Search Results for author: Hong Zhu

Found 30 papers, 11 papers with code

Confidence-Aware Multi-Field Model Calibration

no code implementations27 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.

User-Centric Evaluation of ChatGPT Capability of Generating R Program Code

no code implementations5 Feb 2024 Tanha Miah, Hong Zhu

The evaluation takes a multiple attempt process in which the tester tries to complete the code generation task through a number of attempts until a satisfactory solution is obtained or gives up after a fixed number of maximal attempts.

Code Generation

Efficient LLM inference solution on Intel GPU

no code implementations19 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.

Management

Robust Long-Tailed Learning via Label-Aware Bounded CVaR

no code implementations29 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.

A Scenario-Based Functional Testing Approach to Improving DNN Performance

no code implementations13 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.

Transfer Learning

Differential Privacy May Have a Potential Optimization Effect on Some Swarm Intelligence Algorithms besides Privacy-preserving

no code implementations30 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).

Metaheuristic Optimization Privacy Preserving

Contrastive Multi-view Framework for Customer Lifetime Value Prediction

no code implementations26 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.

Contrastive Learning Marketing +1

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models

1 code implementation19 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.

Music Recommendation Recommendation Systems +1

OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction

1 code implementation9 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.

Click-Through Rate Prediction Recommendation Systems

DIWIFT: Discovering Instance-wise Influential Features for Tabular Data

1 code implementation6 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.

feature selection

Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms

no code implementations12 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.

regression

CoDo: Contrastive Learning with Downstream Background Invariance for Detection

no code implementations10 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).

Contrastive Learning Data Augmentation +6

AI-Lancet: Locating Error-inducing Neurons to Optimize Neural Networks

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.

Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning

1 code implementation10 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.

Few-Shot Learning Language Modelling +1

Discovering Boundary Values of Feature-based Machine Learning Classifiers through Exploratory Datamorphic Testing

no code implementations1 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.

BIG-bench Machine Learning

End-to-end Generative Floor-plan and Layout with Attributes and Relation Graph

1 code implementation15 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.

Relation

Deep Layout of Custom-size Furniture through Multiple-domain Learning

no code implementations15 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.

Structural Plan of Indoor Scenes with Personalized Preferences

no code implementations4 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.

Graph Generation

Adversarial Model for Rotated Indoor Scenes Planning

no code implementations24 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.

Hyper-Parameter Optimization: A Review of Algorithms and Applications

1 code implementation12 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.

Morphy: A Datamorphic Software Test Automation Tool

1 code implementation20 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.

Test

Datamorphic Testing: A Methodology for Testing AI Applications

no code implementations10 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.

BIG-bench Machine Learning Face Recognition

Less Is Better: Unweighted Data Subsampling via Influence Function

1 code implementation3 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.

General Classification Image Classification +3

Anion charge-lattice volume dependent Li ion migration in compounds with the face-centered cubic anion frameworks

no code implementations25 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

Three-Stream Convolutional Neural Network With Multi-Task and Ensemble Learning for 3D Action Recognition

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.

Ensemble Learning Skeleton Based Action Recognition

Seeing isn't Believing: Practical Adversarial Attack Against Object Detectors

no code implementations26 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.

Adversarial Attack Autonomous Driving +1

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