
Stochastic Neighbor Embedding with Gaussian and Studentt Distributions: Tutorial and Survey
Stochastic Neighbor Embedding (SNE) is a manifold learning and dimension...
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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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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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Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey
Multidimensional Scaling (MDS) is one of the first fundamental manifold ...
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BatchIncremental 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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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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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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QuantileQuantile Embedding for Distribution Transformation, Manifold Embedding, and Image Embedding with Choice of Embedding Distribution
We propose a new embedding method, named QuantileQuantile Embedding (QQ...
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Active Measure Reinforcement Learning for Observation Cost Minimization
Standard reinforcement learning (RL) algorithms assume that the observat...
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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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Reinforcement Learning in a PhysicsInspired SemiMarkov Environment
Reinforcement learning (RL) has been demonstrated to have great potentia...
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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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Anomaly Detection and Prototype Selection Using Polyhedron Curvature
We propose a novel approach to anomaly detection called Curvature Anomal...
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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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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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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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Isolation Mondrian Forest for Batch and Online Anomaly Detection
We propose a new method, named isolation Mondrian forest (iMondrian fore...
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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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Roweis Discriminant Analysis: A Generalized Subspace Learning Method
We present a new method which generalizes subspace learning based on eig...
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Quantized Fisher Discriminant Analysis
This paper proposes a new subspace learning method, named Quantized Fish...
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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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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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Fisher and Kernel Fisher Discriminant Analysis: Tutorial
This is a detailed tutorial paper which explains the Fisher discriminant...
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Linear and Quadratic Discriminant Analysis: Tutorial
This tutorial explains Linear Discriminant Analysis (LDA) and Quadratic ...
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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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Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
Pattern analysis often requires a preprocessing stage for extracting or...
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Eigenvalue and Generalized Eigenvalue Problems: Tutorial
This paper is a tutorial for eigenvalue and generalized eigenvalue probl...
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Artificial Counselor System for Stock Investment
This paper proposes a novel trading system which plays the role of an ar...
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Addressing the Mystery of Population Decline of the RoseCrested 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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Fitting A Mixture Distribution to Data: Tutorial
This paper is a stepbystep tutorial for fitting a mixture distribution...
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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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Seeing the Forest Despite the Trees: Large Scale SpatialTemporal Decision Making
We introduce a challenging realworld planning problem where actions mus...
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Mark Crowley
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