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02/12/2023
Efficient Fraud Detection using Deep Boosting Decision Trees
Fraud detection is to identify, monitor, and prevent potentially fraudul...
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09/24/2021
An Improved Frequent Directions Algorithm for Low-Rank Approximation via Block Krylov Iteration
Frequent Directions, as a deterministic matrix sketching technique, has ...
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01/20/2020
An interpretable neural network model through piecewise linear approximation
Most existing interpretable methods explain a black-box model in a post-...
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11/14/2019
Explainable Ordinal Factorization Model: Deciphering the Effects of Attributes by Piece-wise Linear Approximation
Ordinal regression predicts the objects' labels that exhibit a natural o...
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10/12/2019
A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples
We present a preference learning framework for multiple criteria sorting...
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06/04/2019
An interpretable machine learning framework for modelling human decision behavior
Machine learning has recently been widely adopted to address the manager...
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05/21/2019
