101 citations · 125 across the 10 of their papers we have counts for
10 papers
Don't trust your eyes: on the (un)reliability of feature visualizations
Robert Geirhos, Roland S. Zimmermann, Blair Bilodeau +2
How do neural networks extract patterns from pixels? Feature visualizations attempt to answer this important question by visualizing highly activating patterns through optimization…
Impossibility Theorems for Feature Attribution
Blair Bilodeau, Natasha Jaques, Pang Wei Koh +1
Despite a sea of interpretability methods that can produce plausible explanations, the field has also empirically seen many failure cases of such methods. In light of these results…
On the Tightness of the Laplace Approximation for Statistical Inference
Blair Bilodeau, Yanbo Tang, Alex Stringer
Laplace's method is used to approximate intractable integrals in a statistical problems. The relative error rate of the approximation is not worse than . We provide th…
Asymptotics of numerical integration for two-level mixed models
Alex Stringer, Blair Bilodeau, Yanbo Tang
We study mixed models with a single grouping factor, where inference about unknown parameters requires optimizing a marginal likelihood defined by an intractable integral. Low-dime…
Adaptively Exploiting d-Separators with Causal Bandits
Blair Bilodeau, Linbo Wang, Daniel M. Roy
Multi-armed bandit problems provide a framework to identify the optimal intervention over a sequence of repeated experiments. Without additional assumptions, minimax optimal perfor…
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers
Jeffrey Negrea, Blair Bilodeau, Nicolò Campolongo +2
Quantile (and, more generally, KL) regret bounds, such as those achieved by NormalHedge (Chaudhuri, Freund, and Hsu 2009) and its variants, relax the goal of competing against the…
Minimax Rates for Conditional Density Estimation via Empirical Entropy
Blair Bilodeau, Dylan J. Foster, Daniel M. Roy
We consider the task of estimating a conditional density using i.i.d. samples from a joint distribution, which is a fundamental problem with applications in both classification and…
Stochastic Convergence Rates and Applications of Adaptive Quadrature in Bayesian Inference
Blair Bilodeau, Alex Stringer, Yanbo Tang
We provide the first stochastic convergence rates for a family of adaptive quadrature rules used to normalize the posterior distribution in Bayesian models. Our results apply to th…
Relaxing the I.I.D. Assumption: Adaptively Minimax Optimal Regret via Root-Entropic Regularization
Blair Bilodeau, Jeffrey Negrea, Daniel M. Roy
We consider prediction with expert advice when data are generated from distributions varying arbitrarily within an unknown constraint set. This semi-adversarial setting includes (a…
High-Priority Expected Waiting Times in the Delayed Accumulating Priority Queue with Applications to Health Care KPIs
Blair Bilodeau, David A. Stanford
We provide the first analytical expressions for the expected waiting time of high-priority customers in the delayed APQ by exploiting a classical conservation law for work-conservi…