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Found 9 papers, 0 papers with code
A Note on Randomized Kaczmarz Algorithm for Solving Doubly-Noisy Linear Systems
In this paper, we analyze the convergence of RK for noisy linear systems when the coefficient matrix, $A$, is corrupted with both additive and multiplicative noise, along with the noisy vector, $b$.
Stochastic Natural Thresholding Algorithms
Sparse signal recovery is one of the most fundamental problems in various applications, including medical imaging and remote sensing.
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization
We introduce an efficient and robust auto-tuning framework for hyperparameter selection in dimension reduction (DR) algorithms, focusing on large-scale datasets and arbitrary performance metrics.
AVIDA: Alternating method for Visualizing and Integrating Data
In general applications, other methods can be used for the alignment and dimension reduction modules.
Iterative Hard Thresholding for Low CP-rank Tensor Models
In this paper, we utilize the same tensor version of the Restricted Isometry Property (RIP) to extend these results for tensors with low CANDECOMP/PARAFAC (CP) rank.
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
Machine learning algorithms typically rely on optimization subroutines and are well-known to provide very effective outcomes for many types of problems.
Analysis of Fast Structured Dictionary Learning
Sparsity-based models and techniques have been exploited in many signal processing and imaging applications.
Analysis of Fast Alternating Minimization for Structured Dictionary Learning
Alternating minimization algorithms have been particularly popular in dictionary or transform learning.
Improving Image Clustering using Sparse Text and the Wisdom of the Crowds
We propose a method to improve image clustering using sparse text and the wisdom of the crowds.
