17 citations · 46 across the 10 of their papers we have counts for
27 papers
Algebraic optimization of sequential decision problems
Mareike Dressler, Marina Garrote-López, Guido Montúfar +2
We study the optimization of the expected long-term reward in finite partially observable Markov decision processes over the set of stationary stochastic policies. In the case of d…
Solving infinite-horizon POMDPs with memoryless stochastic policies in state-action space
Johannes Müller, Guido Montúfar
Reward optimization in fully observable Markov decision processes is equivalent to a linear program over the polytope of state-action frequencies. Taking a similar perspective in t…
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks
Benjamin Bowman, Guido Montufar
We study the dynamics of a neural network in function space when optimizing the mean squared error via gradient flow. We show that in the underparameterized regime the network lear…
Training Wasserstein GANs without gradient penalties
Dohyun Kwon, Yeoneung Kim, Guido Montúfar +1
We propose a stable method to train Wasserstein generative adversarial networks. In order to enhance stability, we consider two objective functions using the -transform based on…
Information Complexity and Generalization Bounds
Pradeep Kr. Banerjee, Guido Montúfar
We present a unifying picture of PAC-Bayesian and mutual information-based upper bounds on the generalization error of randomized learning algorithms. As we show, Tong Zhang's info…
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang +4
The pairwise interaction paradigm of graph machine learning has predominantly governed the modelling of relational systems. However, graphs alone cannot capture the multi-level int…