
ParkingSticker: A RealWorld Object Detection Dataset
We present a new and challenging object detection dataset, ParkingSticke...
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Automatic Hyperparameter Tuning Method for Local Outlier Factor, with Applications to Anomaly Detection
In recent years, there have been many practical applications of anomaly ...
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An Online Algorithm for Nonparametric Correlations
Nonparametric correlations such as Spearman's rank correlation and Kenda...
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The Mean and Median Criterion for Automatic Kernel Bandwidth Selection for Support Vector Data Description
Support vector data description (SVDD) is a popular technique for detect...
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Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel
Support vector data description (SVDD) is a machine learning technique t...
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Online Robust Principal Component Analysis with Change Point Detection
Robust PCA methods are typically batch algorithms which requires loading...
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Sampling Method for Fast Training of Support Vector Data Description
Support Vector Data Description (SVDD) is a popular outlier detection te...
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A Probabilistic Machine Learning Approach to Detect Industrial Plant Faults
Fault detection in industrial plants is a hot research area as more and ...
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Algorithms, Initializations, and Convergence for the Nonnegative Matrix Factorization
It is well known that good initializations can improve the speed and acc...
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Safe Screening With Variational Inequalities and Its Application to LASSO
Sparse learning techniques have been routinely used for feature selectio...
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Generalized double Pareto shrinkage
We propose a generalized double Pareto prior for Bayesian shrinkage esti...
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A New Bandwidth Selection Criterion for Analyzing Hyperspectral Data Using SVDD
This paper presents a method for hyperspectral image classification usin...
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Provable Convex Coclustering of Tensors
Cluster analysis is a fundamental tool for pattern discovery of complex ...
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Autotune: A Derivativefree Optimization Framework for Hyperparameter Tuning
Machine learning applications often require hyperparameter tuning. The h...
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TrustRegion Algorithms for Training Responses: Machine Learning Methods Using Indefinite Hessian Approximations
Machine learning (ML) problems are often posed as highly nonlinear and n...
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MultiTask Learning with Incomplete Data for Healthcare
Multitask learning is a type of transfer learning that trains multiple ...
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A fast algorithm for computing distance correlation
Classical dependence measures such as Pearson correlation, Spearman's ρ,...
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A New SVDDBased Multivariate Nonparametric Process Capability Index
Process capability index (PCI) is a commonly used statistic to measure a...
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The Trace Criterion for Kernel Bandwidth Selection for Support Vector Data Description
Support vector data description (SVDD) is a popular anomaly detection te...
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Robust Active Learning for Electrocardiographic Signal Classification
The classification of electrocardiographic (ECG) signals is a challengin...
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An Exponential EfronStein Inequality for Lq Stable Learning Rules
There is accumulating evidence in the literature that stability of learn...
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Style Transfer With Adaptation to the Central Objects of the Scene
Style transfer is a problem of rendering image with some content in the ...
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An AIAugmented Lesion Detection Framework For Liver Metastases With Model Interpretability
Colorectal cancer (CRC) is the third most common cancer and the second l...
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A Review of Cooperative MultiAgent Deep Reinforcement Learning
Deep Reinforcement Learning has made significant progress in multiagent...
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Distributed Bayesian clustering
In many modern applications, there is interest in analyzing enormous dat...
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Towards optimized actions in critical situations of soccer games with deep reinforcement learning
Soccer is a sparse rewarding game: any smart or careless action in criti...
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