Gelsight: High-resolution robot tactile sensors for estimating geometry and force

W Yuan, S Dong, EH Adelson - Sensors, 2017‏ - mdpi.com
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 …

Sparsity and compressed sensing in radar imaging

LC Potter, E Ertin, JT Parker, M Cetin - Proceedings of the IEEE, 2010‏ - ieeexplore.ieee.org
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 …

Majorization-minimization algorithms in signal processing, communications, and machine learning

Y Sun, P Babu, DP Palomar - IEEE Transactions on Signal …, 2016‏ - ieeexplore.ieee.org
This paper gives an overview of the majorization-minimization (MM) algorithmic framework,
which can provide guidance in deriving problem-driven algorithms with low computational …

Learning k for kNN Classification

S Zhang, X Li, M Zong, X Zhu, D Cheng - ACM Transactions on …, 2017‏ - dl.acm.org
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 …

Acoustic beamforming for noise source localization–Reviews, methodology and applications

P Chiariotti, M Martarelli, P Castellini - Mechanical Systems and Signal …, 2019‏ - Elsevier
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 …

[PDF][PDF] Self-weighted multiview clustering with multiple graphs.

F Nie, J Li, X Li - IJCAI, 2017‏ - ijcai.org
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 …

Global convergence of ADMM in nonconvex nonsmooth optimization

Y Wang, W Yin, J Zeng - Journal of Scientific Computing, 2019‏ - Springer
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 …

[کتاب][B] An invitation to compressive sensing

S Foucart, H Rauhut, S Foucart, H Rauhut - 2013‏ - Springer
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 …

A unified algorithmic framework for block-structured optimization involving big data: With applications in machine learning and signal processing

M Hong, M Razaviyayn, ZQ Luo… - IEEE Signal Processing …, 2015‏ - ieeexplore.ieee.org
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 …

A compressive hyperspectral video imaging system using a single-pixel detector

Y Xu, L Lu, V Saragadam, KF Kelly - Nature Communications, 2024‏ - nature.com
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 …