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02/06/2023
Importance attribution in neural networks by means of persistence landscapes of time series
We propose and implement a method to analyze time series with a neural n...
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02/06/2023
A Scalable and Efficient Iterative Method for Copying Machine Learning Classifiers
Differential replication through copying refers to the process of replic...
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03/03/2022
Reconstruction of univariate functions from directional persistence diagrams
We describe a method for approximating a single-variable function f usin...
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01/30/2022
Training Thinner and Deeper Neural Networks: Jumpstart Regularization
Neural networks are more expressive when they have multiple layers. In t...
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05/27/2021
Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems
Regression problems have been widely studied in machinelearning literatu...
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07/15/2020
Differential Replication in Machine Learning
When deployed in the wild, machine learning models are usually confronte...
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12/29/2019
Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability
Nowadays, the use of machine learning models is becoming a utility in ma...
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10/01/2019
Sampling Unknown Decision Functions to Build Classifier Copies
Copies have been proposed as a viable alternative to endow machine learn...
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03/05/2019
Copying Machine Learning Classifiers
We study model-agnostic copies of machine learning classifiers. We devel...
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11/19/2018
Towards Global Explanations for Credit Risk Scoring
In this paper we propose a method to obtain global explanations for trai...
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05/29/2015
Learning to count with deep object features
Learning to count is a learning strategy that has been recently proposed...
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02/27/2015
Error-Correcting Factorization
Error Correcting Output Codes (ECOC) is a successful technique in multi-...
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10/16/2014
