Search Results for author: Jinze Li

Found 4 papers, 2 papers with code

MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation

1 code implementation29 Feb 2024 Jinfeng Xu, Zheyu Chen, Shuo Yang, Jinze Li, Hewei Wang, Edith C. -H. Ngai

It utilizes multimodal information to alleviate the data sparsity problem in recommendation systems, thus improving recommendation accuracy.

Multimodal Recommendation Self-Supervised Learning

Bayesian Evidential Learning for Few-Shot Classification

no code implementations19 Jul 2022 Xiongkun Linghu, Yan Bai, Yihang Lou, Shengsen Wu, Jinze Li, Jianzhong He, Tao Bai

Few-Shot Classification(FSC) aims to generalize from base classes to novel classes given very limited labeled samples, which is an important step on the path toward human-like machine learning.

Classification Metric Learning +1

Memory-Based Label-Text Tuning for Few-Shot Class-Incremental Learning

no code implementations3 Jul 2022 Jinze Li, Yan Bai, Yihang Lou, Xiongkun Linghu, Jianzhong He, Shaoyun Xu, Tao Bai

The difficulties are that training on a sequence of limited data from new tasks leads to severe overfitting issues and causes the well-known catastrophic forgetting problem.

Few-Shot Class-Incremental Learning Incremental Learning

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

20 code implementations19 Nov 2019 Zhaohui Zheng, Ping Wang, Wei Liu, Jinze Li, Rongguang Ye, Dongwei Ren

By incorporating DIoU and CIoU losses into state-of-the-art object detection algorithms, e. g., YOLO v3, SSD and Faster RCNN, we achieve notable performance gains in terms of not only IoU metric but also GIoU metric.

object-detection Object Detection +1

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