AIMC Topic: Learning

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Biologically plausible single-layer networks for nonnegative independent component analysis.

Biological cybernetics Sep 7, 2022
An important problem in neuroscience is to understand how brains extract relevant signals from mixtures of unknown sources, i.e., perform blind source separation. To model how the brain performs this task, we seek a biologically plausible single-laye...
Neural Networks, Computer Algorithms Brain Learning Neurons
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Competencies for the Use of Artificial Intelligence-Based Tools by Health Care Professionals.

Academic medicine : journal of the Association of American Medical Colleges Sep 6, 2022
PURPOSE: The expanded use of clinical tools that incorporate artificial intelligence (AI) methods has generated calls for specific competencies for effective and ethical use. This qualitative study used expert interviews to define AI-related clinical...
Humans Artificial Intelligence Health Personnel Delivery of Health Care Learning Clinical Competence
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IDT: An incremental deep tree framework for biological image classification.

Artificial intelligence in medicine Sep 6, 2022
Nowadays, breast and cervical cancers are respectively the first and fourth most common causes of cancer death in females. It is believed that, automated systems based on artificial intelligence would allow the early diagnostic which increases signif...
Humans Neural Networks, Computer Artificial Intelligence Learning Female
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Tf-GCZSL: Task-free generalized continual zero-shot learning.

Neural networks : the official journal of the International Neural Network Society Sep 6, 2022
Learning continually from a stream of training data or tasks with an ability to learn the unseen classes using a zero-shot learning framework is gaining attention in the literature. It is referred to as continual zero-shot learning (CZSL). Existing C...
Machine Learning Learning Memory, Long-Term
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Effect of button layout on the exploration and learning of robot operation using an unfamiliar controller.

PloS one Sep 2, 2022
Robots are becoming increasingly accessible to both experts and non-experts. Therefore, establishing a method for learning robot operations that can be easily mastered by non-experts is important. With this in mind, we aimed to develop a method that ...
Humans Learning Robotics Robotic Surgical Procedures Foot Movement
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A Design Framework of Exploration, Segmentation, Navigation, and Instruction (ESNI) for the Lifecycle of Intelligent Mobile Agents as a Method for Mapping an Unknown Built Environment.

Sensors (Basel, Switzerland) Sep 1, 2022
Recent work on intelligent agents is a popular topic among the artificial intelligence community and robotic system design. The complexity of designing a framework as a guide for intelligent agents in an unknown built environment suggests a pressing ...
Artificial Intelligence Algorithms Learning Built Environment
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BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture.

IEEE transactions on neural networks and learning systems Aug 31, 2022
Efficient neural architecture search (ENAS) achieves novel efficiency for learning architecture with high-performance via parameter sharing and reinforcement learning (RL). In the phase of architecture search, ENAS employs deep scalable architecture ...
Neural Networks, Computer Machine Learning Learning Reinforcement, Psychology
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Joint Label Inference and Discriminant Embedding.

IEEE transactions on neural networks and learning systems Aug 31, 2022
Graph-based learning in semisupervised models provides an effective tool for modeling big data sets in high-dimensional spaces. It has been useful for propagating a small set of initial labels to a large set of unlabeled data. Thus, it meets the requ...
Neural Networks, Computer Algorithms Learning Supervised Machine Learning Pattern Recognition, Automated
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Local Critic Training for Model-Parallel Learning of Deep Neural Networks.

IEEE transactions on neural networks and learning systems Aug 31, 2022
In this article, we propose a novel model-parallel learning method, called local critic training, which trains neural networks using additional modules called local critic networks. The main network is divided into several layer groups, and each laye...
Neural Networks, Computer Machine Learning Learning
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Overcoming Long-Term Catastrophic Forgetting Through Adversarial Neural Pruning and Synaptic Consolidation.

IEEE transactions on neural networks and learning systems Aug 31, 2022
Enabling a neural network to sequentially learn multiple tasks is of great significance for expanding the applicability of neural networks in real-world applications. However, artificial neural networks face the well-known problem of catastrophic for...
Neural Networks, Computer Machine Learning Brain Learning Animals Neuronal Plasticity Mammals
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