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09/14/2023
Proximal Bellman mappings for reinforcement learning and their application to robust adaptive filtering
This paper aims at the algorithmic/theoretical core of reinforcement lea...
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04/06/2023
Multi-Linear Kernel Regression and Imputation in Data Manifolds
This paper introduces an efficient multi-linear nonparametric (kernel-ba...
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10/21/2022
online and lightweight kernel-based approximated policy iteration for dynamic p-norm linear adaptive filtering
This paper introduces a solution to the problem of selecting dynamically...
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10/20/2022
Dynamic selection of p-norm in linear adaptive filtering via online kernel-based reinforcement learning
This study addresses the problem of selecting dynamically, at each time ...
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02/27/2020
Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case
This paper establishes a kernel-based framework for reconstructing data ...
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10/11/2019
Robust Hierarchical-Optimization RLS Against Sparse Outliers
This paper fortifies the recently introduced hierarchical-optimization r...
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06/05/2019
Brain-Network Clustering via Kernel-ARMA Modeling and the Grassmannian
Recent advances in neuroscience and in the technology of functional magn...
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12/27/2018
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery
This paper puts forth a novel bi-linear modeling framework for data reco...
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01/26/2017
Riemannian-geometry-based modeling and clustering of network-wide non-stationary time series: The brain-network case
This paper advocates Riemannian multi-manifold modeling in the context o...
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10/06/2015
Large-scale subspace clustering using sketching and validation
The nowadays massive amounts of generated and communicated data present ...
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01/22/2015
Sketch and Validate for Big Data Clustering
In response to the need for learning tools tuned to big data analytics, ...
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10/01/2014