**Bayesian Optimization with Uncertain Preferences over Attributes**

R. Astudillo & P.I. Frazier

*Artificial Intelligence and Statistics (AISTATS)*, 2020.

**Parallel Bayesian Global Optimization of Expensive Functions**

J. Wang, S.C. Clark, E. Liu & P.I. Frazier

*Operations Research*, to appear.

**Probabilistic Bisection Converges Almost As Quickly As Stochastic Approximation**

P.I. Frazier, S.G. Henderson, R. Waeber

*Mathematics of Operations Research*, 2019.

**Practical Two-Step Lookahead Bayesian Optimization**

J. Wu, P.I. Frazier

*Neural Information Processing Systems (NeurIPS)*, 2019.

**Information Design in Spatial Resource Competition**

P. Yang, K. Iyer, P.I. Frazier

*The 15th Conference on Web and Internet Economics (WINE)*, 2019.

**Bayesian Optimization of Composite Functions**

R. Astudillo, P.I. Frazier

*International Conference on Machine Learning (ICML)*, 2019.
[Slides,
Code]

**Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning**

J. Wu, S. Toscano-Palmerin, P.I. Frazier, A.G. Wilson

*Conference on Uncertainty in Artificial Intelligence (UAI)*, 2019.

**Discovering de novo peptide substrates for enzymes using machine learning**

L. Tallorin, J. Wang, W.E. Kim, S. Sahu, N.M. Kosa, P. Yang, M. C. Thompson, M. K. Gilson, P. I. Frazier, N. C. Gianneschi, M. D. Burkart

**Mean Field Equilibria for Resource Competition in Spatial Settings**

P. Yang, K. Iyer and P.I. Frazier

*Stochastic Systems*, 2018.

**Efficient Search of a Complex Compositional Space of Hybrid Organic-Inorganic Perovskite Candidates via Bayesian Optimization**

M. Poloczek, H. Herbol, W. Hu, P.I. Frazier, and P. Clancy

*npj (Nature Partner Journals) Computational Materials*, 2018.

**Surge Pricing Moves Uber's Driver Partners**

A. Lu, P.I. Frazier, O. Kislev

*19th ACM Conference on Economics and Computation (EC)*, 2018.

**Incentivizing Exploration with Heterogeneous Preferences**

B. Chen, P.I. Frazier, D. Kempe

*Conference on Learning Theory (COLT)*, 2018.
[Slides]

**Effort Allocation and Statistical Inference for 1-Dimensional Multistart Stochastic Gradient Descent**

S. Toscano-Palmerin and P.I. Frazier

*Winter Simulation Conference (WSC)*, 2018.

**Bayesian Optimization**

P.I. Frazier

*INFORMS Tutorials*, 2018.

**Ephemeral Partially Replicated Databases**

R. Agarwal, P.I. Frazier

*4th International Conference on Artificial Intelligence and Applications (AI)*, 2018.

**Advances in Bayesian Optimization with Applications in Aerospace Engineering**

R. Lam, M. Poloczek, P.I. Frazier, K. Willcox

*20th AIAA Non-Deterministic Approaches Conference (AIAA SciTech Forum)*, 2018.

**Probabilistic Group Testing under Sum Observations: A Parallelizable 2-Approximation for Entropy Loss**

(previously titled "Twenty Questions for Localizing Multiple Objects by Counting: Bayes Optimal Policies for Entropy Loss")

W. Han, P.I. Frazier & B.M. Jedynak

*IEEE Transactions on Information Theory*, 2017.

**Dueling Bandits with Weak Regret**

B. Chen & P.I. Frazier

*International Conference on Machine Learning (ICML)*, 2017.

**Bayesian Optimization with Gradients**

J. Wu, M.U. Poloczek, A.G. Wilson & P.I. Frazier

*Neural Information Processing Systems (NIPS)*, 2017.

**Multi-Information Source Optimization**

M.U. Poloczek, J. Wang, P.I. Frazier,
*Neural Information Processing Systems (NIPS)*, 2017.

**Stratified Bayesian Optimization**

S. Toscano-Palmerin & P.I. Frazier

*Proceedings of the 12th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (MCQMC)*, 2017.

