4 papers
Bringing Generative Learning to Representation Learning: Self-Supervised Transfer Learning as Distribution Matching
Yuling Jiao, Wensen Ma, Defeng Sun +2
Most self-supervised learning objectives defend against collapse but leave the target representation law unspecified. We formulate representation learning as Distribution Matching…
CluBear: A Subsampling Package for Interactive Statistical Analysis with Massive Data on A Single Machine
Ke Xu, Yingqiu Zhu, Yijing Liu +1
This article introduces CluBear, a Python-based open-source package for interactive massive data analysis. The key feature of CluBear is that it enables users to conduct convenient…
Mini-batch Gradient Descent with Buffer
Haobo Qi, Du Huang, Yingqiu Zhu +2
In this paper, we studied a buffered mini-batch gradient descent (BMGD) algorithm for training complex model on massive datasets. The algorithm studied here is designed for fast tr…
Improved Naive Bayes with Mislabeled Data
Qianhan Zeng, Yingqiu Zhu, Xuening Zhu +5
Labeling mistakes are frequently encountered in real-world applications. If not treated well, the labeling mistakes can deteriorate the classification performances of a model serio…