Martin Takác
Orcid: 0000-0001-7455-2025Affiliations:
- Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE
- Lehigh University, Bethlehem, PA, USA (former)
According to our database1,
Martin Takác
authored at least 116 papers
between 2011 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Comput. Manag. Sci., June, 2024
Optim. Lett., April, 2024
CoRR, 2024
Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows.
CoRR, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Trans. Mach. Learn. Res., 2023
SANIA: Polyak-type Optimization Framework Leads to Scale Invariant Stochastic Algorithms.
CoRR, 2023
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks.
CoRR, 2023
In Quest of Ground Truth: Learning Confident Models and Estimating Uncertainty in the Presence of Annotator Noise.
CoRR, 2023
Reinforcement Learning Approach to Stochastic Vehicle Routing Problem With Correlated Demands.
IEEE Access, 2023
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
On the Study of Curriculum Learning for Inferring Dispatching Policies on the Job Shop Scheduling.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Optim. Methods Softw., 2022
A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization.
Manuf. Serv. Oper. Manag., 2022
IEEE J. Sel. Top. Signal Process., 2022
Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes.
EURO J. Comput. Optim., 2022
Gradient Descent and the Power Method: Exploiting their connection to find the leftmost eigen-pair and escape saddle points.
CoRR, 2022
FLECS-CGD: A Federated Learning Second-Order Framework via Compression and Sketching with Compressed Gradient Differences.
CoRR, 2022
Robustness Analysis of Classification Using Recurrent Neural Networks with Perturbed Sequential Input.
CoRR, 2022
A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Towards Practical Large Scale Non-Linear Semi-Supervised Learning with Balancing Constraints.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
2021
An accelerated communication-efficient primal-dual optimization framework for structured machine learning.
Optim. Methods Softw., 2021
Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences.
Comput. Optim. Appl., 2021
Proceedings of the Distributed Autonomous Robotic Systems - 15th International Symposium, 2021
Proceedings of the 32nd British Machine Vision Conference 2021, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
SIAM J. Matrix Anal. Appl., 2020
J. Mach. Learn. Res., 2020
Reinforcement Learning based Multi-Robot Classification via Scalable Communication Structure.
CoRR, 2020
DynNet: Physics-based neural architecture design for linear and nonlinear structural response modeling and prediction.
CoRR, 2020
Structural sensing with deep learning: Strain estimation from acceleration data for fatigue assessment.
Comput. Aided Civ. Infrastructure Eng., 2020
Proceedings of the Machine Learning, Optimization, and Data Science, 2020
Finite Difference Neural Networks: Fast Prediction of Partial Differential Equations.
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
J. Mach. Learn. Res., 2019
Convolutional Neural Network Approach for Robust Structural Damage Detection and Localization.
J. Comput. Civ. Eng., 2019
FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods.
CoRR, 2019
A Layered Architecture for Active Perception: Image Classification using Deep Reinforcement Learning.
CoRR, 2019
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
2018
Frontiers Appl. Math. Stat., 2018
CoRR, 2018
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
IEEE Trans. Smart Grid, 2017
A low-rank coordinate-descent algorithm for semidefinite programming relaxations of optimal power flow.
Optim. Methods Softw., 2017
J. Mach. Learn. Res., 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient.
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
Optim. Lett., 2016
IEEE J. Sel. Top. Signal Process., 2016
J. Mach. Learn. Res., 2016
Linear Convergence of Randomized Feasible Descent Methods Under the Weak Strong Convexity Assumption.
J. Mach. Learn. Res., 2016
CoRR, 2016
Projected Semi-Stochastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption.
CoRR, 2016
CoRR, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Linear Convergence of the Randomized Feasible Descent Method Under the Weak Strong Convexity Assumption.
CoRR, 2015
Partitioning Data on Features or Samples in Communication-Efficient Distributed Optimization?
CoRR, 2015
CoRR, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function.
Math. Program., 2014
CoRR, 2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014
2013
Proceedings of the 30th International Conference on Machine Learning, 2013
2012
Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes
CoRR, 2012
2011
Efficient Serial and Parallel Coordinate Descent Methods for Huge-Scale Truss Topology Design.
Proceedings of the Operations Research Proceedings 2011, Selected Papers of the International Conference on Operations Research (OR 2011), August 30, 2011