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ORCIDPeter I. Frazier
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- affiliation: Cornell University, School of Operations Research and Information Engineering
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2020 – today
- 2024
[j26]J. Massey Cashore
, Peter I. Frazier, Éva Tardos:
Dynamic Pricing Provides Robust Equilibria in Stochastic Ridesharing Networks. Math. Oper. Res. 49(3): 1647-1677 (2024)- [c51]Poompol Buathong, Jiayue Wan, Raul Astudillo, Samuel Daulton, Maximilian Balandat, Peter I. Frazier:
Bayesian Optimization of Function Networks with Partial Evaluations. ICML 2024 - [i42]Su Jia, Peter I. Frazier, Nathan Kallus:
Multi-Armed Bandits with Interference. CoRR abs/2402.01845 (2024) - [i41]Samuel Tan, Peter I. Frazier:
Asymptotically Optimal Regret for Black-Box Predict-then-Optimize. CoRR abs/2406.07866 (2024) - [i40]Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin:
Cost-aware Bayesian optimization via the Pandora's Box Gittins index. CoRR abs/2406.20062 (2024) - 2023
- [c50]Raul Astudillo, Zhiyuan (Jerry) Lin, Eytan Bakshy, Peter I. Frazier:
qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization. AISTATS 2023: 1093-1114 - [c49]Su Jia, Qian Xie, Nathan Kallus, Peter I. Frazier:
Smooth Non-stationary Bandits. ICML 2023: 14930-14944 - [i39]Su Jia, Qian Xie, Nathan Kallus, Peter I. Frazier:
Smooth Non-Stationary Bandits. CoRR abs/2301.12366 (2023) - [i38]Raul Astudillo, Zhiyuan (Jerry) Lin, Eytan Bakshy, Peter I. Frazier:
qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization. CoRR abs/2303.15746 (2023) - [i37]Adelinde M. Uhrmacher, Peter I. Frazier, Reiner Hähnle, Franziska Klügl, Fabian Lorig, Bertram Ludäscher, Laura Nenzi, Cristina Ruiz Martin, Bernhard Rumpe, Claudia Szabo, Gabriel A. Wainer, Pia Wilsdorf:
Context, Composition, Automation, and Communication - The C2AC Roadmap for Modeling and Simulation. CoRR abs/2310.05649 (2023) - [i36]Poompol Buathong, Jiayue Wan, Samuel Daulton, Raul Astudillo, Maximilian Balandat, Peter I. Frazier:
Bayesian Optimization of Function Networks with Partial Evaluations. CoRR abs/2311.02146 (2023) - 2022
- [j25]Saul Toscano-Palmerin, Peter I. Frazier:
Bayesian Optimization with Expensive Integrands. SIAM J. Optim. 32(2): 417-444 (2022) - [c48]Zhiyuan (Jerry) Lin, Raul Astudillo, Peter I. Frazier, Eytan Bakshy:
Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes. AISTATS 2022: 4235-4258 - [c47]J. Massey Cashore, Peter I. Frazier, Éva Tardos:
Dynamic Pricing Provides Robust Equilibria in Stochastic Ride-Sharing Networks. EC 2022: 301-302 - [i35]Raul Astudillo, Peter I. Frazier:
Thinking inside the box: A tutorial on grey-box Bayesian optimization. CoRR abs/2201.00272 (2022) - [i34]Zhiyuan (Jerry) Lin, Raul Astudillo, Peter I. Frazier, Eytan Bakshy:
Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes. CoRR abs/2203.11382 (2022) - [i33]Xiangyu Zhang, Peter I. Frazier:
Near-optimality for infinite-horizon restless bandits with many arms. CoRR abs/2203.15853 (2022) - [i32]J. Massey Cashore, Peter I. Frazier, Éva Tardos:
Dynamic Pricing Provides Robust Equilibria in Stochastic Ridesharing Networks. CoRR abs/2205.09679 (2022) - 2021
- [c46]Yunxiang Zhang, Xiangyu Zhang, Peter I. Frazier:
Two-step lookahead Bayesian optimization with inequality constraints. NeurIPS 2021: 12563-12575 - [c45]Raul Astudillo, Peter I. Frazier:
Bayesian Optimization of Function Networks. NeurIPS 2021: 14463-14475 - [c44]Raul Astudillo, Daniel R. Jiang, Maximilian Balandat, Eytan Bakshy, Peter I. Frazier:
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs. NeurIPS 2021: 20197-20209 - [c43]Raul Astudillo, Peter I. Frazier:
Thinking Inside the Box: A Tutorial on Grey-Box Bayesian Optimization. WSC 2021: 1-15 - [i31]Xiangyu Zhang, Peter I. Frazier:
Restless Bandits with Many Arms: Beating the Central Limit Theorem. CoRR abs/2107.11911 (2021) - [i30]Raul Astudillo, Daniel R. Jiang, Maximilian Balandat, Eytan Bakshy, Peter I. Frazier:
