Vyacheslav Kungurtsev

Francesco Rinaldi

Damiano Zeffiro

Comput. Optim. Appl., June, 2024

Trilevel and multilevel optimization using monotone operator theory.

[BibT_eX]

[DOI]

Allahkaram Shafiei

Math. Methods Oper. Res., April, 2024

Time-Varying Semidefinite Programming: Path Following a Burer-Monteiro Factorization.

[BibT_eX]

[DOI]

Antonio Bellon

Mareike Dressler

André Uschmajew

SIAM J. Optim., March, 2024

Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration.

[BibT_eX]

[DOI]

Mahdi Morafah

Hojin Chang

Chen Chen

Bill Lin

CoRR, 2024

Probabilistic Iterative Hard Thresholding for Sparse Learning.

[BibT_eX]

[DOI]

Matteo Bergamaschi

Andrea Cristofari

Francesco Rinaldi

CoRR, 2024

Dataset Distillation from First Principles: Integrating Core Information Extraction and Purposeful Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference.

[BibT_eX]

[DOI]

Apaar

Aarya Khandelwal

Parth Sandeep Rastogi

CoRR, 2024

Learning Dynamic Bayesian Networks from Data: Foundations, First Principles and Numerical Comparisons.

[BibT_eX]

[DOI]

CoRR, 2024

Group Distributionally Robust Dataset Distillation with Risk Minimization.

[BibT_eX]

[DOI]

Saeed Vahidian

Mingyu Wang

Jianyang Gu

Erwann de Belloy de Saint-Lienard

Wei Jiang

Yiran Chen

CoRR, 2024

The Effects of Transmission-Rights Pricing on Multi-Stage Electricity Markets.

[BibT_eX]

[DOI]

CoRR, 2024

Federated SGD with Local Asynchrony.

[BibT_eX]

[DOI]

Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024

Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents.

[BibT_eX]

[DOI]

Neil Zhenqiang Gong

Yiran Chen

Proceedings of the Computer Vision - ECCV 2024, 2024

Efficient Dataset Distillation via Minimax Diffusion.

[BibT_eX]

[DOI]

Jianyang Gu

Saeed Vahidian

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Decentralized Asynchronous Nonconvex Stochastic Optimization on Directed Graphs.

[BibT_eX]

[DOI]

Mahdi Morafah

Tara Javidi

IEEE Trans. Control. Netw. Syst., December, 2023

Regularized quasi-monotone method for stochastic optimization.

[BibT_eX]

[DOI]

V. Shikhman

Optim. Lett., June, 2023

On the ergodic control of ensembles in the presence of non-linear filters.

[BibT_eX]

[DOI]

Ramen Ghosh

Robert Shorten

Autom., June, 2023

Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence.

[BibT_eX]

[DOI]

Diyuan Wu

Marco Mondelli

Trans. Mach. Learn. Res., 2023

Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo.

[BibT_eX]

[DOI]

Adam D. Cobb

Tara Javidi

Brian Jalaian

Mach. Learn., 2023

Scheduling a Multi-Product Pipeline: A Discretized MILP Formulation.

[BibT_eX]

[DOI]

Ales Wodecki

Pavel Rytír

CoRR, 2023

Quantum Solutions to the Privacy vs. Utility Tradeoff.

[BibT_eX]

[DOI]

Sagnik Chatterjee

CoRR, 2023

A Stochastic-Gradient-based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems.

[BibT_eX]

[DOI]

Frank E. Curtis

Daniel P. Robinson

Qi Wang

CoRR, 2023

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond.

[BibT_eX]

[DOI]

Philip Intallura

Georgios Korpas

Sudeepto Chakraborty

CoRR, 2023

Riemannian Stochastic Approximation for Minimizing Tame Nonsmooth Objective Functions.

[BibT_eX]

[DOI]

Johannes Aspman

Reza Roohi Seraji

CoRR, 2023

When Do Curricula Work in Federated Learning?

[BibT_eX]

[DOI]

Chen Chen

Mubarak Shah

Bill Lin

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces.

[BibT_eX]

[DOI]

Saeed Vahidian

Mahdi Morafah

Weijia Wang

Chen Chen

Mubarak Shah

Bill Lin

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Subsampling Line-Search Method with Second-Order Results.

[BibT_eX]

[DOI]

Vladimir Kunc

INFORMS J. Optim., October, 2022

Distributed stochastic nonsmooth nonconvex optimization.

[BibT_eX]

[DOI]

Oper. Res. Lett., 2022

Diminishing stepsize methods for nonconvex composite problems via ghost penalties: from the general to the convex regular constrained case.

[BibT_eX]

[DOI]

Lorenzo Lampariello

Optim. Methods Softw., 2022

A Stochastic Levenberg-Marquardt Method Using Random Models with Complexity Results.

[BibT_eX]

[DOI]

SIAM/ASA J. Uncertain. Quantification, 2022

Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.

[BibT_eX]

[DOI]

Alexander Shevchenko

Marco Mondelli

J. Mach. Learn. Res., 2022

Stochastic Langevin Differential Inclusions with Applications to Machine Learning.

[BibT_eX]

[DOI]

Fabio V. Difonzo

CoRR, 2022

Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGD.

[BibT_eX]

[DOI]

CoRR, 2022

A Sensitivity Assisted Alternating Directions Method of Multipliers for Distributed Optimization.