**Multi-Attribute Bayesian Optimization under Utility Uncertainty**

R. Astudillo Marban & P.I. Frazier

*NIPS Workshop on Bayesian Optimization*, 2017.

**Continuous-Fidelity Bayesian Optimization with Knowledge Gradient**

R. Astudillo Marban & P.I. Frazier

*NIPS Workshop on Bayesian Optimization*, 2017.

**Bayesian Optimization via Simulation with Pairwise Sampling and Correlated Prior Beliefs**

J. Xie, P.I. Frazier & S.E. Chick

*Operations Research*, 2016.

**The Parallel Knowledge Gradient Method for Batch Bayesian Optimization**

J. Wu & P.I. Frazier

*Neural Information Processing Systems (NIPS)*, 2016.

**Coupled Bisection for Root Ordering**

S.N. Pallone, P.I. Frazier & S.G. Henderson

*Operations Research Letters*, 2016.

**Unbiased Concurrent Evaluation on a Budget**

T. Schnabel, T. Joachims, A. Swaminathan & P.I. Frazier

*2nd ACM International Conference on the Theory of Information Retrieval (ICTIR)*, 2016.

**The Bayesian Linear Information Filtering Problem**

B. Chen & P.I. Frazier

*IEEE International Conference on Tools with Artificial Intelligence (ICTAI)*, 2016.

**Warm Starting Bayesian Optimization**

M. Poloczek, J. Wang & P.I. Frazier

*Winter Simulation Conference (WSC)*, 2016.

**Mean Field Equilibria for Competitive Exploration in Resource Sharing Settings**

P. Yang, K. Iyer & P.I. Frazier

*International World Wide Web Web Conference (WWW)*, 2016.

**Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies**

W. Hu & P.I. Frazier

*International Artificial Intelligence and Statistics Conference (AISTATS)*, 2016.

**Bayesian Optimization for Materials Design**

P.I. Frazier & J. Wang

in *Information Science for Materials Discovery and Design* Springer Series in Materials Science, 2016.

**A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution**

B. Yang, C. Cardie & P.I. Frazier

*Transactions of the Association for Computational Linguistics*, 2015.

**Distance Dependent Infinite Latent Feature Models**

S.J. Gershman, P.I. Frazier & D.M. Blei,

*IEEE Transactions on Pattern Analysis and Machine Intelligence*, 2015.

**A New Optimal Stepsize Rule for Approximate Dynamic Programming,**

I.O. Ryzhov, P.I. Frazier & W.B. Powell

*IEEE Transactions on Automatic Control*, 2015.

**Predicting Bike Usage for New York City's Bike Sharing System**

D. Singhvi, S. Singhvi, P.I. Frazier, S.G. Henderson, E. O'Mahony, D.B. Shmoys & D.B. Woodard

*AAAI-15 Workshop on Computational Sustainability*, 2015.

**Bayesian Multiple Target Localization**

P. Rajan, W. Han, R. Sznitman, P.I. Frazier & B. Jedynak

*International Conference on Machine Learning*, 2015.
[Slides]

**Asymptotic Validity of the Bayes-Inspired Indifference Zone Procedure: the Non-Normal Known Variance Case**

S. Toscano-Palmerin & P.I. Frazier
*Winter Simulation Conference*, 2015.

**A Fully Sequential Elimination Procedure for Indifference-Zone Ranking and Selection with Tight Bounds on Probability of Correct Selection**

P.I. Frazier

*Operations Research*, 2014.
[Slides]

**Incentiving Exploration**

P.I. Frazier, D. Kempe, R. Kleinberg & J. Kleinberg

*ACM Conference on Economics and Computation*, 2014.

**A Markov Decision Process Analysis of the Cold Start Problem in Bayesian Information Filtering**

X. Zhao & P.I. Frazier

*NIPS Workshop on Personalization: Methods and Applications*, 2014.

**Parallel Bayesian Policies for Finite-Horizon Multiple Comparisons with a Known Standard**

W. Hu, P.I. Frazier & J. Xie

*Winter Simulation Conference*, 2014.

**Multisection: Parallelized Bisection**

S. Pallone, P.I. Frazier, S.G. Henderson

*Winter Simulation Conference*, 2014.

