Andrei Patrascu

Orcid: 0000-0002-9293-9386

According to our database1, Andrei Patrascu authored at least 28 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly Detection.
CoRR, 2024

Learning Explicitly Conditioned Sparsifying Transforms.
CoRR, 2024

2022
On finite termination of an inexact Proximal Point algorithm.
Appl. Math. Lett., 2022

Unsupervised Abnormal Traffic Detection through Topological Flow Analysis.
Proceedings of the 14th International Conference on Communications, 2022

Dictionary Learning with Uniform Sparse Representations for Anomaly Detection.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Stochastic proximal splitting algorithm for composite minimization.
Optim. Lett., 2021

Computational complexity of Inexact Proximal Point Algorithm for Convex Optimization under Holderian Growth.
CoRR, 2021

2020
Stochastic Proximal Gradient Algorithm with Minibatches. Application to Large Scale Learning Models.
CoRR, 2020

2019
Randomized Projection Methods for Convex Feasibility: Conditioning and Convergence Rates.
SIAM J. Optim., 2019

Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming.
Optim. Methods Softw., 2019

Stochastic proximal splitting algorithm for stochastic composite minimization.
CoRR, 2019

Community-Level Anomaly Detection for Anti-Money Laundering.
CoRR, 2019

Fraud Detection in Networks: State-of-the-art.
CoRR, 2019

On convergence rate of stochastic proximal point algorithm without strong convexity, smoothness or bounded gradients.
CoRR, 2019

2018
On the Convergence of Inexact Projection Primal First-Order Methods for Convex Minimization.
IEEE Trans. Autom. Control., 2018

OR-SAGA: Over-relaxed stochastic average gradient mapping algorithms for finite sum minimization.
Proceedings of the 16th European Control Conference, 2018

2017
Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization.
Optim. Lett., 2017

Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization.
J. Mach. Learn. Res., 2017

2016
Iteration complexity analysis of dual first-order methods for conic convex programming.
Optim. Methods Softw., 2016

Complexity certifications of inexact projection primal gradient method for convex problems: Application to embedded MPC.
Proceedings of the 24th Mediterranean Conference on Control and Automation, 2016

2015
Random Coordinate Descent Methods for ℓ<sub>0</sub> Regularized Convex Optimization.
IEEE Trans. Autom. Control., 2015

Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization.
J. Glob. Optim., 2015

Random Coordinate Descent Methods for Sparse Optimization: Application to Sparse Control.
Proceedings of the 20th International Conference on Control Systems and Computer Science, 2015

Rate of convergence analysis of a dual fast gradient method for general convex optimization.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

On the behavior of first-order penalty methods for conic constrained convex programming when Lagrange multipliers do not exist.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014
A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints.
Comput. Optim. Appl., 2014

A proximal alternating minimization method for ℓ0-regularized nonlinear optimization problems: application to state estimation.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013
A random coordinate descent algorithm for large-scale sparse nonconvex optimization.
Proceedings of the 12th European Control Conference, 2013


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