Guido Montúfar
Orcid: 0000-0002-0131-2669
According to our database1,
Guido Montúfar
authored at least 81 papers
between 2011 and 2024.
Collaborative distances:
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Bibliography
2024
J. Symb. Comput., March, 2024
Fisher-Rao Gradient Flows of Linear Programs and State-Action Natural Policy Gradients.
CoRR, 2024
2023
Int. J. Approx. Reason., October, 2023
Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks.
J. Mach. Learn. Res., 2023
Proceedings of the International Conference on Machine Learning, 2023
Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Sharp Bounds for the Number of Regions of Maxout Networks and Vertices of Minkowski Sums.
SIAM J. Appl. Algebra Geom., March, 2022
Found. Comput. Math., 2022
Solving infinite-horizon POMDPs with memoryless stochastic policies in state-action space.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Oversquashing in GNNs through the lens of information contraction and graph expansion.
Proceedings of the 58th Annual Allerton Conference on Communication, 2022
2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Mathematical and Scientific Machine Learning, 2021
Proceedings of the IEEE International Symposium on Information Theory, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the Geometric Science of Information - 5th International Conference, 2021
2020
Implicit bias of gradient descent for mean squared error regression with wide neural networks.
CoRR, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
2019
Proceedings of the Mathematical Aspects of Computer and Information Sciences, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Geometric Science of Information - 4th International Conference, 2019
2018
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018
2017
SIAM J. Appl. Algebra Geom., 2017
Int. J. Approx. Reason., 2017
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017
Proceedings of the Geometric Science of Information - Third International Conference, 2017
2016
Evaluating Morphological Computation in Muscle and DC-Motor Driven Models of Hopping Movements.
Frontiers Robotics AI, 2016
CoRR, 2016
2015
SIAM J. Discret. Math., 2015
J. Mach. Learn. Res., 2015
Geometry and Determinism of Optimal Stationary Control in Partially Observable Markov Decision Processes.
CoRR, 2015
Universal Approximation of Markov Kernels by Shallow Stochastic Feedforward Networks.
CoRR, 2015
Proceedings of the 3rd International Conference on Learning Representations, 2015
Evaluating Morphological Computation in Muscle and DC-motor Driven Models of Human Hopping.
CoRR, 2015
2014
Universal Approximation Depth and Errors of Narrow Belief Networks with Discrete Units.
Neural Comput., 2014
Kybernetika, 2014
On the number of inference regions of deep feed forward networks with piece-wise linear activations.
Proceedings of the 2nd International Conference on Learning Representations, 2014
Expressive Power of Conditional Restricted Boltzmann Machines for Sensorimotor Control.
CoRR, 2014
Sequential Recurrence-Based Multidimensional Universal Source Coding of Lempel-Ziv Type.
CoRR, 2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
2013
Mixture decompositions of exponential families - using a decomposition of their sample spaces.
Kybernetika, 2013
Kybernetika, 2013
Proceedings of the Geometric Science of Information - First International Conference, 2013
2012
On the expressive power of discrete mixture models, restricted Boltzmann machines, and deep belief networks: a unified mathematical treatment.
PhD thesis, 2012
2011
Refinements of Universal Approximation Results for Deep Belief Networks and Restricted Boltzmann Machines.
Neural Comput., 2011
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011