AIMC Topic: Learning

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A Deep-Ensemble-Level-Based Interpretable Takagi-Sugeno-Kang Fuzzy Classifier for Imbalanced Data.

IEEE transactions on cybernetics May 19, 2022
Existing research reveals that the misclassification rate for imbalanced data depends heavily on the problematic areas due to the existence of small disjoints, class overlap, borderline, and rare data samples. In this study, by stacking zero-order Ta...
Algorithms Learning Fuzzy Logic
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Semisupervised Multiple Choice Learning for Ensemble Classification.

IEEE transactions on cybernetics May 19, 2022
Ensemble learning has many successful applications because of its effectiveness in boosting the predictive performance of classification models. In this article, we propose a semisupervised multiple choice learning (SemiMCL) approach to jointly train...
Learning Supervised Machine Learning
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Hybrid Model-Based Emotion Contextual Recognition for Cognitive Assistance Services.

IEEE transactions on cybernetics May 19, 2022
Endowing ubiquitous robots with cognitive capabilities for recognizing emotions, sentiments, affects, and moods of humans in their context is an important challenge, which requires sophisticated and novel approaches of emotion recognition. Most studi...
Humans Neural Networks, Computer Learning Cognition Emotions
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Novel Multitask Conditional Neural-Network Surrogate Models for Expensive Optimization.

IEEE transactions on cybernetics May 19, 2022
Multiple-related tasks can be learned simultaneously by sharing information among tasks to avoid tabula rasa learning and to improve performance in the no transfer case (i.e., when each task learns in isolation). This study investigates multitask lea...
Neural Networks, Computer Algorithms Learning Bayes Theorem
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On Adaptive Learning Framework for Deep Weighted Sparse Autoencoder: A Multiobjective Evolutionary Algorithm.

IEEE transactions on cybernetics May 19, 2022
In this article, an adaptive learning framework is established for a deep weighted sparse autoencoder (AE) by resorting to the multiobjective evolutionary algorithm (MOEA). The weighted sparsity is introduced to facilitate the design of the varying d...
Neural Networks, Computer Algorithms Learning
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Learning Cross-Modal Common Representations by Private-Shared Subspaces Separation.

IEEE transactions on cybernetics May 19, 2022
Due to the inconsistent distributions and representations of different modalities (e.g., images and texts), it is very challenging to correlate such heterogeneous data. A standard solution is to construct one common subspace, where the common represe...
Machine Learning Learning
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Personalized Hybrid Education Framework Based on Neuroevolution Methodologies.

Computational intelligence and neuroscience May 19, 2022
The future pedagogical systems need anthropocentric inclusive educational programs in which the goal should be adjustable according to the knowledge requirements, intelligence, and learning objective of each student. Prioritizing these needs, innovat...
Humans Neural Networks, Computer Artificial Intelligence Algorithms Learning Cluster Analysis
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Intelligent career planning via stochastic subsampling reinforcement learning.

Scientific reports May 18, 2022
Career planning consists of a series of decisions that will significantly impact one's life. However, current recommendation systems have serious limitations, including the lack of effective artificial intelligence algorithms for long-term career pla...
Humans Artificial Intelligence Algorithms Learning Intelligence Reinforcement, Psychology
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Feature blindness: A challenge for understanding and modelling visual object recognition.

PLoS computational biology May 13, 2022
Humans rely heavily on the shape of objects to recognise them. Recently, it has been argued that Convolutional Neural Networks (CNNs) can also show a shape-bias, provided their learning environment contains this bias. This has led to the proposal tha...
Humans Neural Networks, Computer Learning Bias Visual Perception Blindness
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Polyp segmentation network with hybrid channel-spatial attention and pyramid global context guided feature fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society May 11, 2022
In clinical practice, automatic polyp segmentation from colonoscopy images is an effective assistant manner in the early detection and prevention of colorectal cancer. This paper proposed a new deep model for accurate polyp segmentation based on an e...
Neural Networks, Computer Learning Image Processing, Computer-Assisted Attention
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