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Found 6 papers, 1 papers with code
Multi-Armed Bandits with Interference
Prior research on experimentation with interference has concentrated on the final output of a policy.
Constrained Two-step Look-Ahead Bayesian Optimization
Recent advances in computationally efficient non-myopic Bayesian optimization offer improved query efficiency over traditional myopic methods like expected improvement, with only a modest increase in computational cost.
Bayesian Optimization of Risk Measures
We consider Bayesian optimization of objective functions of the form $\rho[ F(x, W) ]$, where $F$ is a black-box expensive-to-evaluate function and $\rho$ denotes either the VaR or CVaR risk measure, computed with respect to the randomness induced by the environmental random variable $W$.
Practical Two-Step Lookahead Bayesian Optimization
Expected improvement and other acquisition functions widely used in Bayesian optimization use a "one-step" assumption: they value objective function evaluations assuming no future evaluations will be performed.
Unbiased Comparative Evaluation of Ranking Functions
Eliciting relevance judgments for ranking evaluation is labor-intensive and costly, motivating careful selection of which documents to judge.
A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution
We present a novel hierarchical distance-dependent Bayesian model for event coreference resolution.
