no code implementations • 12 Apr 2024 • Peijie Sun, Yifan Wang, Min Zhang, Chuhan Wu, Yan Fang, Hong Zhu, Yuan Fang, Meng Wang
In summary, our contributions underscore the importance of stable model training frameworks and the efficacy of collaborative-enhanced models in predicting user spending behavior in mobile gaming.
no code implementations • 24 Mar 2024 • Hong Zhu, Alexander Venus, Erik Leitinger, Stefan Tertinek, Klaus Witrisal
Then, a joint tracking algorithm that utilizes both active and passive measurements is developed for the extended object.
no code implementations • 27 Feb 2024 • Yuang Zhao, Chuhan Wu, Qinglin Jia, Hong Zhu, Jia Yan, Libin Zong, Linxuan Zhang, Zhenhua Dong, Muyu Zhang
Calibration aims to address this issue by post-processing model predictions, and field-aware calibration can adjust model output on different feature field values to satisfy fine-grained advertising demands.
no code implementations • 5 Feb 2024 • Tanha Miah, Hong Zhu
The paper reports an application of the method in the evaluation of ChatGPT usability as a code generation tool for the R programming language.
no code implementations • 19 Dec 2023 • Hui Wu, Yi Gan, Feng Yuan, Jing Ma, Wei Zhu, Yutao Xu, Hong Zhu, Yuhua Zhu, Xiaoli Liu, Jinghui Gu
A customized Scaled-Dot-Product-Attention kernel is designed to match our fusion policy based on the segment KV cache solution.
1 code implementation • 15 Oct 2023 • Jiuyang Zhou, Tengfei Niu, Hong Zhu, Xingping Wang
This paper explores the modeling method of polyphonic music sequence.
no code implementations • 29 Aug 2023 • Hong Zhu, Runpeng Yu, Xing Tang, Yifei Wang, Yuan Fang, Yisen Wang
Data in the real-world classification problems are always imbalanced or long-tailed, wherein the majority classes have the most of the samples that dominate the model training.
no code implementations • 1 Aug 2023 • Jiuyang Zhou, Hong Zhu, Xingping Wang
We also proposed a music representation suitable for polyphonic music generation.
no code implementations • 13 Jul 2023 • Hong Zhu, Thi Minh Tam Tran, Aduen Benjumea, Andrew Bradley
This paper proposes a scenario-based functional testing approach for enhancing the performance of machine learning (ML) applications.
no code implementations • 30 Jun 2023 • Zhiqiang Zhang, Hong Zhu, Meiyi Xie
For this reason, this paper attempts to combine DP and SI for the first time, and proposes a general differentially private swarm intelligence algorithm framework (DPSIAF).
no code implementations • 26 Jun 2023 • Chuhan Wu, Jingjie Li, Qinglin Jia, Hong Zhu, Yuan Fang, Ruiming Tang
Accurate customer lifetime value (LTV) prediction can help service providers optimize their marketing policies in customer-centric applications.
1 code implementation • 19 Jun 2023 • Yunjia Xi, Weiwen Liu, Jianghao Lin, Xiaoling Cai, Hong Zhu, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu
In this work, we propose an Open-World Knowledge Augmented Recommendation Framework with Large Language Models, dubbed KAR, to acquire two types of external knowledge from LLMs -- the reasoning knowledge on user preferences and the factual knowledge on items.
1 code implementation • 13 Oct 2022 • Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang
In this paper, we empirically show that sample-wise AT has limited improvement on OOD performance.
1 code implementation • 9 Aug 2022 • Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu
To this end, we propose an optimal embedding table learning framework OptEmbed, which provides a practical and general method to find an optimal embedding table for various base CTR models.
Ranked #2 on Click-Through Rate Prediction on KDD12
1 code implementation • 6 Jul 2022 • Dugang Liu, Pengxiang Cheng, Hong Zhu, Xing Tang, Yanyu Chen, Xiaoting Wang, Weike Pan, Zhong Ming, Xiuqiang He
Tabular data is one of the most common data storage formats behind many real-world web applications such as retail, banking, and e-commerce.
no code implementations • 12 Jun 2022 • Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He
Due to the poor generalization performance of traditional empirical risk minimization (ERM) in the case of distributional shift, Out-of-Distribution (OoD) generalization algorithms receive increasing attention.
no code implementations • 10 May 2022 • Bing Zhao, Jun Li, Hong Zhu
To bridge the performance gap, we propose a novel object-level self-supervised learning method, called Contrastive learning with Downstream background invariance (CoDo).
