Results 71 to 80 of about 16,800,197 (383)

To learn or not to learn ......

, 1996
Multiagent systems in which agents interact with each other are now being proposed as a solution to many problems which can be grouped together under the “distributed problem solving” umbrella. For such systems to work properly, it is necessary that agents learn from their environment and adapt their behaviour accordingly.
openaire   +3 more sources

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

Optimization of the Asymptotic Property of Mutual Learning Involving an Integration Mechanism of Ensemble Learning [PDF]

, 2007
We propose an optimization method of mutual learning which converges into the identical state of optimum ensemble learning within the framework of on-line learning, and have analyzed its asymptotic property through the statistical mechanics method.The proposed model consists of two learning steps: two students independently learn from a teacher, and ...
arxiv   +1 more source

Unsupervised Representation Learning to Aid Semi-Supervised Meta Learning [PDF]

arXiv, 2023
Few-shot learning or meta-learning leverages the data scarcity problem in machine learning. Traditionally, training data requires a multitude of samples and labeling for supervised learning. To address this issue, we propose a one-shot unsupervised meta-learning to learn the latent representation of the training samples. We use augmented samples as the
arxiv  

Aerial LIDAR Processing to Prevent Wildfires [PDF]

, 2021
This project looks at the use of Aerial LIDAR data to prevent wildfires. Aerial LIDAR can be captured by a drone or airplane and is much more efficient then using ground crews.
Flahive, Keegan
core   +1 more source

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

Conscientization, Dialogue and Collaborative Problem Based Learning

Journal of Problem Based Learning in Higher Education, 2013
It has been argued that Paulo Freire’s concept of conscientization, where critical awareness and engagement are central to a problem-posing pedagogy, provides the philosophical principles to underpin Problem Based Learning (PBL). By using dialogue groups
Conscientization, Dialogue and Collaborative Problem Based Learning
doaj  

Dex: Incremental Learning for Complex Environments in Deep Reinforcement Learning [PDF]

arXiv, 2017
This paper introduces Dex, a reinforcement learning environment toolkit specialized for training and evaluation of continual learning methods as well as general reinforcement learning problems. We also present the novel continual learning method of incremental learning, where a challenging environment is solved using optimal weight initialization ...
arxiv  

Semi-supervised Learning on Large Graphs: is Poisson Learning a Game-Changer? [PDF]

arXiv, 2022
We explain Poisson learning on graph-based semi-supervised learning to see if it could avoid the problem of global information loss problem as Laplace-based learning methods on large graphs. From our analysis, Poisson learning is simply Laplace regularization with thresholding, cannot overcome the problem.
arxiv  

Microglial reprogramming: a potential new frontier in enhancing immunotherapy for melanoma brain metastasis

Molecular Oncology, EarlyView.
Microglia act as tumor suppressors during brain metastasis colonization but shift to a tumor‐promoting role after melanoma brain metastases form. NF‐κB/RelA signaling emerges as a key driver of this phenotypic shift. Targeting this pathway reprograms microglia into a pro‐inflammatory state, enhancing antitumor immunity and immune checkpoint inhibitor ...
Noam Savion‐Gaiger, Dorin Bar‐Ziv, Harriet Kluger   +2 more
wiley   +1 more source