18 citations · 76 across the 14 of their papers we have counts for
14 papers
Optimal rates for density and mode estimation with expand-and-sparsify representations
Kaushik Sinha, Christopher Tosh
Expand-and-sparsify representations are a class of theoretical models that capture sparse representation phenomena observed in the sensory systems of many animals. At a high level,…
Robustifying likelihoods by optimistically re-weighting data
Miheer Dewaskar, Christopher Tosh, Jeremias Knoblauch +1
Likelihood-based inferences have been remarkably successful in wide-spanning application areas. However, even after due diligence in selecting a good model for the data at hand, th…
Targeted active learning for probabilistic models
Christopher Tosh, Mauricio Tec, Wesley Tansey
A fundamental task in science is to design experiments that yield valuable insights about the system under study. Mathematically, these insights can be represented as a utility or…
Simple and near-optimal algorithms for hidden stratification and multi-group learning
Christopher Tosh, Daniel Hsu
Multi-group agnostic learning is a formal learning criterion that is concerned with the conditional risks of predictors within subgroups of a population. The criterion addresses re…
Bayesian decision-making under misspecified priors with applications to meta-learning
Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy +4
Thompson sampling and other Bayesian sequential decision-making algorithms are among the most popular approaches to tackle explore/exploit trade-offs in (contextual) bandits. The c…
The piranha problem: Large effects swimming in a small pond
Christopher Tosh, Philip Greengard, Ben Goodrich +3
In some scientific fields, it is common to have certain variables of interest that are of particular importance and for which there are many studies indicating a relationship with…