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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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09/22/2020
Design of Efficient Deep Learning models for Determining Road Surface Condition from Roadside Camera Images and Weather Data
Road maintenance during the Winter season is a safety critical and resou...
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09/22/2020
Semantic Workflows and Machine Learning for the Assessment of Carbon Storage by Urban Trees
Climate science is critical for understanding both the causes and conseq...
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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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05/26/2020
Active Measure Reinforcement Learning for Observation Cost Minimization
Standard reinforcement learning (RL) algorithms assume that the observat...
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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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04/15/2020
Reinforcement Learning in a Physics-Inspired Semi-Markov Environment
Reinforcement learning (RL) has been demonstrated to have great potentia...
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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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03/02/2020
A review of machine learning applications in wildfire science and management
Artificial intelligence has been applied in wildfire science and managem...
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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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02/01/2017
Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program
The 7th Symposium on Educational Advances in Artificial Intelligence (EA...
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05/09/2012
