Results 51 to 60 of about 12,738,743 (318)
On early stopping of stochastic mirror descent method for ill-posed inverse problems
Numerische MathematikIn recent years, stochastic algorithms have been introduced to solve ill-posed inverse problems. These algorithms select a random subset of equations during each iteration, displaying excellent scalability and competitive performance in large-scale ...
Jingfang Huang +3 more
semanticscholar +1 more source
Practical early stopping for adaptive barrier SGD: balancing stochastic speed with validation accuracy [PDF]
Iranian Journal of Numerical Analysis and OptimizationStochastic Gradient Descent (SGD) algorithms based on adaptive barrier functions are highly efficient for large-scale constrained optimization. However, their inherent stochastic nature leads to the critical ”last- iterate problem”, where update noise ...
Abdelouakil Fillali +2 more
doaj +1 more source
Do we need to adjust for interim analyses in a Bayesian adaptive trial design?
BMC Medical Research Methodology, 2020 Background Bayesian adaptive methods are increasingly being used to design clinical trials and offer several advantages over traditional approaches. Decisions at analysis points are usually based on the posterior distribution of the treatment effect ...
Elizabeth G. Ryan +3 more
doaj +1 more source
Early Stopping for Nonparametric Testing
, 2018 To appear in NIPS ...
Meimei Liu 0002, Guang Cheng 0003
openaire +3 more sources
Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification [PDF]
IEEE/IFIP Network Operations and Management SymposiumFederated learning (FL) enables multiple devices to collaboratively train a global model while maintaining data on local servers. Each device trains the model on its local server and shares only the model updates (i.e., gradient weights) during the ...
Nishant S. Gaikwad +5 more
semanticscholar +1 more source
Stopping clinical trials early
BMJ, 2004 Data monitoring committees may have important role H alting high profile trials early has been in the news again this year.1 Legitimate questions have been raised about who decides that a trial should stop early, how they do it, and on what basis they reach such a decision.
openaire +3 more sources
An Empirical Investigation of Early Stopping Optimizations in Proximal Policy Optimization
IEEE Access, 2021 Code-level optimizations, which are low-level optimization techniques used in the implementation of algorithms, have generally been considered as tangential and often do not appear in published pseudo-code of Reinforcement Learning (RL) algorithms ...
Rousslan Fernand Julien Dossa +3 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Febrile neutropenia (FN) is a frequent and serious complication in children receiving cancer therapy. Standardizing FN management across Asia is challenging due to variable healthcare infrastructure, diagnostic capacity, and infection patterns; however, it could improve resource use and patient outcomes.
Joliza Patricia Cañeba +29 more
wiley +1 more source
Symbolic Early Stopping in Neural Sequence Models via Mapper-Induced Symbolic Dynamics
TechnologiesEarly stopping is a standard form of implicit regularization in neural sequence models, but criteria based solely on validation loss can become unstable or weakly informative in noisy, non-stationary, or weakly separated regimes.
Ivan Tomilov +3 more
doaj +1 more source
Unsupervised GAN epoch selection for biomedical data synthesis
Current Directions in Biomedical Engineering, 2023 Supervised Neural Networks are used for segmentation in many biological and biomedical applications. To omit the time-consuming and tiring process of manual labeling, unsupervised Generative Adversarial Networks (GANs) can be used to synthesize labeled ...
Böhland Moritz +3 more
doaj +1 more source