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08/26/2023
On Philomatics and Psychomatics for Combining Philosophy and Psychology with Mathematics
We propose the concepts of philomatics and psychomatics as hybrid combin...
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04/22/2023
Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey
This is a tutorial paper on Recurrent Neural Network (RNN), Long Short-T...
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10/30/2022
Gravitational Dimensionality Reduction Using Newtonian Gravity and Einstein's General Relativity
Due to the effectiveness of using machine learning in physics, it has be...
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08/29/2022
Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A Human
After the development of different machine learning and manifold learnin...
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09/22/2020
Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey
Stochastic Neighbor Embedding (SNE) is a manifold learning and dimension...
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09/17/2020
Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey
Multidimensional Scaling (MDS) is one of the first fundamental manifold ...
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07/10/2020
Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem
Variants of Triplet networks are robust entities for learning a discrimi...
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07/04/2020
Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches
We analyze the effect of offline and online triplet mining for colorecta...
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06/28/2020
Roweisposes, Including Eigenposes, Supervised Eigenposes, and Fisherposes, for 3D Action Recognition
Human action recognition is one of the important fields of computer visi...
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06/19/2020
Quantile-Quantile Embedding for Distribution Transformation, Manifold Embedding, and Image Embedding with Choice of Embedding Distribution
We propose a new embedding method, named Quantile-Quantile Embedding (QQ...
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05/10/2020
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study
As many algorithms depend on a suitable representation of data, learning...
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04/05/2020
Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces
After the tremendous development of neural networks trained by backpropa...
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04/05/2020
Anomaly Detection and Prototype Selection Using Polyhedron Curvature
We propose a novel approach to anomaly detection called Curvature Anomal...
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04/05/2020
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
Siamese neural network is a very powerful architecture for both feature ...
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04/04/2020
Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders
Generative models and inferential autoencoders mostly make use of ℓ_2 no...
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04/04/2020
Weighted Fisher Discriminant Analysis in the Input and Feature Spaces
Fisher Discriminant Analysis (FDA) is a subspace learning method which m...
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03/08/2020
Isolation Mondrian Forest for Batch and Online Anomaly Detection
We propose a new method, named isolation Mondrian forest (iMondrian fore...
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10/22/2019
Distributed Voting in Beep Model
In this paper, we propose two distributed algorithms, named Distributed ...
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10/11/2019
Roweis Discriminant Analysis: A Generalized Subspace Learning Method
We present a new method which generalizes subspace learning based on eig...
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09/06/2019
Quantized Fisher Discriminant Analysis
This paper proposes a new subspace learning method, named Quantized Fish...
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08/25/2019
Locally Linear Image Structural Embedding for Image Structure Manifold Learning
Most of existing manifold learning methods rely on Mean Squared Error (M...
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08/25/2019
Principal Component Analysis Using Structural Similarity Index for Images
Despite the advances of deep learning in specific tasks using images, th...
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06/22/2019
Fisher and Kernel Fisher Discriminant Analysis: Tutorial
This is a detailed tutorial paper which explains the Fisher discriminant...
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06/01/2019
Linear and Quadratic Discriminant Analysis: Tutorial
This tutorial explains Linear Discriminant Analysis (LDA) and Quadratic ...
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05/28/2019
The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial
In this tutorial paper, we first define mean squared error, variance, co...
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05/07/2019
Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
Pattern analysis often requires a pre-processing stage for extracting or...
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03/25/2019
Eigenvalue and Generalized Eigenvalue Problems: Tutorial
This paper is a tutorial for eigenvalue and generalized eigenvalue probl...
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03/03/2019
Artificial Counselor System for Stock Investment
This paper proposes a novel trading system which plays the role of an ar...
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03/03/2019
Addressing the Mystery of Population Decline of the Rose-Crested Blue Pipit in a Nature Preserve using Data Visualization
Two main methods for exploring patterns in data are data visualization a...
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01/20/2019
Fitting A Mixture Distribution to Data: Tutorial
This paper is a step-by-step tutorial for fitting a mixture distribution...
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09/25/2018
Tree-Based Optimization: A Meta-Algorithm for Metaheuristic Optimization
Designing search algorithms for finding global optima is one of the most...
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07/05/2018
Pontogammarus Maeoticus Swarm Optimization: A Metaheuristic Optimization Algorithm
Nowadays, metaheuristic optimization algorithms are used to find the glo...
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02/07/2018
Pixel-Level Alignment of Facial Images for High Accuracy Recognition Using Ensemble of Patches
The variation of pose, illumination and expression makes face recognitio...
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11/17/2017
