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Gelsight: High-resolution robot tactile sensors for estimating geometry and force
Tactile sensing is an important perception mode for robots, but the existing tactile
technologies have multiple limitations. What kind of tactile information robots need, and how …
technologies have multiple limitations. What kind of tactile information robots need, and how …
Sparsity and compressed sensing in radar imaging
Remote sensing with radar is typically an ill-posed linear inverse problem: a scene is to be
inferred from limited measurements of scattered electric fields. Parsimonious models provide …
inferred from limited measurements of scattered electric fields. Parsimonious models provide …
Majorization-minimization algorithms in signal processing, communications, and machine learning
This paper gives an overview of the majorization-minimization (MM) algorithmic framework,
which can provide guidance in deriving problem-driven algorithms with low computational …
which can provide guidance in deriving problem-driven algorithms with low computational …
Learning k for kNN Classification
The K Nearest Neighbor (kNN) method has widely been used in the applications of data
mining and machine learning due to its simple implementation and distinguished …
mining and machine learning due to its simple implementation and distinguished …
Acoustic beamforming for noise source localization–Reviews, methodology and applications
This paper is a review on acoustic beamforming for noise source localization and its
applications. The main concepts of beamforming, starting from the very basics and …
applications. The main concepts of beamforming, starting from the very basics and …
[PDF][PDF] Self-weighted multiview clustering with multiple graphs.
In multiview learning, it is essential to assign a reasonable weight to each view according to
the view importance. Thus, for multiview clustering task, a wise and elegant method should …
the view importance. Thus, for multiview clustering task, a wise and elegant method should …
Global convergence of ADMM in nonconvex nonsmooth optimization
In this paper, we analyze the convergence of the alternating direction method of multipliers
(ADMM) for minimizing a nonconvex and possibly nonsmooth objective function, ϕ (x_0 …
(ADMM) for minimizing a nonconvex and possibly nonsmooth objective function, ϕ (x_0 …
[کتاب][B] An invitation to compressive sensing
This first chapter formulates the objectives of compressive sensing. It introduces the
standard compressive problem studied throughout the book and reveals its ubiquity in many …
standard compressive problem studied throughout the book and reveals its ubiquity in many …
A unified algorithmic framework for block-structured optimization involving big data: With applications in machine learning and signal processing
This article presents a powerful algorithmic framework for big data optimization, called the
block successive upper-bound minimization (BSUM). The BSUM includes as special cases …
block successive upper-bound minimization (BSUM). The BSUM includes as special cases …
A compressive hyperspectral video imaging system using a single-pixel detector
Capturing fine spatial, spectral, and temporal information of the scene is highly desirable in
many applications. However, recording data of such high dimensionality requires significant …
many applications. However, recording data of such high dimensionality requires significant …