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06/16/2023
Structural Restricted Boltzmann Machine for image denoising and classification
Restricted Boltzmann Machines are generative models that consist of a la...
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06/11/2023
Efficient Learning of Minimax Risk Classifiers in High Dimensions
High-dimensional data is common in multiple areas, such as health care a...
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05/12/2023
On the Fair Comparison of Optimization Algorithms in Different Machines
An experimental comparison of two or more optimization algorithms requir...
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10/13/2022
Dirichlet process mixture models for non-stationary data streams
In recent years, we have seen a handful of work on inference algorithms ...
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08/29/2022
Semantic Clustering of a Sequence of Satellite Images
Satellite images constitute a highly valuable and abundant resource for ...
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03/15/2022
Comparing two samples through stochastic dominance: a graphical approach
Non-deterministic measurements are common in real-world scenarios: the p...
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08/04/2021
MRCpy: A Library for Minimax Risk Classifiers
Existing libraries for supervised classification implement techniques th...
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12/07/2020
Passive Approach for the K-means Problem on Streaming Data
Currently the amount of data produced worldwide is increasing beyond mea...
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10/15/2020
Minimax Classification with 0-1 Loss and Performance Guarantees
Supervised classification techniques use training samples to find classi...
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07/10/2020
Generalized Maximum Entropy for Supervised Classification
The maximum entropy principle advocates to evaluate events' probabilitie...
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10/19/2019
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem
The Quadratic Assignment Problem (QAP) is a well-known permutation-based...
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10/19/2019
Online Ranking with Concept Drifts in Streaming Data
Two important problems in preference elicitation are rank aggregation an...
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02/02/2019
Supervised classification via minimax probabilistic transformations
One of the most common and studied problem in machine learning is classi...
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01/24/2019
General Supervision via Probabilistic Transformations
Different types of training data have led to numerous schemes for superv...
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04/26/2018
Weak Labeling for Crowd Learning
Crowdsourcing has become very popular among the machine learning communi...
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01/09/2018
An efficient K -means clustering algorithm for massive data
The analysis of continously larger datasets is a task of major importanc...
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05/10/2016