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检索条件"机构=Research Center of Machine Learning and Data Analysis"
307 条 记 录,以下是91-100 订阅
排序:
RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement
arXiv
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arXiv 2023年
作者: Koehler, Gregor Wald, Tassilo Ulrich, Constantin Zimmerer, David Jaeger, Paul F. Franke, Jörg K.H. Kohl, Simon Isensee, Fabian Maier-Hein, Klaus H. Heidelberg Division of Medical Image Computing Germany Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Helmholtz Imaging DKFZ Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Interactive Machine Learning Group DKFZ Applied Computer Vision Lab DKFZ Machine Learning Lab University of Freiburg Freiburg Germany London United Kingdom Pattern Analysis and Learning Group Heidelberg University Hospital Heidelberg Germany
Despite the remarkable success of deep learning systems over the last decade, a key difference still remains between neural network and human decision-making: As humans, we can not only form a decision on the spot, bu... 详细信息
来源: 评论
Deep Reinforcement learning for Beam Angle Optimization of Intensity-Modulated Radiation Therapy
arXiv
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arXiv 2023年
作者: Bao, Peng Wang, Gong Yang, Ruijie Dong, Bin The Center for Data Science Peking University the Department of Radiation Oncology Peking University Third Hospital Beijing China The Department of Radiation Oncology Peking University Third Hospital Beijing China Beijing International Center for Mathematical Research Center for Machine Learning Research National Biomedical Imaging Center Peking University Beijing China
Objective: Intensity-modulated radiation therapy (IMRT) beam angle optimization (BAO) is a challenging combinatorial optimization problem that is NP-hard. In this study, we aim to develop a personalized BAO algorithm ... 详细信息
来源: 评论
Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network research
arXiv
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arXiv 2024年
作者: Hille, Tobias Stubbemann, Maximilian Hanika, Tom Knowledge & Data Engineering Group University of Kassel Kassel Germany Interdisciplinary Research Center for Information System Design University of Kassel Kassel Germany Information Systems and Machine Learning Lab University of Hildesheim Hildesheim Germany Institute of Computer Science University of Hildesheim Hildesheim Germany
Difficulties in replication and reproducibility of empirical evidences in machine learning research have become a prominent topic in recent years. Ensuring that machine learning research results are sound and reliable... 详细信息
来源: 评论
Marine Predators Algorithm for Energy Scheduling Problem Using Renewable Energy
Marine Predators Algorithm for Energy Scheduling Problem Usi...
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Cyber Resilience (ICCR), International Conference on
作者: Sharif Naser Makhadmeh Ammar Kamal Abasi Mohammed Azmi Al-Betar Department of Data Science and Artificial Intelligence University of Petra Amman Jordan Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi United Arab Emirates Artificial Intelligence Research Center (AIRC) Ajman University Ajman United Arab Emirates
The Energy Scheduling Problem (ESP) involves scheduling smart home appliances based on electricity pricing schemes. This entails adjusting the timing of operations for these appliances across different periods. The pr... 详细信息
来源: 评论
BIM: Improving Graph Neural Networks with Balanced Influence Maximization
BIM: Improving Graph Neural Networks with Balanced Influence...
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International Conference on data Engineering
作者: Wentao Zhang Xinyi Gao Ling Yang Meng Cao Ping Huang Jiulong Shan Hongzhi Yin Bin Cui Center for Machine Learning Research Peking University Institute of Advanced Algorithms Research Shanghai National Engineering Labratory for Big Data Analytics and Applications The University of Queensland Australia Key Lab of High Confidence Software Technologies Peking University Apple Inc. Institute of Computational Social Science Peking University Qingdao
The imbalanced data classification problem has aroused lots of concerns from both academia and industry since data imbalance is a widespread phenomenon in many real-world scenarios. Although this problem has been well... 详细信息
来源: 评论
Enhancing Predictive Imaging Biomarker Discovery Through Treatment Effect analysis
Enhancing Predictive Imaging Biomarker Discovery Through Tre...
