Information maximization perspective of orthogonal matching pursuit with applications to explainable ai
A Chattopadhyay, R Pilgrim… - Advances in Neural …, 2024 - proceedings.neurips.cc
Abstract Information Pursuit (IP) is a classical active testing algorithm for predicting an output
by sequentially and greedily querying the input in order of information gain. However, IP is …
by sequentially and greedily querying the input in order of information gain. However, IP is …
Blade tip timing for monitoring crack propagation of rotor blades using Block-AOLS
Blade tip timing (BTT) as a non-contact measurement technique can identify the blade
vibration parameters. However, the signal recorded by BTT usually does not satisfy the …
vibration parameters. However, the signal recorded by BTT usually does not satisfy the …
Sparse identification of Volterra models for power amplifiers without pseudoinverse computation
We present a new formulation of the doubly orthogonal matching pursuit (DOMP) algorithm
for the sparse recovery of Volterra series models. The proposal works over the covariance …
for the sparse recovery of Volterra series models. The proposal works over the covariance …
On the benefits of progressively increasing sampling sizes in stochastic greedy weak submodular maximization
Many problems in signal processing and machine learning can be formalized as weak
submodular optimization tasks. For such problems, a simple greedy algorithm (Greedy) is …
submodular optimization tasks. For such problems, a simple greedy algorithm (Greedy) is …
Evolutionary self-expressive models for subspace clustering
The problem of organizing data that evolves over time into clusters is encountered in a
number of practical settings. We introduce evolutionary subspace clustering, a method …
number of practical settings. We introduce evolutionary subspace clustering, a method …
A Nonlinear Modeling Framework for Force Estimation in Human-Robot Interaction
In modern applied research concerning human-machine interaction, the possibility of
increasing the degree of intelligence and dexterity of the controlled plant by imitating human …
increasing the degree of intelligence and dexterity of the controlled plant by imitating human …
Cooperative spectrum sensing for Internet of Things using modeling of power-spectral-density estimation errors
L Niu, F Li - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
The application of cognitive radio (CR) technology to the Internet of Things (IoT) network can
effectively solve the bottleneck problem of spectrum scarcity. As one of the key steps in …
effectively solve the bottleneck problem of spectrum scarcity. As one of the key steps in …
Efficient least residual greedy algorithms for sparse recovery
G Leibovitz, R Giryes - IEEE Transactions on Signal Processing, 2020 - ieeexplore.ieee.org
We present a novel stagewise strategy for improving greedy algorithms for sparse recovery.
We demonstrate its efficiency both for synthesis and analysis sparse priors, where in both …
We demonstrate its efficiency both for synthesis and analysis sparse priors, where in both …
Sparse inversion of potential field data based on Orthogonal Least Squares (OLS)
LX YE, YJ ZHANG, CY LUO - Progress in Geophysics, 2023 - en.dzkx.org
Traditional gravity and magnetic inversion methods are mostly based on the minimization of
the norm constrained by the observation data and model parameters, and use Conjugate …
the norm constrained by the observation data and model parameters, and use Conjugate …
Hyperspectral image recovery using a color camera for detecting colonies of foodborne pathogens on agar plate
Purpose Hyperspectral imaging often requires a special camera system to obtain spectral
images. The cost for acquisition and process of hyperspectral images is usually much higher …
images. The cost for acquisition and process of hyperspectral images is usually much higher …