and direct current (AC/DC) hybrid systems necessitates a faster power flow analysis tool than ever.
no code implementations • 7 Aug 2023 • Yancheng Liang, Jiajie Zhang, Hui Li, Xiaochen Liu, Yi Hu, Yong Wu, Jinyao Zhang, Yongyan Liu, Yi Wu
Despite the tremendous advances achieved over the past years by deep learning techniques, the latest risk prediction models for industrial applications still rely on highly handtuned stage-wised statistical learning tools, such as gradient boosting and random forest methods.
no code implementations • 4 Sep 2023 • Zhuo-yong Shi, Ye-tao Jia, Ke-xin Zhang, Ding-han Wang, Long-meng Ji, Yong Wu
Based on this, this paper improves wearable devices of table tennis sport, and realizes the pattern recognition and evaluation of table tennis players' motor skills through artificial intelligence.
1 code implementation • 22 Sep 2023 • Yong Wu, Yanwei Fu, Shouyan Wang, Xinwei Sun
To address these challenges, we propose a kernel-based DR estimator that can well handle continuous treatments.
no code implementations • 29 Sep 2023 • Yong Wu, Mingzhou Liu, Jing Yan, Yanwei Fu, Shouyan Wang, Yizhou Wang, Xinwei Sun
To accommodate these scenarios, we consider a new setting dubbed as multiple treatments and multiple outcomes.
no code implementations • 1 Nov 2023 • Ruihang Lai, Junru Shao, Siyuan Feng, Steven S. Lyubomirsky, Bohan Hou, Wuwei Lin, Zihao Ye, Hongyi Jin, Yuchen Jin, Jiawei Liu, Lesheng Jin, Yaxing Cai, Ziheng Jiang, Yong Wu, Sunghyun Park, Prakalp Srivastava, Jared G. Roesch, Todd C. Mowry, Tianqi Chen
Dynamic shape computations have become critical in modern machine learning workloads, especially in emerging large language models.
2 code implementations • 20 Nov 2023 • Lei Fan, Yiwen Ding, Dongdong Fan, Yong Wu, Hongxia Chu, Maurice Pagnucco, Yang song
We present a machine vision-based database named GrainSet for the purpose of visual quality inspection of grain kernels.
1 code implementation • 20 Nov 2023 • Lei Fan, Yiwen Ding, Dongdong Fan, Yong Wu, Maurice Pagnucco, Yang song
Cereal grain plays a crucial role in the human diet as a major source of essential nutrients.
1 code implementation • 7 Mar 2024 • Boyang Peng, Sanqing Qu, Yong Wu, Tianpei Zou, Lianghua He, Alois Knoll, Guang Chen, Changjun Jiang
In this paper, we target a practical setting where only a well-trained source model is available and investigate how we can realize IP protection.
1 code implementation • 17 Apr 2024 • Xin Li, Kun Yuan, Yajing Pei, Yiting Lu, Ming Sun, Chao Zhou, Zhibo Chen, Radu Timofte, Wei Sun, HaoNing Wu, ZiCheng Zhang, Jun Jia, Zhichao Zhang, Linhan Cao, Qiubo Chen, Xiongkuo Min, Weisi Lin, Guangtao Zhai, Jianhui Sun, Tianyi Wang, Lei LI, Han Kong, Wenxuan Wang, Bing Li, Cheng Luo, Haiqiang Wang, Xiangguang Chen, Wenhui Meng, Xiang Pan, Huiying Shi, Han Zhu, Xiaozhong Xu, Lei Sun, Zhenzhong Chen, Shan Liu, Fangyuan Kong, Haotian Fan, Yifang Xu, Haoran Xu, Mengduo Yang, Jie zhou, Jiaze Li, Shijie Wen, Mai Xu, Da Li, Shunyu Yao, Jiazhi Du, WangMeng Zuo, Zhibo Li, Shuai He, Anlong Ming, Huiyuan Fu, Huadong Ma, Yong Wu, Fie Xue, Guozhi Zhao, Lina Du, Jie Guo, Yu Zhang, huimin zheng, JunHao Chen, Yue Liu, Dulan Zhou, Kele Xu, Qisheng Xu, Tao Sun, Zhixiang Ding, Yuhang Hu
This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i. e., Kuaishou/Kwai Platform.