Mixture of experts: a literature survey
Mixture of experts (ME) is one of the most popular and interesting combining methods, which
has great potential to improve performance in machine learning. ME is established based on …
has great potential to improve performance in machine learning. ME is established based on …
Twenty years of mixture of experts
In this paper, we provide a comprehensive survey of the mixture of experts (ME). We discuss
the fundamental models for regression and classification and also their training with the …
the fundamental models for regression and classification and also their training with the …
Macular OCT classification using a multi-scale convolutional neural network ensemble
Computer-aided diagnosis (CAD) of retinal pathologies is a current active area in medical
image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) …
image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) …
A mixture-of-experts prediction framework for evolutionary dynamic multiobjective optimization
Dynamic multiobjective optimization requires the robust tracking of varying Pareto-optimal
solutions (POS) in a changing environment. When a change is detected in the environment …
solutions (POS) in a changing environment. When a change is detected in the environment …
Activity recognition with android phone using mixture-of-experts co-trained with labeled and unlabeled data
YS Lee, SB Cho - Neurocomputing, 2014 - Elsevier
As the number of smartphone users has grown recently, many context-aware services have
been studied and launched. Activity recognition becomes one of the important issues for …
been studied and launched. Activity recognition becomes one of the important issues for …
Audiovisual emotion recognition using ANOVA feature selection method and multi-classifier neural networks
To make human–computer interaction more naturally and friendly, computers must enjoy the
ability to understand human's affective states the same way as human does. There are many …
ability to understand human's affective states the same way as human does. There are many …
Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange
A new method for forecasting the trend of time series, based on mixture of MLP experts, is
presented. In this paper, three neural network combining methods and an Adaptive Network …
presented. In this paper, three neural network combining methods and an Adaptive Network …
Knitted fabric defect classification for uncertain labels based on Dempster–Shafer theory of evidence
A new approach for classification of circular knitting fabric defects is proposed which is
based on accepting uncertainty in labels of the learning data. In the basic classification …
based on accepting uncertainty in labels of the learning data. In the basic classification …
Preserving text space integrity for robust compositional zero-shot learning via mixture of pretrained experts
In the current landscape of Compositional Zero-Shot Learning (CZSL) methods that
leverage CLIP, the predominant approach is based on prompt learning paradigms. These …
leverage CLIP, the predominant approach is based on prompt learning paradigms. These …
Mixture of neural fields for heterogeneous reconstruction in cryo-EM
Cryo-electron microscopy (cryo-EM) is an experimental technique for protein structure
determination that images an ensemble of macromolecules in near-physiological contexts …
determination that images an ensemble of macromolecules in near-physiological contexts …