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs. CoRR abs/2111.06537 (2021) - [i29]Yunxiang Zhang, Xiangyu Zhang, Peter I. Frazier:
Two-step Lookahead Bayesian Optimization with Inequality Constraints. CoRR abs/2112.02833 (2021) - [i28]Raul Astudillo, Peter I. Frazier:
Bayesian Optimization of Function Networks. CoRR abs/2112.15311 (2021) - 2020
- [j24]Jialei Wang, Scott C. Clark, Eric Liu, Peter I. Frazier:
Parallel Bayesian Global Optimization of Expensive Functions. Oper. Res. 68(6): 1850-1865 (2020) - [c42]Raul Astudillo, Peter I. Frazier:
Multi-attribute Bayesian optimization with interactive preference learning. AISTATS 2020: 4496-4507 - [c41]Sait Cakmak, Raul Astudillo, Peter I. Frazier, Enlu Zhou:
Bayesian Optimization of Risk Measures. NeurIPS 2020 - [i27]Francisco Castro, Peter I. Frazier, Hongyao Ma, Hamid Nazerzadeh, Chiwei Yan:
Matching Queues, Flexibility and Incentives. CoRR abs/2006.08863 (2020) - [i26]Sait Cakmak, Raul Astudillo, Peter I. Frazier, Enlu Zhou:
Bayesian Optimization of Risk Measures. CoRR abs/2007.05554 (2020)
2010 – 2019
- 2019
- [j23]Peter I. Frazier, Shane G. Henderson, Rolf Waeber:
Probabilistic Bisection Converges Almost as Quickly as Stochastic Approximation. Math. Oper. Res. 44(2): 651-667 (2019) - [c40]Raul Astudillo, Peter I. Frazier:
Bayesian Optimization of Composite Functions. ICML 2019: 354-363 - [c39]Jian Wu, Peter I. Frazier:
Practical Two-Step Lookahead Bayesian Optimization. NeurIPS 2019: 9810-9820 - [c38]Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson:
Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning. UAI 2019: 788-798 - [c37]Pu Yang, Krishnamurthy Iyer, Peter I. Frazier:
Information Design in Spatial Resource Competition. WINE 2019: 346 - [i25]Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson:
Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning. CoRR abs/1903.04703 (2019) - [i24]Raul Astudillo, Peter I. Frazier:
Bayesian Optimization of Composite Functions. CoRR abs/1906.01537 (2019) - [i23]Pu Yang, Krishnamurthy Iyer, Peter I. Frazier:
Information Design in Spatial Resource Competition. CoRR abs/1909.12723 (2019) - [i22]Raul Astudillo, Peter I. Frazier:
Bayesian Optimization with Uncertain Preferences over Attributes. CoRR abs/1911.05934 (2019) - 2018
- [c36]Bangrui Chen, Peter I. Frazier, David Kempe:
Incentivizing Exploration by Heterogeneous Users. COLT 2018: 798-818 - [c35]Alice Lu, Peter I. Frazier, Oren Kislev:
Surge Pricing Moves Uber's Driver-Partners. EC 2018: 3 - [c34]Peter I. Frazier:
Bridging the Gap from Academic Research to Industry Impact. WSC 2018: 10 - [c33]Saul Toscano-Palmerin, Peter I. Frazier:
Effort Allocation and Statistical Inference for 1-dimensional Multistart stochastic Gradient Descent. WSC 2018: 1850-1861 - [i21]Saul Toscano-Palmerin, Peter I. Frazier:
Bayesian Optimization with Expensive Integrands. CoRR abs/1803.08661 (2018) - [i20]Peter I. Frazier:
A Tutorial on Bayesian Optimization. CoRR abs/1807.02811 (2018) - 2017
- [j22]Weidong Han, Purnima Rajan, Peter I. Frazier, Bruno M. Jedynak:
Bayesian Group Testing Under Sum Observations: A Parallelizable Two-Approximation for Entropy Loss. IEEE Trans. Inf. Theory 63(2): 915-933 (2017) - [c32]Bangrui Chen, Peter I. Frazier:
Dueling Bandits with Weak Regret. ICML 2017: 731-739 - [c31]Matthias Poloczek, Jialei Wang, Peter I. Frazier:
Multi-Information Source Optimization. NIPS 2017: 4288-4298 - [c30]Jian Wu, Matthias Poloczek, Andrew Gordon Wilson, Peter I. Frazier:
Bayesian Optimization with Gradients. NIPS 2017: 5267-5278 - [i19]Stephen N. Pallone, Peter I. Frazier, Shane G. Henderson:
Bayes-Optimal Entropy Pursuit for Active Choice-Based Preference Learning. CoRR abs/1702.07694 (2017) - [i18]Jian Wu, Matthias Poloczek, Andrew Gordon Wilson, Peter I. Frazier:
Bayesian Optimization with Gradients. CoRR abs/1703.04389 (2017) - [i17]Bangrui Chen, Peter I. Frazier:
Dueling Bandits With Weak Regret. CoRR abs/1706.04304 (2017) - [i16]Pu Yang, Krishnamurthy Iyer, Peter I. Frazier:
