research
∙
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...
share
research
∙
05/23/2023
A Deep Learning Approach for Generating Soft Range Information from RF Data
Radio frequency (RF)-based techniques are widely adopted for indoor loca...
research
∙
05/23/2023
Deep GEM-Based Network for Weakly Supervised UWB Ranging Error Mitigation
Ultra-wideband (UWB)-based techniques, while becoming mainstream approac...
research
∙
05/23/2023
Deep Generative Model for Simultaneous Range Error Mitigation and Environment Identification
Received waveforms contain rich information for both range information a...
research
∙
05/23/2023
A Semi-Supervised Learning Approach for Ranging Error Mitigation Based on UWB Waveform
Localization systems based on ultra-wide band (UWB) measurements can hav...
research
∙
05/23/2023
Variational Bayesian Framework for Advanced Image Generation with Domain-Related Variables
Deep generative models (DGMs) and their conditional counterparts provide...
research
∙
05/15/2023
Double-Weighting for Covariate Shift Adaptation
Supervised learning is often affected by a covariate shift in which the ...
research
∙
05/31/2022
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees
The statistical characteristics of instance-label pairs often change wit...
research
∙
01/17/2022
Minimax risk classifiers with 0-1 loss
Supervised classification techniques use training samples to learn a cla...
research
∙
08/04/2021
MRCpy: A Library for Minimax Risk Classifiers
Existing libraries for supervised classification implement techniques th...
research
∙
11/30/2020
Probabilistic Load Forecasting Based on Adaptive Online Learning
Load forecasting is crucial for multiple energy management tasks such as...
research
∙
10/15/2020
Minimax Classification with 0-1 Loss and Performance Guarantees
Supervised classification techniques use training samples to find classi...
research
∙
07/10/2020
Generalized Maximum Entropy for Supervised Classification
The maximum entropy principle advocates to evaluate events' probabilitie...
research
∙
02/02/2019
Supervised classification via minimax probabilistic transformations
One of the most common and studied problem in machine learning is classi...
research
∙
01/24/2019