Search Results for author: Xiawei Guo

Found 7 papers, 4 papers with code

Fast Learning with Nonconvex L1-2 Regularization

no code implementations29 Oct 2016 Quanming Yao, James T. Kwok, Xiawei Guo

In this paper, we show that a closed-form solution can be derived for the proximal step associated with this regularizer.

Sparse Learning

Differential Private Stack Generalization with an Application to Diabetes Prediction

no code implementations23 Nov 2018 Quanming Yao, Xiawei Guo, James T. Kwok, WeiWei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang

To meet the standard of differential privacy, noise is usually added into the original data, which inevitably deteriorates the predicting performance of subsequent learning algorithms.

Diabetes Prediction Ensemble Learning +3

AutoSpeech 2020: The Second Automated Machine Learning Challenge for Speech Classification

no code implementations25 Oct 2020 Jingsong Wang, Tom Ko, Zhen Xu, Xiawei Guo, Souxiang Liu, Wei-Wei Tu, Lei Xie

The AutoSpeech challenge calls for automated machine learning (AutoML) solutions to automate the process of applying machine learning to speech processing tasks.

AutoML BIG-bench Machine Learning +1

Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction

1 code implementation16 Aug 2021 Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao, Weinan Zhang, Xiawei Guo, Jian Shen, Yanru Qu, Jieli Lu, Min Xu, Yu Xu, Tiange Wang, Mian Li, Wei-Wei Tu, Yong Yu, Yufang Bi, Weiqing Wang, Guang Ning

To tackle the above challenges, we employ gradient boosting decision trees (GBDT) to handle data heterogeneity and introduce multi-task learning (MTL) to solve data insufficiency.

Diabetes Prediction Multi-Task Learning

TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction

1 code implementation20 Aug 2021 Xiawei Guo, Yuhan Quan, Huan Zhao, Quanming Yao, Yong Li, WeiWei Tu

Tabular data prediction (TDP) is one of the most popular industrial applications, and various methods have been designed to improve the prediction performance.

Exploring Model Dynamics for Accumulative Poisoning Discovery

1 code implementation6 Jun 2023 Jianing Zhu, Xiawei Guo, Jiangchao Yao, Chao Du, Li He, Shuo Yuan, Tongliang Liu, Liang Wang, Bo Han

In this paper, we dive into the perspective of model dynamics and propose a novel information measure, namely, Memorization Discrepancy, to explore the defense via the model-level information.

Memorization

Combating Bilateral Edge Noise for Robust Link Prediction

1 code implementation NeurIPS 2023 Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han

To address this dilemma, we propose an information-theory-guided principle, Robust Graph Information Bottleneck (RGIB), to extract reliable supervision signals and avoid representation collapse.

Denoising Link Prediction +1

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