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IEEE Workshop on Applications of Computer Vision (WACV)
作者: Shuhan Xiao Lukas Klein Jens Petersen Philipp Vollmuth Paul F. Jaeger Klaus H. Maier-Hein German Cancer Research Center (DKFZ) Heidelberg Division of Medical Image Computing Germany Faculty of Mathematics and Computer Science Heidelberg University Germany DKFZ Heidelberg Interactive Machine Learning Group Germany Institute for Machine Learning ETH Zürich Switzerland DKFZ Heidelberg Helmholtz Imaging Germany Division for Computational Radiology Clinical AI (CCIBonn.ai) Clinic for Neuroradiology University Hospital Bonn Germany Medical Faculty Bonn University of Bonn Germany Department of Radiation Oncology Pattern Analysis and Learning Group Heidelberg University Hospital Germany
Identifying predictive covariates, which forecast individual treatment effectiveness, is crucial for decision-making across different disciplines such as personalized medicine. These covariates, referred to as biomark... 详细信息
来源: 评论
Improving generative model-based unfolding with Schrödinger bridges
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Physical Review D 2024年 第7期109卷 076011-076011页
作者: Sascha Diefenbacher Guan-Horng Liu Vinicius Mikuni Benjamin Nachman Weili Nie Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Autonomous Control and Decision Systems Laboratory Georgia Institute of Technology Atlanta Georgia 30332 USA National Energy Research Scientific Computing Center Berkeley Lab Berkeley California 94720 USA Berkeley Institute for Data Science University of California Berkeley California 94720 USA Machine Learning Research Group NVIDIA Research
machine learning-based unfolding has enabled unbinned and high-dimensional differential cross section measurements. Two main approaches have emerged in this research area; one based on discriminative models and one ba... 详细信息
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Double variance reduction: a smoothing trick for composite optimization problems without first-order gradient  24
Double variance reduction: a smoothing trick for composite o...
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Proceedings of the 41st International Conference on machine learning
作者: Hao Di Haishan Ye Yueling Zhang Xiangyu Chang Guang Dai Ivor W. Tsang Center for Intelligent Decision-Making and Machine Learning School of Management Xi'an Jiaotong University China and SGIT AI Lab State Grid Corporation of China International Business School Beijing Foreign Studies University Beijing China Center for Intelligent Decision-Making and Machine Learning School of Management Xi'an Jiaotong University China SGIT AI Lab State Grid Corporation of China CFAR and IHPC Agency for Science Technology and Research (A*STAR) Singapore and College of Computing and Data Science NTU Singapore
Variance reduction techniques are designed to decrease the sampling variance, thereby accelerating convergence rates of first-order (FO) and zeroth-order (ZO) optimization methods. However, in composite optimization p...
来源: 评论
ReInform: Selecting paths with reinforcement learning for contextualized link prediction
arXiv
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arXiv 2022年
作者: Speranskaya, Marina Methias, Sameh Roth, Benjamin Center for Information and Language Processing LMU Munich Germany Technical University of Munich Munich Germany Research Group Data Mining and Machine Learning University of Vienna Vienna Austria
We propose to use reinforcement learning to inform transformer-based contextualized link prediction models by providing paths that are most useful for predicting the correct answer. This is in contrast to previous app... 详细信息
来源: 评论
Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series
Back to the Future: Challenges of Sparse and Irregular M...
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Workshop on Longitudinal Disease Tracking and Modeling with Medical Images and data, LDTM 2024, 5th International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2024, 1st Workshop on machine learning for Multimodal/-sensor Healthcare data, ML4MHD2024 and Workshop on Multimodal learning and Fusion Across Scales for Clinical Decision Support, ML-CDS 2024 held in conjunction with the 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024
作者: Disch, Nico Albert Peretzke, Robin Roy, Saikat Ulrich, Constantin Zimmerer, David Stiefelhagen, Rainer Kleesiek, Jens Maier-Hein, Klaus Division of Medical Image Computing German Cancer Research Center Heidelberg Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Faculty of Mathematics and Computer Science University of Heidelberg Heidelberg Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Karlsruhe Institute of Technology Karlsruhe Germany University Hospital Essen Essen Germany University Hospital Essen West German Cancer Center Essen Essen Germany Medical Faculty Heidelberg University of Heidelberg Heidelberg Germany
In longitudinal medical image analysis, most work focuses on regularly sampled images, or on tasks like regression or classification. However, in the clinical context, images are frequently generated irregularly due t... 详细信息
来源: 评论