Andrei Patrascu

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 22

Top Topics

Anomaly Detection

Convergence Rate

Lagrange Multipliers

Top Venues

IEEE Trans. Autom. Control.

Publications

Andrei Patrascu, Cristian Rusu, Paul Irofti
Learning Explicitly Conditioned Sparsifying Transforms. CoRR (2024)
Paul Irofti, Andrei Iulian Hîji, Andrei Patrascu, Nicolae Cleju
Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly Detection. CoRR (2024)
Paul Irofti, Andrei Patrascu, Andrei Iulian Hîji
Unsupervised Abnormal Traffic Detection through Topological Flow Analysis. COMM (2022)
Andrei Patrascu, Paul Irofti
On finite termination of an inexact Proximal Point algorithm. Appl. Math. Lett. 134 (2022)
Paul Irofti, Andrei Patrascu, Andrei Iulian Hîji
Unsupervised Abnormal Traffic Detection through Topological Flow Analysis. CoRR (2022)
Paul Irofti, Cristian Rusu, Andrei Patrascu
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection. CoRR (2022)
Paul Irofti, Cristian Rusu, Andrei Patrascu
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection. ICASSP (2022)
Andrei Patrascu, Paul Irofti
Stochastic proximal splitting algorithm for composite minimization. Optim. Lett. 15 (6) (2021)
Andrei Patrascu, Paul Irofti
Computational complexity of Inexact Proximal Point Algorithm for Convex Optimization under Holderian Growth. CoRR (2021)
Andrei Patrascu, Ciprian Paduraru, Paul Irofti
Stochastic Proximal Gradient Algorithm with Minibatches. Application to Large Scale Learning Models. CoRR (2020)
Paul Irofti, Andrei Patrascu, Andra Baltoiu
Fraud Detection in Networks: State-of-the-art. CoRR (2019)
Andra Baltoiu, Andrei Patrascu, Paul Irofti
Community-Level Anomaly Detection for Anti-Money Laundering. CoRR (2019)
Andrei Patrascu, Paul Irofti
Stochastic proximal splitting algorithm for stochastic composite minimization. CoRR (2019)
Ion Necoara, Andrei Patrascu, François Glineur
Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming. Optim. Methods Softw. 34 (2) (2019)
Andrei Patrascu
On convergence rate of stochastic proximal point algorithm without strong convexity, smoothness or bounded gradients. CoRR (2019)
Ion Necoara, Peter Richtárik, Andrei Patrascu
Randomized Projection Methods for Convex Feasibility: Conditioning and Convergence Rates. SIAM J. Optim. 29 (4) (2019)
Andrei Patrascu, Ion Necoara
On the Convergence of Inexact Projection Primal First-Order Methods for Convex Minimization. IEEE Trans. Autom. Control. 63 (10) (2018)
Ion Necoara, Andrei Patrascu
OR-SAGA: Over-relaxed stochastic average gradient mapping algorithms for finite sum minimization. ECC (2018)
Andrei Patrascu, Ion Necoara
Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization. J. Mach. Learn. Res. 18 (2017)
Andrei Patrascu, Ion Necoara, Quoc Tran-Dinh
Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization. Optim. Lett. 11 (3) (2017)
Andrei Patrascu, Ion Necoara
Complexity certifications of inexact projection primal gradient method for convex problems: Application to embedded MPC. MED (2016)
Ion Necoara, Andrei Patrascu
Iteration complexity analysis of dual first-order methods for conic convex programming. Optim. Methods Softw. 31 (3) (2016)
Andrei Patrascu, Ion Necoara
Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization. J. Glob. Optim. 61 (1) (2015)
Andrei Patrascu, Ion Necoara
Random Coordinate Descent Methods for Sparse Optimization: Application to Sparse Control. CSCS (2015)
Andrei Patrascu, Ion Necoara
Regularized Convex Optimization. IEEE Trans. Autom. Control. 60 (7) (2015)
Ion Necoara, Andrei Patrascu
On the behavior of first-order penalty methods for conic constrained convex programming when Lagrange multipliers do not exist. CDC (2015)
Andrei Patrascu, Ion Necoara, Rolf Findeisen
Rate of convergence analysis of a dual fast gradient method for general convex optimization. CDC (2015)
Andrei Patrascu, Ion Necoara, Panagiotis Patrinos
A proximal alternating minimization method for ℓ0-regularized nonlinear optimization problems: application to state estimation. CDC (2014)
Ion Necoara, Andrei Patrascu
A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints. Comput. Optim. Appl. 57 (2) (2014)
Andrei Patrascu, Ion Necoara
A random coordinate descent algorithm for large-scale sparse nonconvex optimization. ECC (2013)