
PAC Best Arm Identification Under a Deadline
We study (ϵ, δ)PAC best arm identification, where a decisionmaker must...
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Online Learning Demands in Maxmin Fairness
We describe mechanisms for the allocation of a scarce resource among mul...
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Resource Allocation in Multiarmed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism
We study exploration in stochastic multiarmed bandits when we have acce...
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Mechanism Design with Bandit Feedback
We study a multiround welfaremaximising mechanism design problem, wher...
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ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
We describe ChemBO, a Bayesian Optimization framework for generating and...
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Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
Bayesian Optimisation (BO), refers to a suite of techniques for global o...
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ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization
Optimizing an expensivetoquery function is a common task in science an...
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Noisy Blackbox Optimization with MultiFidelity Queries: A Tree Search Approach
We study the problem of blackbox optimization of a noisy function in th...
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A Flexible MultiObjective Bayesian Optimization Approach using Random Scalarizations
Many real world applications can be framed as multiobjective optimizati...
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Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming
We design a new myopic strategy for a wide class of sequential design of...
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Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Bayesian Optimisation (BO) refers to a class of methods for global optim...
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Asynchronous Parallel Bayesian Optimisation via Thompson Sampling
We design and analyse variations of the classical Thompson sampling (TS)...
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Multifidelity Bayesian Optimisation with Continuous Approximations
Bandit methods for blackbox optimisation, such as Bayesian optimisation...
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Batch Policy Gradient Methods for Improving Neural Conversation Models
We study reinforcement learning of chatbots with recurrent neural networ...
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Query Efficient Posterior Estimation in Scientific Experiments via Bayesian Active Learning
A common problem in disciplines of applied Statistics research such as A...
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Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
Recently, there has been a surge of interest in using spectral methods f...
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Multifidelity Gaussian Process Bandit Optimisation
In many scientific and engineering applications, we are tasked with the ...
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Additive Approximations in High Dimensional Nonparametric Regression via the SALSA
High dimensional nonparametric regression is an inherently difficult pro...
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High Dimensional Bayesian Optimisation and Bandits via Additive Models
Bayesian Optimisation (BO) is a technique used in optimising a Ddimensi...
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Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations
We propose and analyze estimators for statistical functionals of one or ...
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On Estimating L_2^2 Divergence
We give a comprehensive theoretical characterization of a nonparametric ...
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Nonparametric Estimation of Renyi Divergence and Friends
We consider nonparametric estimation of L_2, Renyiα and Tsallisα diver...
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