**Sequential Bayes-Optimal Policies for Multiple Comparisons with a Control**

J. Xie & P.I. Frazier

*Operations Research*, 2013.

**Bisection Search with Noisy Responses**

R. Waeber, P.I. Frazier & S.G. Henderson

*SIAM Journal on Control and Optimization*, 2013.

**ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies**

S.C. Clark, R. Egan, P.I. Frazier & Z. Wang

*Bioinformatics*, 2013.
[Publisher]

**Advances in Simulation Optimization and its Applications**

L.H. Lee, E.P. Chew, P.I. Frazier, Q.S. Jia & C.H. Chen

*IIE Transactions*, 2013.

**Upper Bounds for Bayesian Ranking & Selection**

J. Xie & P.I. Frazier

*Winter Simulation Conference*, 2013.

**An Optimal Policy for Target Localization with Application to Electron Microscopy**

R. Sznitman, A. Lucchi, B. Jedynak, P.I. Frazier & P. Fua

*International Conference on Machine Learning (ICML)*, 2013.

**Sequential Sampling with Economics of Selection Procedures**

S.E. Chick & P.I. Frazier

*Management Science*, 2012.
[Publisher]

**The Knowledge-Gradient Algorithm for a General Class of Online Learning Problems**

I.O. Ryzhov, W.B. Powell & P.I. Frazier

*Operations Research*, 2012.
[Publisher]

**A Framework for Selecting a Selection Procedure**

R. Waeber, P.I. Frazier & S.G. Henderson

*ACM Transactions on Modeling and Computer Simulation*, 2012.
[Publisher]

**Twenty Questions with Noise: Bayes Optimal Policies for Entropy Loss**

B. Jedynak, P.I. Frazier & R. Sznitman

*Journal of Applied Probability*, 2012.
[Publisher]

**Risk Factors for Early Failure after Peripheral Endovascular Intervention: Application of a Reliability Engineering Approach**

A.J. Meltzer, A. Graham, P.H. Connolly, J.K. Karwowski, H.L. Bush, P.I. Frazier & D.B. Schneider

*Annals of Vascular Surgery*, 2012.
[Publisher]

**Tutorial: Optimization via Simulation with Bayesian Statistics and Dynamic Programming**

P.I. Frazier

*Winter Simulation Conference*, 2012.
[Slides]

**Sequential Screening: A Bayesian Dynamic Programming Analysis of Optimal Group-Splitting**

P.I. Frazier, B. Jedynak & L. Chen

*Winter Simulation Conference*, 2012.
[Slides]

**Optimal Patient-specific Postoperative Surveillance for Vascular Surgery**

S. Zhang, P. Hanagal, P.I. Frazier, A.J. Meltzer & D.B. Schneider

*7th INFORMS Workshop on Data Mining and Health Informatics*, 2012.
i[Slides]

**Optimization of Computationally Expensive Simulations with Gaussian Processes and Parameter Uncertainty: Application to Cardiovascular Surgery**

J. Xie, P.I. Frazier, S. Sankaran, A. Marsden & S. Elmohamed

*50th Annual Allerton Conference on Communication, Control, and Computing*, 2012.
[Slides]

**Hierarchical Knowledge Gradient for Sequential Sampling**

M.R.K. Mes, W.B. Powell & P.I. Frazier

*Journal of Machine Learning Research*, 2011.

**The Correlated Knowledge Gradient for Simulation Optimization of Continuous Parameters Using Gaussian Process Regression**

W. Scott, P.I. Frazier & W.B. Powell

*SIAM Journal on Optimization*, 2011.
[Publisher]

**The Knowledge-Gradient Algorithm for Sequencing Experiments in Drug Discovery**

D. Negoescu, P.I. Frazier & W.B. Powell

*INFORMS Journal on Computing*, 2011.
[Publisher]

**Distance Dependent Chinese Restaurant Processes**

D.M. Blei & P.I. Frazier

*Journal of Machine Learning Research*, 2011.
[Publisher]

**Consistency of Sequential Bayesian Sampling Policies**

P.I. Frazier & W.B. Powell

*SIAM Journal on Control and Optimization*, 2011.
[Slides]

**A Bayesian Approach to Stochastic Root Finding**

R. Waeber, P.I. Frazier & S.G. Henderson

*Winter Simulation Conference*, 2011.