[BibT_eX]

[DOI]

Dinesh Krishnamoorthy

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Asynchronous Optimization Over Graphs: Linear Convergence Under Error Bound Conditions.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2021

A Nonmonotone Matrix-Free Algorithm for Nonlinear Equality-Constrained Least-Squares Problems.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2021

Complexity iteration analysis for strongly convex multi-objective optimization using a Newton path-following procedure.

[BibT_eX]

[DOI]

Optim. Lett., 2021

Ghost Penalties in Nonconvex Constrained Optimization: Diminishing Stepsizes and Iteration Complexity.

[BibT_eX]

[DOI]

Lorenzo Lampariello

Math. Oper. Res., 2021

Randomized Algorithms for Monotone Submodular Function Maximization on the Integer Lattice.

[BibT_eX]

[DOI]

Alberto Schiabel

CoRR, 2021

Decentralized Langevin Dynamics over a Directed Graph.

[BibT_eX]

[DOI]

Alexander Kolesov

CoRR, 2021

A zeroth order method for stochastic weakly convex optimization.

[BibT_eX]

[DOI]

Francesco Rinaldi

Comput. Optim. Appl., 2021

Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.

[BibT_eX]

[DOI]

Giorgi Nadiradze

Ilia Markov

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees.

[BibT_eX]

[DOI]

Malcolm Egan

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A Shifted Primal-Dual Penalty-Barrier Method for Nonlinear Optimization.

[BibT_eX]

[DOI]

Philip E. Gill

Daniel P. Robinson

SIAM J. Optim., 2020

Second-Order Guarantees of Distributed Gradient Algorithms.

[BibT_eX]

[DOI]

SIAM J. Optim., 2020

Asynchronous parallel algorithms for nonconvex optimization.

[BibT_eX]

[DOI]

Math. Program., 2020

Convergence and Complexity Analysis of a Levenberg-Marquardt Algorithm for Inverse Problems.

[BibT_eX]

[DOI]

J. Optim. Theory Appl., 2020

A Nonmonotone Matrix-Free Algorithm for Nonlinear Equality-Constrained Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2020

Stochastic Gradient Langevin with Delayed Gradients.

[BibT_eX]

[DOI]

CoRR, 2020

Reinforcement Learning Based on Real-Time Iteration NMPC.

[BibT_eX]

[DOI]

Mario Zanon

Sébastien Gros

CoRR, 2020

Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent.

[BibT_eX]

[DOI]

CoRR, 2020

Stochastic Gradient Langevin Dynamics on a Distributed Network.

[BibT_eX]

[DOI]

CoRR, 2020

Lifted Weight Learning of Markov Logic Networks (Revisited One More Time).

[BibT_eX]

[DOI]

Ondrej Kuzelka

Yuyi Wang

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

A Two-Step Pre-Processing for Semidefinite Programming.

[BibT_eX]

[DOI]

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019

Lifted Weight Learning of Markov Logic Networks Revisited.

[BibT_eX]

[DOI]

Ondrej Kuzelka

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Algorithms for solving optimization problems arising from deep neural net models: nonsmooth problems.

[BibT_eX]

[DOI]

Tomás Pevný

CoRR, 2018

Algorithms for solving optimization problems arising from deep neural net models: smooth problems.

[BibT_eX]

[DOI]

Tomás Pevný

CoRR, 2018

Second-order Guarantees of Gradient Algorithms over Networks.

[BibT_eX]

[DOI]

Proceedings of the 56th Annual Allerton Conference on Communication, 2018

2017

A Predictor-Corrector Path-Following Algorithm for Dual-Degenerate Parametric Optimization Problems.

[BibT_eX]

[DOI]

Johannes Jäschke

SIAM J. Optim., 2017

A stabilized SQP method: superlinear convergence.

[BibT_eX]

[DOI]

Philip E. Gill

Daniel P. Robinson

Math. Program., 2017

Essentially cyclic asynchronous nonconvex large-scale optimization.

[BibT_eX]

[DOI]

Proceedings of the 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2017

Capacity sensitivity in additive non-Gaussian noise channels.

[BibT_eX]

[DOI]

Malcolm Egan

Samir Medina Perlaza

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Asynchronous parallel nonconvex large-scale optimization.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Asynchronous Parallel Algorithms for Nonconvex Big-Data Optimization: Model and Convergence.

[BibT_eX]

[DOI]

CoRR, 2016

Parallel asynchronous lock-free algorithms for nonconvex big-data optimization.

[BibT_eX]

[DOI]

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

Hybrid Random/Deterministic Parallel Algorithms for Convex and Nonconvex Big Data Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2015

2014

Hybrid Random/Deterministic Parallel Algorithms for Nonconvex Big Data Optimization.

[BibT_eX]

[DOI]

CoRR, 2014

Sequential quadratic programming methods for parametric nonlinear optimization.

[BibT_eX]

[DOI]

Moritz Diehl

Comput. Optim. Appl., 2014

Linear convergence of distributed multiple shooting.

[BibT_eX]

[DOI]

Attila Kozma

Moritz Diehl

Proceedings of the 13th European Control Conference, 2014

Flexible selective parallel algorithms for big data optimization.

[BibT_eX]

[DOI]

Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013

Second-derivative sequential quadratic programming methods for nonlinear optimization

[BibT_eX]

[DOI]