[HTML][HTML] Integration strategies of multi-omics data for machine learning analysis
Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …
number of omics data that seek to portray many different but complementary biological …
Computational analysis of cancer genome sequencing data
Distilling biologically meaningful information from cancer genome sequencing data requires
comprehensive identification of somatic alterations using rigorous computational methods …
comprehensive identification of somatic alterations using rigorous computational methods …
Graph regularized nonnegative matrix factorization for community detection in attributed networks
K Berahmand, M Mohammadi… - … on Network Science …, 2022 - ieeexplore.ieee.org
Community detection has become an important research topic in machine learning due to
the proliferation of network data. However, most existing methods have been developed …
the proliferation of network data. However, most existing methods have been developed …
Deciphering signatures of mutational processes operative in human cancer
The genome of a cancer cell carries somatic mutations that are the cumulative
consequences of the DNA damage and repair processes operative during the cellular …
consequences of the DNA damage and repair processes operative during the cellular …
Fast, generic, and reliable control and simulation of soft robots using model order reduction
Obtaining an accurate mechanical model of a soft deformable robot compatible with the
computation time imposed by robotic applications is often considered an unattainable goal …
computation time imposed by robotic applications is often considered an unattainable goal …
Dimensional reduction of nonlinear finite element dynamic models with finite rotations and energy‐based mesh sampling and weighting for computational efficiency
SUMMARY A rigorous computational framework for the dimensional reduction of discrete,
high‐fidelity, nonlinear, finite element structural dynamics models is presented. It is based …
high‐fidelity, nonlinear, finite element structural dynamics models is presented. It is based …
Inertial proximal alternating linearized minimization (iPALM) for nonconvex and nonsmooth problems
In this paper we study nonconvex and nonsmooth optimization problems with semialgebraic
data, where the variables vector is split into several blocks of variables. The problem …
data, where the variables vector is split into several blocks of variables. The problem …
A survey on deep matrix factorizations
Constrained low-rank matrix approximations have been known for decades as powerful
linear dimensionality reduction techniques able to extract the information contained in large …
linear dimensionality reduction techniques able to extract the information contained in large …
Target recognition in synthetic aperture radar images via non‐negative matrix factorisation
Z Cui, Z Cao, J Yang, J Feng… - IET Radar, Sonar & …, 2015 - Wiley Online Library
This study proposes a novel non‐negative matrix factorisation (NMF) variant L1/2‐NMF after
visualisation and analysis of the process of target recognition via NMF for synthetic aperture …
visualisation and analysis of the process of target recognition via NMF for synthetic aperture …
Graph non-negative matrix factorization with alternative smoothed regularizations
Graph non-negative matrix factorization (GNMF) can discover the data's intrinsic low-
dimensional structure embedded in the high-dimensional space. So, it has superior …
dimensional structure embedded in the high-dimensional space. So, it has superior …