AIMC Topic: Learning

Clear Filters Showing 491 to 500 of 1397 articles

Capturing advanced human cognitive abilities with deep neural networks.

Trends in cognitive sciences Nov 2, 2022
How can artificial neural networks capture the advanced cognitive abilities of pioneering scientists? I suggest they must learn to exploit human-invented tools of thought and human-like ways of using them, and must engage in explicit goal-directed pr...
Humans Neural Networks, Computer Learning Cognition Problem Solving
View on PubMed DOI

Developments in Artificial Intelligence for Ophthalmology: Federated Learning.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) Nov 1, 2022
Humans Artificial Intelligence Machine Learning Learning Ophthalmology
View on PubMed DOI

Prediction of drug-target interactions through multi-task learning.

Scientific reports Oct 31, 2022
Identifying the binding between the target proteins and molecules is essential in drug discovery. The multi-task learning method has been introduced to facilitate knowledge sharing among tasks when the amount of information for each task is small. Ho...
Machine Learning Learning Drug Discovery Proteins Ligands
View on PubMed DOI

ReLMole: Molecular Representation Learning Based on Two-Level Graph Similarities.

Journal of chemical information and modeling Oct 27, 2022
Molecular representation is a critical part of various prediction tasks for physicochemical properties of molecules and drug design. As graph notations are common in expressing the structural information of chemical compounds, graph neural networks (...
Neural Networks, Computer Learning Drug Interactions
View on PubMed DOI

What and Where: Learn to Plug Adapters via NAS for Multidomain Learning.

IEEE transactions on neural networks and learning systems Oct 27, 2022
As an important and challenging problem, multidomain learning (MDL) typically seeks a set of effective lightweight domain-specific adapter modules plugged into a common domain-agnostic network. Usually, existing ways of adapter plugging and structure...
Neural Networks, Computer Software Learning
View on PubMed DOI

Orientation-Preserving Rewards' Balancing in Reinforcement Learning.

IEEE transactions on neural networks and learning systems Oct 27, 2022
Auxiliary rewards are widely used in complex reinforcement learning tasks. However, previous work can hardly avoid the interference of auxiliary rewards on pursuing the main rewards, which leads to the destruction of the optimal policy. Thus, it is c...
Neural Networks, Computer Computer Simulation Learning Reward Reinforcement, Psychology
View on PubMed DOI

Frequency Principle in Broad Learning System.

IEEE transactions on neural networks and learning systems Oct 27, 2022
Deep neural networks have achieved breakthrough improvement in various application fields. Nevertheless, they usually suffer from a time-consuming training process because of the complicated structures of neural networks with a huge number of paramet...
Neural Networks, Computer Learning
View on PubMed DOI

Towards Transfer Learning Techniques-BERT, DistilBERT, BERTimbau, and DistilBERTimbau for Automatic Text Classification from Different Languages: A Case Study.

Sensors (Basel, Switzerland) Oct 26, 2022
The Internet of Things is a paradigm that interconnects several smart devices through the internet to provide ubiquitous services to users. This paradigm and Web 2.0 platforms generate countless amounts of textual data. Thus, a significant challenge ...
Language Learning Deep Learning Social Media Natural Language Processing
View on PubMed DOI

Co-Learning Computational and Design Thinking Using Educational Robotics: A Case of Primary School Learners in Namibia.

Sensors (Basel, Switzerland) Oct 25, 2022
In a two-day educational robotics workshop in a Namibian primary boarding school, learners with no programming skills managed to apply both computational and design thinking skills with the aid of educational robotics. Educational robotics has proved...
Humans Learning Robotics Schools Thinking Education Namibia
View on PubMed DOI

A Routing Optimization Method for Software-Defined Optical Transport Networks Based on Ensembles and Reinforcement Learning.

Sensors (Basel, Switzerland) Oct 24, 2022
Optical transport networks (OTNs) are widely used in backbone- and metro-area transmission networks to increase network transmission capacity. In the OTN, it is particularly crucial to rationally allocate routes and maximize network capacities. By em...
Neural Networks, Computer Software Algorithms Learning
View on PubMed DOI
Popular Topics
Recent Journals