Results 151 to 160 of about 9,609,759 (372)
Augmented Q Imitation Learning (AQIL) [PDF]
arXiv, 2020 The study of unsupervised learning can be generally divided into two categories: imitation learning and reinforcement learning. In imitation learning the machine learns by mimicking the behavior of an expert system whereas in reinforcement learning the machine learns via direct environment feedback.
arxiv
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 +4 more
wiley +1 more source
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 +7 more
wiley +1 more source
AutoCompete: A Framework for Machine Learning Competition [PDF]
arXiv, 2015 In this paper, we propose AutoCompete, a highly automated machine learning framework for tackling machine learning competitions. This framework has been learned by us, validated and improved over a period of more than two years by participating in online machine learning competitions.
arxiv
ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems
, 2014 Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest.
Aparna Lakshmiratan +10 more
core
A Python package for fast GPU‐based proton pencil beam dose calculation
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Purpose Open‐source GPU‐based Monte Carlo (MC) proton dose calculation algorithms provide high speed and unparalleled accuracy but can be complex to integrate with new applications and remain slower than GPU‐based pencil beam (PB) methods, which sacrifice some physical accuracy for sub‐second plan calculation.
Mahasweta Bhattacharya +4 more
wiley +1 more source
Joint Training of Deep Boltzmann Machines [PDF]
arXiv, 2012 We introduce a new method for training deep Boltzmann machines jointly. Prior methods require an initial learning pass that trains the deep Boltzmann machine greedily, one layer at a time, or do not perform well on classifi- cation tasks.
arxiv