581 citations · 1.8k across the 41 of their papers we have counts for
6 papers · 1 filter
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
Gauthier Gidel, David Balduzzi, Wojciech Marian Czarnecki +2
Adversarial training, a special case of multi-objective optimization, is an increasingly prevalent machine learning technique: some of its most notable applications include GAN-bas…
Compliance-Aware Bandits
Nicolás Della Penna, Mark D. Reid, David Balduzzi
Motivated by clinical trials, we study bandits with observable non-compliance. At each step, the learner chooses an arm, after, instead of observing only the reward, it also observ…
Correlated random features for fast semi-supervised learning
Brian McWilliams, David Balduzzi, Joachim M. Buhmann
This paper presents Correlated Nystrom Views (XNV), a fast semi-supervised algorithm for regression and classification. The algorithm draws on two main ideas. First, it generates t…
Domain Generalization via Invariant Feature Representation
Krikamol Muandet, David Balduzzi, Bernhard Schölkopf
This paper investigates domain generalization: How to take knowledge acquired from an arbitrary number of related domains and apply it to previously unseen domains? We propose Doma…
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function
Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein +2
We propose a novel Bayesian approach to solve stochastic optimization problems that involve finding extrema of noisy, nonlinear functions. Previous work has focused on representing…
Falsification and future performance
David Balduzzi
We information-theoretically reformulate two measures of capacity from statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. We show these capacity…