**Bayesian Optimization via Simulation with Correlated Sampling and Correlated Prior Beliefs**

P.I. Frazier, J. Xie & S.E. Chick

*Winter Simulation Conference*, 2011.
[Slides]

**Guessing Preferences: A New Approach to Multi-Attribute Ranking and Selection**

P.I. Frazier & A.M. Kazachkov

*Winter Simulation Conference*, 2011.
[Slides]

**Paradoxes in Learning and the Marginal Value of Information**

P.I. Frazier & W.B. Powell

*Decision Analysis*, 2010.
[Slides]

**Performance Measures for Ranking and Selection Procedures**

R. Waeber, P.I. Frazier & S.G. Henderson

*Winter Simulation Conference*, 2010.
[Slides]

**Distance Dependent Chinese Restaurant Processes**

D. Blei & P.I. Frazier

*International Conference on Machine Learning*, 2010.

**On the Robustness of a One-Period Look-Ahead Policy in Multi-Armed Bandit Problems**

I.O. Ryzhov, P.I. Frazier & W.B. Powell

*International Conference on Computational Stochastics*, 2010.
[Publisher]

**Decision-Theoretic Foundations of Simulation Optimization**

P.I. Frazier

*Wiley Encyclopedia of Operations Research & Management Science*, 2010.

**Learning with Dynamic Programming**

P.I. Frazier

*Wiley Encyclopedia of Operations Research & Management Science*, 2010.

**The Knowledge-Gradient Policy for Correlated Normal Beliefs**

P.I. Frazier, W.B. Powell & S. Dayanik

*INFORMS Journal on Computing*, 2009.
[Slides]

**Simulation Model Calibration with Correlated Knowledge-Gradients**

P.I. Frazier, W.B. Powell & H.P. Simao

*Winter Simulation Conference*, 2009.
[Slides]

**The Conjunction of the Knowledge Gradient and the Economic Approach to Simulation Selection**

S. Chick & P.I. Frazier

*Winter Simulation Conference*, 2009.
[Slides]

**Approximate Dynamic Programming in Knowledge Discovery for Rapid Response**

P.I. Frazier, W.B. Powell, S. Dayanik & P. Kantor

*Hawaii International Conference on Systems Science*, 2009.

**Knowledge-Gradient Methods for Statistical Learning**

P.I. Frazier

*PhD Thesis, Princeton University*, 2009.
[Slides]

**A Knowledge-Gradient Policy for Sequential Information Collection**

P.I. Frazier, W.B. Powell & S. Dayanik

*SIAM Journal on Control and Optimization*, 2008.
[Publisher, Slides]

**The Knowledge-Gradient Stopping Rule for Ranking and Selection**

P.I. Frazier & W.B. Powell

*Winter Simulation Conference*, 2008.
[Slides]

**Optimal Learning**

W.B.Powell & P.I. Frazier

*TutORials in Operations Research, INFORMS*, 2008.
[Slides]

**Sequential Hypothesis Testing under Stochastic Deadlines**

P.I. Frazier & A.J. Yu

*Neural Information Processing Systems*, 2007.
[Slides]

**The Knowledge Gradient Policy for Offline Learning with Independent Normal Rewards**

P.I. Frazier & W.B. Powell

*IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning*, 2007.
[Slides]

**Optimal Learning Policies for the Newsvendor Problem with Censored Demand and Unobservable Lost Sales**

D. Negoescu, P.I. Frazier & W.B. Powell

**Clustering via Content-Augmented Stochastic Blockmodels**

J.M. Cashore, X. Zhao, A.A. Alemi, Y. Liu & P.I. Frazier

**Multi-Step Bayesian Optimization for One-Dimensional Feasibility Determination**

J.M. Cashore, L. Kumarga & P.I. Frazier

**Dueling Bandits with Dependent Arms**

B. Chen & P.I. Frazier,

**Exploration vs. Exploitation in the Information Filtering Problem**

X. Zhao & P.I. Frazier