research
∙
08/17/2023
MixBag: Bag-Level Data Augmentation for Learning from Label Proportions
Learning from label proportions (LLP) is a promising weakly supervised l...
share
research
∙
02/17/2023
Learning from Label Proportion with Online Pseudo-Label Decision by Regret Minimization
This paper proposes a novel and efficient method for Learning from Label...
research
∙
03/17/2022
Revealing Reliable Signatures by Learning Top-Rank Pairs
Signature verification, as a crucial practical documentation analysis ta...
research
∙
03/17/2022
Optimal Rejection Function Meets Character Recognition Tasks
In this paper, we propose an optimal rejection method for rejecting ambi...
research
∙
07/20/2021
Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
Cell detection is an essential task in cell image analysis. Recent deep ...
research
∙
09/19/2020
AAA: Adaptive Aggregation of Arbitrary Online Trackers with Theoretical Performance Guarantee
For visual object tracking, it is difficult to realize an almighty onlin...
research
∙
05/31/2020
Theory and Algorithms for Shapelet-based Multiple-Instance Learning
We propose a new formulation of Multiple-Instance Learning (MIL), in whi...
research
∙
11/14/2019
An Application of Multiple-Instance Learning to Estimate Generalization Risk
We focus on several learning approaches that employ max-operator to eval...
research
∙
11/20/2018