- Highly Efficient Representation and Active Learning Framework and ...🔍
- Highly Efficient Representation and Active Learning Framework for ...🔍
- [PDF] Highly Efficient Representation and Active Learning ...🔍
- Publications🔍
- Patrick Bangert's lab🔍
- an effective and scalable active learning framework for GNNs on ...🔍
- [PDF] An Efficient Active Learning Framework for New Relation ...🔍
- Exploring Minimally Sufficient Representation in Active Learning...🔍
Highly Efficient Representation and Active Learning Framework and ...
Highly Efficient Representation and Active Learning Framework and ...
We propose a highly data-efficient active learning framework for image classification. Our novel framework combines: (1) unsupervised representation learning.
Highly Efficient Representation and Active Learning Framework and ...
We propose a highly data-efficient active learning framework for image classifi- cation. Our novel framework combines: (1) unsupervised representation learning.
Highly Efficient Representation and Active Learning Framework for ...
We propose a highly data-efficient classification and active learning framework for classifying chest X-rays. It is based on (1) unsupervised representation ...
Highly Efficient Representation and Active Learning Framework and ...
We propose a highly data-efficient active learning framework for image classifi- cation. Our novel framework combines: (1) unsupervised ...
Highly Efficient Representation and Active Learning Framework and ...
Heng Hao, Hankyu Moon, Sima Didari, Jae Oh Woo, Patrick Bangert. We propose a highly data-efficient active learning framework for image ...
Highly Efficient Representation and Active Learning Framework for ...
It is based on (1) unsupervised representation learning of a CNN (Convolutional Neural Network) and (2) the GP (Gaussian Process) method. The ...
[PDF] Highly Efficient Representation and Active Learning ...
We propose a highly data-efficient active learning framework for image classification. Our novel framework combines: (1) unsupervised representation learning ...
Highly Efficient Representation and Active Learning Framework and ...
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification (preprint). Heng Hao, H. Moon ...
Highly Efficient Representation and Active Learning Framework and ...
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification. Dec 6, 2021 ...
Publications - jaeohwoo - Google Sites
(with Heng Hao, Sima Didari, Hankyu Moon, and Patrick Bangert) Highly Efficient Representation and Active Learning Framework for Imbalanced Data and Its ...
Patrick Bangert's lab - ResearchGate
We propose a highly data-efficient classification and active learning framework for classifying chest X-rays. It is based on (1) unsupervised representation ...
an effective and scalable active learning framework for GNNs on ...
Active learning for graph neural networks (GNNs) aims to select B nodes to label for the best possible GNN performance.
[PDF] An Efficient Active Learning Framework for New Relation ...
It is felt active learning is a good direction to do relation extraction and presents a more efficient active learning framework that shows a substantial ...
Exploring Minimally Sufficient Representation in Active Learning...
... effective AL for medical image classification. This work proposes an efficient AL framework based on off-the-shelf self-supervised learning ...
Focus on informative graphs! Semi-supervised active learning for ...
... framework GraphSpa for graph-level classification, which develops an effective fusion selection strategy from both local similarity and global semantic ...
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification ... We propose a highly data- ...
ActiveMatch: End-To-End Semi-Supervised Active Representation ...
Semi-supervised learning (SSL) is an efficient framework that can train models with both labeled and unlabeled data, but may generate ambiguous and ...
Exploring Minimally Sufficient Representation in Active Learning ...
This work proposes an efficient AL framework based on off-the-shelf self-supervised learning models, complemented by a label-irrelevant patch augmentation ...
Is there an efficient representation for ordinal numbers?
Though this is language agnostic, I take the freedom to show a proposal how to do this in Java, should be easily transferable to any ...
Active representation learning for general task space with...
... efficient solution under our general framework. That is, the solution q from [2] ... I have a follow up question about Q2: I understand that [2] can be seen as an ...