1 code implementation • ACM SIGSAC Conference on Computer and Communications Security 2021 • Yue Zhao, Hong Zhu, Kai Chen, Shengzhi Zhang
With the knowledge of error-inducing neurons, we propose two methods to fix the errors: the neuron-flip and the neuron-fine-tuning.
1 code implementation • 10 Oct 2021 • Shaohua Wu, Xudong Zhao, Tong Yu, Rongguo Zhang, Chong Shen, Hongli Liu, Feng Li, Hong Zhu, Jiangang Luo, Liang Xu, Xuanwei Zhang
With this method, Yuan 1. 0, the current largest singleton language model with 245B parameters, achieves excellent performance on thousands GPUs during training, and the state-of-the-art results on NLP tasks.
no code implementations • 1 Oct 2021 • Hong Zhu, Ian Bayley
This paper proposes a set of testing strategies for testing machine learning applications in the framework of the datamorphism testing methodology.
no code implementations • 5 Mar 2021 • Chang Liu, Xiaoguang Li, Guohao Cai, Zhenhua Dong, Hong Zhu, Lifeng Shang
It is still an open question to leverage various types of information under the BERT framework.
no code implementations • 15 Dec 2020 • Xinhan Di, Pengqian Yu, Danfeng Yang, Hong Zhu, Changyu Sun, YinDong Liu
In this paper, we propose a multiple-domain model for producing a custom-size furniture layout in the interior scene.
1 code implementation • 15 Dec 2020 • Xinhan Di, Pengqian Yu, Danfeng Yang, Hong Zhu, Changyu Sun, YinDong Liu
We conduct our experiments on the proposed real-world interior layout dataset that contains $191208$ designs from the professional designers.
no code implementations • 4 Aug 2020 • Xinhan Di, Pengqian Yu, Hong Zhu, Lei Cai, Qiuyan Sheng, Changyu Sun
In this paper, we propose an assistive model that supports professional interior designers to produce industrial interior decoration solutions and to meet the personalized preferences of the property owners.
no code implementations • 24 Jun 2020 • Xinhan Di, Pengqian Yu, Hong Zhu, Lei Cai, Qiuyan Sheng, Changyu Sun
In this paper, we propose an adversarial model for producing furniture layout for interior scene synthesis when the interior room is rotated.
1 code implementation • 12 Mar 2020 • Tong Yu, Hong Zhu
This study next reviews major services and toolkits for HPO, comparing their support for state-of-the-art searching algorithms, feasibility with major deep learning frameworks, and extensibility for new modules designed by users.
1 code implementation • 20 Dec 2019 • Hong Zhu, Ian Bayley, Dongmei Liu, Xiaoyu Zheng
This paper focuses on the datamorphism combination strategies by giving their definitions and implementation algorithms.
no code implementations • 10 Dec 2019 • Hong Zhu, Dongmei Liu, Ian Bayley, Rachel Harrison, Fabio Cuzzolin
With the rapid growth of the applications of machine learning (ML) and other artificial intelligence (AI) techniques, adequate testing has become a necessity to ensure their quality.
1 code implementation • 3 Dec 2019 • Zifeng Wang, Hong Zhu, Zhenhua Dong, Xiuqiang He, Shao-Lun Huang
In the time of Big Data, training complex models on large-scale data sets is challenging, making it appealing to reduce data volume for saving computation resources by subsampling.
no code implementations • 25 Oct 2019 • Zhenming Xu, Xin Chen, Ronghan Chen, Xin Li, Hong Zhu
In this work, the face-centered cubic (fcc) anion frameworks were creatively constructed to study the effects of anion charge and lattice volume on the stability of lithium ion occupation and lithium ion migration.
Applied Physics
no code implementations • The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019 2019 • Duohan Liang, Guoliang Fan, Guangfeng Lin, Wanjun Chen, Xiaorong Pan, Hong Zhu
In this paper, we propose a three-stream convolutional neural network (3SCNN) for action recognition from skeleton sequences, which aims to thoroughly and fully exploit the skeleton data by extracting, learning, fusing and inferring multiple motion-related features, including 3D joint positions and joint displacements across adjacent frames as well as oriented bone segments.
Ranked #54 on Skeleton Based Action Recognition on NTU RGB+D
no code implementations • 26 Dec 2018 • Yue Zhao, Hong Zhu, Ruigang Liang, Qintao Shen, Shengzhi Zhang, Kai Chen
In this paper, we presented systematic solutions to build robust and practical AEs against real world object detectors.