Results 41 to 50 of about 549,366 (277)

Statistical Mechanics of Linear and Nonlinear Time-Domain Ensemble Learning

, 2006
Conventional ensemble learning combines students in the space domain. In this paper, however, we combine students in the time domain and call it time-domain ensemble learning.
Cesa-Bianchi N., Freund Y., Freund Y., Hara K., Inoue J. I., Krogh A., Miyoshi S., Miyoshi S., Miyoshi S., Miyoshi S., Nishimori H., Saad D., Urbanczik R.   +12 more
core   +1 more source

Domain Generalization with Domain-Specific Aggregation Modules [PDF]

, 2019
Visual recognition systems are meant to work in the real world. For this to happen, they must work robustly in any visual domain, and not only on the data used during training. Within this context, a very realistic scenario deals with domain generalization, i.e.
D'Innocente, Antonio, Caputo, Barbara
openaire   +2 more sources

Implicit Sharpness-Aware Minimization for Domain Generalization

Remote Sensing
Domain generalization (DG) aims to learn knowledge from multiple related domains to achieve a robust generalization performance in unseen target domains, which is an effective approach to mitigate domain shift in remote sensing image classification ...
Mingrong Dong, Yixuan Yang, Kai Zeng, Qingwang Wang, Tao Shen   +4 more
doaj   +1 more source

An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset

Journal of Imaging, 2021
This work aims at developing a generalizable Magnetic Resonance Imaging (MRI) reconstruction method in the meta-learning framework. Specifically, we develop a deep reconstruction network induced by a learnable optimization algorithm (LOA) to solve the ...
Wanyu Bian, Yunmei Chen, Xiaojing Ye, Qingchao Zhang   +3 more
doaj   +1 more source

Domain-adversarial neural networks to address the appearance variability of histopathology images

, 2017
Preparing and scanning histopathology slides consists of several steps, each with a multitude of parameters. The parameters can vary between pathology labs and within the same lab over time, resulting in significant variability of the tissue appearance ...
Eppenhof, Koen A. J., Lafarge, Maxime W., Moeskops, Pim, Pluim, Josien P. W., Veta, Mitko   +4 more
core   +1 more source

Why and When Are Evidence‐Based Interventions Adopted in Paediatric Supportive Care? A Qualitative Exploration of the Determinants of Photobiomodulation Implementation

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Oral mucositis is a common and debilitating side effect of childhood cancer and stem cell transplant treatments. It affects the quality of life of children and young people (CYP) and places a strain on services. Photobiomodulation is recommended for oral mucositis prevention in international guidance but is poorly implemented in UK ...
Claudia Heggie, Kara A. Gray‐Burrows, Peter F. Day, Bob Phillips, Carl A. Thompson   +4 more
wiley   +1 more source

Polyp Generalization via Diversifying Style at Feature-Level Space

Applied Sciences
In polyp segmentation, the latest notable topic revolves around polyp generalization, which aims to develop deep learning-based models capable of learning from single or multiple source domains and applying this knowledge to unseen datasets.
Sahadev Poudel, Sang-Woong Lee
doaj   +1 more source

On the Importance of Attention and Augmentations for Hypothesis Transfer in Domain Adaptation and Generalization

Sensors, 2023
Unsupervised domain adaptation (UDA) aims to mitigate the performance drop due to the distribution shift between the training and testing datasets. UDA methods have achieved performance gains for models trained on a source domain with labeled data to a ...
Rajat Sahay, Georgi Thomas, Chowdhury Sadman Jahan, Mihir Manjrekar, Dan Popp, Andreas Savakis   +5 more
doaj   +1 more source

Dynamic Domain Generalization

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Domain generalization (DG) is a fundamental yet very challenging research topic in machine learning. The existing arts mainly focus on learning domain-invariant features with limited source domains in a static model. Unfortunately, there is a lack of training-free mechanism to adjust the model when generalized to the agnostic target domains.
Sun, Zhishu, Shen, Zhifeng, Lin, Luojun, Yu, Yuanlong, Yang, Zhifeng, Yang, Shicai, Chen, Weijie   +6 more
openaire   +2 more sources

Real‐World Pediatric Blinatumomab Administration: Access to Outpatient Care Delivery and Impact of a Hospital‐Dispensed Model

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Blinatumomab has been shown to be highly effective for patients with pediatric B‐ALL and has recently become standard of care therapy. Due to its past use in the clinical trial setting, there is limited information available about real‐world administration.
Katelyn Oranges, Kelly A. Duffy, Sara McDonough, Evelyn Kurpiewski, R. Jennifer Randall, Allison Barz Leahy, Haley M. Newman, Joyce P. Lee, Stephen P. Hunger, Anne F. Reilly, David T. Teachey, Susan R. Rheingold, Daniel J. Zheng   +12 more
wiley   +1 more source