Results 121 to 130 of about 2,291,078 (312)

Active Reinforcement Learning -- A Roadmap Towards Curious Classifier Systems for Self-Adaptation [PDF]

arXiv, 2022
Intelligent systems have the ability to improve their behaviour over time taking observations, experiences or explicit feedback into account. Traditional approaches separate the learning problem and make isolated use of techniques from different field of machine learning such as reinforcement learning, active learning, anomaly detection or transfer ...
arxiv  

Time, the final frontier

Molecular Oncology, EarlyView.
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain, Michal Dibus, Omkar Joshi, Guillaume Jacquemet   +3 more
wiley   +1 more source

Active learning applied to automated physical systems increases the rate of discovery

Scientific Reports, 2023
Active machine learning is widely used in computational studies where repeated numerical simulations can be conducted on high performance computers without human intervention.
Michael D. Shields, Kurtis Gurley, Ryan Catarelli, Mohit Chauhan, Mariel Ojeda-Tuz, Forrest J. Masters   +5 more
doaj   +1 more source

Activized Learning: Transforming Passive to Active with Improved Label Complexity [PDF]

arXiv, 2011
We study the theoretical advantages of active learning over passive learning. Specifically, we prove that, in noise-free classifier learning for VC classes, any passive learning algorithm can be transformed into an active learning algorithm with asymptotically strictly superior label complexity for all nontrivial target functions and distributions.
arxiv  

Machine learning assisted sorting of active microswimmers

The Journal of Chemical Physics
Active matter systems, being in a non-equilibrium state, exhibit complex behaviors, such as self-organization, giving rise to emergent phenomena. There are many examples of active particles with biological origins, including bacteria and spermatozoa, or with artificial origins, such as self-propelled swimmers and Janus particles.
Abdolhalim Torrik, Mahdi Zarif
openaire   +3 more sources

Beyond digital twins: the role of foundation models in enhancing the interpretability of multiomics modalities in precision medicine

FEBS Open Bio, EarlyView.
This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi, Xin Gao, Takashi Gojobori   +2 more
wiley   +1 more source

Convergence between emerging technologies and active methodologies in the university

Journal of Technology and Science Education
In today's educational environment, the convergence of emerging technologies and active methodologies has become a fundamental driver of change in university education.
Oscar-Yecid Aparicio-Gómez, Olga-Lucia Ostos-Ortiz, Constanza Abadía-García   +2 more
doaj   +1 more source

Active Learning with Neural Networks: Insights from Nonparametric Statistics [PDF]

arXiv, 2022
Deep neural networks have great representation power, but typically require large numbers of training examples. This motivates deep active learning methods that can significantly reduce the amount of labeled training data. Empirical successes of deep active learning have been recently reported in the literature, however, rigorous label complexity ...
arxiv  

Mapping Hsp104 interactions using cross‐linking mass spectrometry

FEBS Open Bio, EarlyView.
This study examines how cross‐linking mass spectrometry can be utilized to analyze ATP‐induced conformational changes in Hsp104 and its interactions with substrates. We developed an analytical pipeline to distinguish between intra‐ and inter‐subunit contacts within the hexameric homo‐oligomer and discovered contacts between Hsp104 and a selected ...
Kinga Westphal, Karolina Michalska, Andrzej Joachimiak, Lukasz A. Joachimiak   +3 more
wiley   +1 more source

Deep Active Learning with a Neural Architecture Search [PDF]

arXiv, 2018
We consider active learning of deep neural networks. Most active learning works in this context have focused on studying effective querying mechanisms and assumed that an appropriate network architecture is a priori known for the problem at hand. We challenge this assumption and propose a novel active strategy whereby the learning algorithm searches ...
arxiv