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Efficient Learning of Minimax Risk Classifiers in High Dimensions
(2023-08-01)
High-dimensional data is common in multiple areas, such as health care and genomics, where the
number of features can be tens of thousands. In
such scenarios, the large number of features often leads to inefficient ...
Minimax Risk Classifiers with 0-1 Loss
(2023-07-01)
Supervised classification techniques use training samples to learn a classification rule with
small expected 0 -1 loss (error probability). Conventional methods enable tractable learning
and provide out-of-sample ...
A Variational Learning Approach for Concurrent Distance Estimation and Environmental Identification
(2023-02-01)
Wireless propagated signals encapsulate rich information
for high-accuracy localization and environment sensing.
However, the full exploitation of positional and environmental
features as well as their correlation remains ...
Female Models in AI and the Fight Against COVID-19
(2022-11-01)
Gender imbalance has persisted over time and is well documented in science, technology,
engineering and mathematics (STEM) and singularly in artificial intelligence
(AI). In this article we emphasize the importance of ...
The role of asymmetric prediction losses in smart charging of electric vehicles
(2022-07-01)
Climate change prompts humanity to look for decarbonisation opportunities, and a viable option is to supply electric vehicles with renewable energy. The stochastic nature of charging demand and renewable generation requires ...
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees
(2022-07)
The statistical characteristics of instance-label pairs often change with time in practical scenarios of supervised classification. Conventional learning techniques adapt to such concept drift accounting for a scalar rate ...
Variational Bayesian Framework for Advanced Image Generation with Domain-Related Variables
(2022-05-23)
Deep generative models (DGMs) and their conditional
counterparts provide a powerful ability for general-purpose
generative modeling of data distributions. However, it remains
challenging for existing methods to address ...
Generalized Maximum Entropy for Supervised Classification
(2022-04)
The maximum entropy principle advocates to
evaluate events’ probabilities using a distribution that maximizes
entropy among those that satisfy certain expectations’ constraints. Such principle can be generalized for ...
A Deep Learning Approach for Generating Soft Range Information from RF Data
(2022-01-24)
Radio frequency (RF)-based techniques are widely
adopted for indoor localization despite the challenges in extracting
sufficient information from measurements. Soft range
information (SRI) offers a promising alternative ...
Derivation of a Cost-Sensitive COVID-19 Mortality Risk Indicator Using a Multistart Framework
(2022-01-14)
The overall global death rate for COVID-19 patients
has escalated to 2.13% after more than a year of worldwide
spread. Despite strong research on the infection pathogenesis, the
molecular mechanisms involved in a fatal ...