Results 71 to 80 of about 33,100 (246)

Dynamic, Unconstrained Optimization of Secreted Enzyme Production in Fed‐Batch Fermentation Using Reinforcement Learning

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Reinforcement learning (RL) has been used to control a wide range of dynamic processes, especially ones that are too complex to model well or have stochastic environmental perturbations. Fed‐batch fermentations are subject to changes in starting cell growth rates and process variations that can affect cell growth and secreted target production.
Sai Harish Uthravalli, Sakib Ferdous, J. Michael Hess, Nigel F. Reuel   +3 more
wiley   +1 more source

Overcoming catastrophic forgetting with hard attention to the task

CoRR, 2018
Includes appendix.
Serrà Julià, Joan, Surís, Dídac, Miron, Marius, Karatzoglou, Alexandros   +3 more
openaire   +4 more sources

Investigating Perceptions of the Eating Disorder Examination‐Questionnaire Among Undergraduate Students: A Qualitative Approach

International Journal of Eating Disorders, EarlyView.
ABSTRACT Objective Quantitative methods that have evaluated the Eating Disorder Examination Questionnaire (EDE‐Q) have found consistent evidence that the original four‐factor structure does not replicate across diverse samples and genders. Emerging evidence in the broader psychology literature shows that qualitative methods can provide nuanced insight ...
Katarina L. Huellemann, Safia Ouédraogo, Janet A. Lydecker, Sarah E. Racine   +3 more
wiley   +1 more source

Pseudorehearsal in value function approximation

, 2017
Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole ...
A Robins, A Robins, B Baddeley, CJ Watkins, J Gama, JL McClelland, JN Tsitsiklis, KP Murphy, M Frean, M Hattori, M McCloskey, R Coop, R Ratcliff, RJ Williams, RM French, RS Sutton, S Adam   +16 more
core   +1 more source

Quantum Continual Learning Overcoming Catastrophic Forgetting

Chinese Physics Letters, 2022
Catastrophic forgetting describes the fact that machine learning models will likely forget the knowledge of previously learned tasks after the learning process of a new one. It is a vital problem in the continual learning scenario and recently has attracted tremendous concern across different communities.
Wenjie Jiang, Zhide Lu, Dong-Ling Deng
openaire   +2 more sources

The Non‐Professional Virtues of the Hospice Volunteer

Journal of Applied Philosophy, EarlyView.
ABSTRACT Volunteers have long played a significant role in hospice care. Much of the care volunteers provide consists of weekly hour‐long in‐home visits. Home‐visiting hospice volunteers are not professionals, nor are they strangers or intimates. Hospice volunteers will not typically face moral dilemmas, nor be called upon to make dramatic decisions ...
Michael B. Gill
wiley   +1 more source

A multifidelity approach to continual learning for physical systems

Machine Learning: Science and Technology
We introduce a novel continual learning method based on multifidelity deep neural networks. This method learns the correlation between the output of previously trained models and the desired output of the model on the current training dataset, limiting ...
Amanda Howard, Yucheng Fu, Panos Stinis
doaj   +1 more source

Mitigating Catastrophic Forgetting in Pest Detection Through Adaptive Response Distillation

Agriculture
Pest detection in agriculture faces the challenge of adapting to new pest species while preserving the ability to recognize previously learned ones. Traditional model fine-tuning approaches often result in catastrophic forgetting, where the acquisition ...
Hongjun Zhang, Zhendong Yin, Dasen Li, Yanlong Zhao   +3 more
doaj   +1 more source

Coping Practices of Small‐ and Medium‐Sized Enterprises Facing Power Asymmetry in Digital Platform Business

Strategic Change, EarlyView.
ABSTRACT Digital platform (DP) enterprises have risen to the top of the global economy by inverting traditional business models. They earn money through matchmaking, transaction facilitation, and efficient orchestration of other stakeholders' resources.
Lukas R. G. Fitz, Jochen Scheeg
wiley   +1 more source

Zero-shot incremental learning using spatial-frequency feature representations

Scientific Reports
Zero-shot incremental learning aims to enable a model to generalize to new classes without forgetting previously learned classes. However, the semantic gap between old and new sample classes can lead to catastrophic forgetting.
Jie Ren, Yang Zhao, Weichuan Zhang, Changming Sun   +3 more
doaj   +1 more source