Results 81 to 90 of about 120,084 (296)

Distributed Deep Learning Based on Edge Computing Over Internet of Vehicles: Overview, Applications, and Challenges

IEEE Access
Recently, the internet of vehicles (IoVs), mobile edge computing (MEC), and deep learning have attracted many research attentions in the applications of autonomous driving.
Zhuangxing Lin, Haixia Cui, Yong Liu
doaj   +1 more source

Metaoptimization on a Distributed System for Deep Reinforcement Learning [PDF]

2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), 2019
Training intelligent agents through reinforcement learning is a notoriously unstable procedure. Massive parallelization on GPUs and distributed systems has been exploited to generate a large amount of training experiences and consequently reduce instabilities, but the success of training remains strongly influenced by the choice of the hyperparameters.
Greg Heinrich, Iuri Frosio
openaire   +2 more sources

Why human connection is the true metric of research success

FEBS Open Bio, EarlyView.
Human‐centred mentorship can be shaped by mentor attributes, actions, intrinsic drive and career ambition. Drawing on reflections across Singapore and France, as well as workshop insights from FEBS‐IUBMB ENABLE 2024, this article shows that human‐centred mentorship creates the conditions for sustainable growth, well‐being and retention in research ...
Timothy Lin Yun Tan, Mattias Wei Ren Kon, Xavier Coumoul, Fun Man Fung   +3 more
wiley   +1 more source

A Discrete-event-based Simulator for Distributed Deep Learning

, 2022
New intelligence applications are driving increasing interest in deploying deep neural networks (DNN) in a distributed way. To set up distributed deep learning involves alterations of a great number of the parameter configurations of network/edge devices
Qin, Yana, Liu, Xiaoyan, Tian, Jie, Xu, Zhiwei   +3 more
core   +2 more sources

Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer

Aging and Cancer, EarlyView.
Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss, Alexis C. Wardell, Allison M. Deal, Kirsten A. Nyrop, Allison Ross, Yara G. Abdou, Jeffrey D. Aldrich, Lisa A. Cary, E. Claire Dees, Katherine E. Reeder‐Hayes, Emily M. Ray, Natalia Mitin, Denis Tsygankov   +12 more
wiley   +1 more source

Trinity: Neural Network Adaptive Distributed Parallel Training Method Based on Reinforcement Learning

Algorithms, 2022
Deep learning, with increasingly large datasets and complex neural networks, is widely used in computer vision and natural language processing. A resulting trend is to split and train large-scale neural network models across multiple devices in parallel,
Yan Zeng, Jiyang Wu, Jilin Zhang, Yongjian Ren, Yunquan Zhang   +4 more
doaj   +1 more source

Democratizing Production-Scale Distributed Deep Learning

CoRR, 2018
The interest and demand for training deep neural networks have been experiencing rapid growth, spanning a wide range of applications in both academia and industry. However, training them distributed and at scale remains difficult due to the complex ecosystem of tools and hardware involved.
Minghuang Ma, Hadi Pouransari, Daniel Chao, Saurabh Adya, Santiago Akle Serrano, Yi Qin, Dan Gimnicher, Dominic Walsh   +7 more
openaire   +2 more sources

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

Distributed Compressive Sensing: A Deep Learning Approach [PDF]

IEEE Transactions on Signal Processing, 2016
Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different channels to be jointly sparse. In this paper, we relax this condition. Instead we assume that these sparse vectors depend on each other but that this dependency is unknown. We
Hamid Palangi, Rabab K. Ward, Li Deng 0001   +2 more
openaire   +2 more sources

Profound Leadership Strategies: Transcending the Leadership Crisis in the Age of Artificial Intelligence

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT This article examines the evolving role of organizational leadership amidst the rapid advancements in artificial intelligence (AI). It explores a broadly experienced and documented crisis in leadership, due in part to the disruptive nature of AI and emerging technology.
Rachel Wlodarsky, Davin Carr Chellman
wiley   +1 more source