Results 101 to 110 of about 746,368 (310)

Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation [PDF]

arXiv
Learning curve extrapolation predicts neural network performance from early training epochs and has been applied to accelerate AutoML, facilitating hyperparameter tuning and neural architecture search. However, existing methods typically model the evolution of learning curves in isolation, neglecting the impact of neural network (NN) architectures ...
arxiv  

Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings [PDF]

arXiv, 2019
We propose probabilistic models that can extrapolate learning curves of iterative machine learning algorithms, such as stochastic gradient descent for training deep networks, based on training data with variable-length learning curves. We study instantiations of this framework based on random forests and Bayesian recurrent neural networks.
arxiv  

Phacoemulsification during the learning curve: Risk/benefit analysis [PDF]

, 1993
Helen Seward, R.N. Dalton, Amy Davis
openalex   +1 more source

Open‐source deep‐learning models for segmentation of normal structures for prostatic and gynecological high‐dose‐rate brachytherapy: Comparison of architectures

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background The use of deep learning‐based auto‐contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containing high‐dose‐rate (HDR) brachytherapy treatment scans, leading to poor performance on images ...
Andrew J. Krupien, Yasin Abdulkadir, Dishane C. Luximon, John Charters, Huiming Dong, Jonathan Pham, Dylan O'Connell, Jack Neylon, James M. Lamb   +8 more
wiley   +1 more source

Short-term outcomes of fetoscopic laser surgery for severe twin–twin transfusion syndrome from Taiwan single center experience: Demonstration of learning curve effect on the fetal outcomes

Taiwanese Journal of Obstetrics & Gynecology, 2012
Objective: To evaluate the learning curve effect on fetal outcomes while using fetoscopic laser photocoagulation (FLP) for twin–twin transfusion syndrome (TTTS) as managed by a newly established single center in Taiwan.
Yao-Lung Chang, An-Shine Chao, Shuenn-Dyh Chang, Peter C.C. Hsieh, Chao-Nin Wang   +4 more
doaj   +1 more source

The second two hundred cases of endocapsular phacoemulsification: the learning curve levels off [PDF]

, 1994
Simon Irvine, Ian C. Francis, Medduma B. Kappagoda, Margaret J. Haylen, Stella Alexander, Ralf Schumacher, Kerry Boytell   +6 more
openalex   +1 more source

An extension to the OVH concept for knowledge‐based dose volume histogram prediction in lung tumor volumetric‐modulated arc therapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Volumetric‐modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (PTV) and a simultaneous sparing of organs‐at‐risk (OARs). Particularly in the case of lung tumors, deciding whether it is possible or worth spending more time on further improvements of a treatment
Johann Brand, Juliane Szkitsak, Oliver J. Ott, Christoph Bert, Stefan Speer   +4 more
wiley   +1 more source

A method to benchmark high-dimensional process drift detection [PDF]

arXiv
Process curves are multivariate finite time series data coming from manufacturing processes. This paper studies machine learning that detect drifts in process curve datasets. A theoretic framework to synthetically generate process curves in a controlled way is introduced in order to benchmark machine learning algorithms for process drift detection.
arxiv  

Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single‐center retrospective study in China

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC). Methods Postoperative PDAC patients were retrospectively selected, all of whom had undergone preoperative CT imaging and surgery. Both patients with resectable or borderline‐resectable pancreatic cancer met
Xinze Du, Yongsu Ma, Kexin Wang, Xiejian Zhong, Jianxin Wang, Xiaodong Tian, Xiaoying Wang, Yinmo Yang   +7 more
wiley   +1 more source

A Bayesian Learning Model Fitted to a Variety of Empirical Learning Curves [PDF]

, 1995
Boyan Jovanovic, Yaw Nyarko, Griliches
openalex   +1 more source