Martin Takác

According to our database1, Martin Takác authored at least 85 papers between 1997 and 2021.

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Bibliography

2021
Roles for Event Representations in Sensorimotor Experience, Memory Formation, and Language Processing.
Top. Cogn. Sci., 2021

Inexact SARAH algorithm for stochastic optimization.
Optim. Methods Softw., 2021

An accelerated communication-efficient primal-dual optimization framework for structured machine learning.
Optim. Methods Softw., 2021

Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information.
CoRR, 2021

Improving Text-to-Image Synthesis Using Contrastive Learning.
CoRR, 2021

AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods.
CoRR, 2021

Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences.
Comput. Optim. Appl., 2021

Active metric learning for supervised classification.
Comput. Chem. Eng., 2021

A platform for embodied models of infant cognition, and its use in a model of event perception.
Proceedings of the IEEE International Conference on Development and Learning, 2021

SONIA: A Symmetric Blockwise Truncated Optimization Algorithm.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory.
SIAM J. Matrix Anal. Appl., 2020

A robust multi-batch L-BFGS method for machine learning.
Optim. Methods Softw., 2020

A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning.
J. Mach. Learn. Res., 2020

Applying deep learning to the newsvendor problem.
IISE Trans., 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

Constrained Combinatorial Optimization with Reinforcement Learning.
CoRR, 2020

Structural sensing with deep learning: Strain estimation from acceleration data for fatigue assessment.
Comput. Aided Civ. Infrastructure Eng., 2020

Scaling Up Quasi-newton Algorithms: Communication Efficient Distributed SR1.
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

SOM-Based System for Sequence Chunking and Planning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 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
New Convergence Aspects of Stochastic Gradient Algorithms.
J. Mach. Learn. Res., 2019

Distributed Fixed Point Methods with Compressed Iterates.
CoRR, 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

Don't Forget Your Teacher: A Corrective Reinforcement Learning Framework.
CoRR, 2019

Quasi-Newton Methods for Deep Learning: Forget the Past, Just Sample.
CoRR, 2019

Distributed Learning with Compressed Gradient Differences.
CoRR, 2019

Multi-Agent Image Classification via Reinforcement Learning.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Entropy-Penalized Semidefinite Programming.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
On the complexity of parallel coordinate descent.
Optim. Methods Softw., 2018

On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches.
CoRR, 2018

Active Metric Learning for Supervised Classification.
CoRR, 2018

Deep Reinforcement Learning for Solving the Vehicle Routing Problem.
CoRR, 2018

Matrix Completion Under Interval Uncertainty: Highlights.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Reinforcement Learning for Solving the Vehicle Routing Problem.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

SGD and Hogwild! Convergence Without the Bounded Gradients Assumption.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Hybrid Methods in Solving Alternating-Current Optimal Power Flows.
IEEE Trans. Smart Grid, 2017

A low-rank coordinate-descent algorithm for semidefinite programming relaxations of optimal power flow.
Optim. Methods Softw., 2017

Distributed optimization with arbitrary local solvers.
Optim. Methods Softw., 2017

CoCoA: A General Framework for Communication-Efficient Distributed Optimization.
J. Mach. Learn. Res., 2017

Cooperation Via Intimidation: An Emergent System of Mutual Threats can Maintain Social Order.
J. Artif. Soc. Soc. Simul., 2017

Matrix completion under interval uncertainty.
Eur. J. Oper. Res., 2017

Underestimate Sequences via Quadratic Averaging.
CoRR, 2017

Stock-out Prediction in Multi-echelon Networks.
CoRR, 2017

A Deep Q-Network for the Beer Game with Partial Information.
CoRR, 2017

Stochastic Recursive Gradient Algorithm for Nonconvex Optimization.
CoRR, 2017

Cognitive adaptations to criminal justice lead to "paranoid" norm obedience.
Adapt. Behav., 2017

SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient.
Proceedings of the 34th International Conference on Machine Learning, 2017

Distributed Inexact Damped Newton Method: Data Partitioning and Work-Balancing.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

Distributed Hessian-Free Optimization for Deep Neural Network.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
On optimal probabilities in stochastic coordinate descent methods.
Optim. Lett., 2016

Parallel coordinate descent methods for big data optimization.
Math. Program., 2016

Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting.
IEEE J. Sel. Top. Signal Process., 2016

Distributed Coordinate Descent Method for Learning with Big Data.
J. Mach. Learn. Res., 2016

Linear Convergence of Randomized Feasible Descent Methods Under the Weak Strong Convexity Assumption.
J. Mach. Learn. Res., 2016

Distributed Inexact Damped Newton Method: Data Partitioning and Load-Balancing.
CoRR, 2016

Projected Semi-Stochastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption.
CoRR, 2016

Large Scale Distributed Hessian-Free Optimization for Deep Neural Network.
CoRR, 2016

Exploration of cognition-affect and Type 1-Type 2 dichotomies in a computational model of decision making.
Cogn. Syst. Res., 2016

A Multi-Batch L-BFGS Method for Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Primal-Dual Rates and Certificates.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Working memory encoding of events and their participants: a neural network model with applications in sensorimotor processing and sentence generation.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

Mechanisms for storing and accessing event representations in episodic memory, and their expression in language: a neural network model.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

2015
Distributed Mini-Batch SDCA.
CoRR, 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

Dual Free SDCA for Empirical Risk Minimization with Adaptive Probabilities.
CoRR, 2015

A Neural Network Model of Episode Representations in Working Memory.
Cogn. Comput., 2015

Adding vs. Averaging in Distributed Primal-Dual Optimization.
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

Inequality-Constrained Matrix Completion: Adding the Obvious Helps!
CoRR, 2014

mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting.
CoRR, 2014

Communication-Efficient Distributed Dual Coordinate Ascent.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Fast distributed coordinate descent for non-strongly convex losses.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

2013
TOP-SPIN: TOPic discovery via Sparse Principal component INterference.
CoRR, 2013

Mini-Batch Primal and Dual Methods for SVMs.
Proceedings of the 30th International Conference on Machine Learning, 2013

A neural network model of working memory for episodes.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 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

A Sentence Generation Network That Learns Surface and Abstract Syntactic Structures.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2008
Autonomous construction of ecologically and socially relevant semantics.
Cogn. Syst. Res., 2008

1997
Fixed Point Classification Method for Qualitative Simulation.
Proceedings of the Progress in Artificial Intelligence, 1997


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