Mean Field Equilibria for Resource Competition in Spatial Settings. CoRR abs/1707.07919 (2017) - 2016
- [j21]Jing Xie, Peter I. Frazier, Stephen E. Chick:
Bayesian Optimization via Simulation with Pairwise Sampling and Correlated Prior Beliefs. Oper. Res. 64(2): 542-559 (2016) - [j20]Stephen Pallone, Peter I. Frazier, Shane G. Henderson:
Coupled bisection for root ordering. Oper. Res. Lett. 44(2): 165-169 (2016) - [c29]Weici Hu, Peter I. Frazier:
Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies. AISTATS 2016: 324-332 - [c28]Bangrui Chen, Peter I. Frazier:
The Bayesian Linear Information Filtering Problem. ICTAI 2016: 270-277 - [c27]Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims:
Unbiased Comparative Evaluation of Ranking Functions. ICTIR 2016: 109-118 - [c26]Jian Wu, Peter I. Frazier:
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization. NIPS 2016: 3126-3134 - [c25]Theresa Roeder, Peter I. Frazier, Roberto Szechtman, Enlu Zhou:
Preface. WSC 2016: 1-4 - [c24]Matthias Poloczek, Jialei Wang, Peter I. Frazier:
Warm starting Bayesian optimization. WSC 2016: 770-781 - [c23]Pu Yang, Krishnamurthy Iyer, Peter I. Frazier:
Mean Field Equilibria for Competitive Exploration in Resource Sharing Settings. WWW 2016: 177-187 - [i15]Saul Toscano-Palmerin, Peter I. Frazier:
Stratified Bayesian Optimization. CoRR abs/1602.02338 (2016) - [i14]Pu Yang, Krishnamurthy Iyer, Peter I. Frazier:
Mean Field Equilibria for Competitive Exploration in Resource Sharing Settings. CoRR abs/1602.06571 (2016) - [i13]Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims:
Unbiased Comparative Evaluation of Ranking Functions. CoRR abs/1604.07209 (2016) - [i12]Bangrui Chen, Peter I. Frazier:
Dueling Bandits with Dependent Arms. CoRR abs/1605.08838 (2016) - [i11]Bangrui Chen, Peter I. Frazier:
The Bayesian Linear Information Filtering Problem. CoRR abs/1605.09088 (2016) - [i10]Jian Wu, Peter I. Frazier:
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization. CoRR abs/1606.04414 (2016) - [i9]J. Massey Cashore, Lemuel Kumarga, Peter I. Frazier:
Multi-Step Bayesian Optimization for One-Dimensional Feasibility Determination. CoRR abs/1607.03195 (2016) - [i8]Matthias Poloczek, Jialei Wang, Peter I. Frazier:
Warm Starting Bayesian Optimization. CoRR abs/1608.03585 (2016) - 2015
- [j19]Samuel Gershman, Peter I. Frazier, David M. Blei:
Distance Dependent Infinite Latent Feature Models. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 334-345 (2015) - [j18]Ilya O. Ryzhov, Peter I. Frazier, Warren B. Powell:
A New Optimal Stepsize for Approximate Dynamic Programming. IEEE Trans. Autom. Control. 60(3): 743-758 (2015) - [j17]Bishan Yang, Claire Cardie, Peter I. Frazier:
A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution. Trans. Assoc. Comput. Linguistics 3: 517-528 (2015) - [c22]Divya Singhvi, Somya Singhvi, Peter I. Frazier, Shane G. Henderson, Eoin O'Mahony, David B. Shmoys, Dawn B. Woodard:
Predicting Bike Usage for New York City's Bike Sharing System. AAAI Workshop: Computational Sustainability 2015 - [c21]Purnima Rajan, Weidong Han, Raphael Sznitman, Peter I. Frazier, Bruno Jedynak:
Bayesian Multiple Target Localization. ICML 2015: 1945-1953 - [c20]Saul Toscano-Palmerin, Peter I. Frazier:
Asymptotic validity of the bayes-inspired indifference zone procedure: the non-normal known variance case. WSC 2015: 3868-3879 - [i7]Bishan Yang, Claire Cardie, Peter I. Frazier:
A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution. CoRR abs/1504.05929 (2015) - [i6]J. Massey Cashore, Xiaoting Zhao, Alexander A. Alemi, Yujia Liu, Peter I. Frazier:
Clustering via Content-Augmented Stochastic Blockmodels. CoRR abs/1505.06538 (2015) - [i5]Weici Hu, Peter I. Frazier:
Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies. CoRR abs/1512.09204 (2015) - 2014
- [j16]Peter I. Frazier:
A Fully Sequential Elimination Procedure for Indifference-Zone Ranking and Selection with Tight Bounds on Probability of Correct Selection. Oper. Res. 62(4): 926-942 (2014) - [c19]Peter I. Frazier, David Kempe, Jon M. Kleinberg, Robert Kleinberg:
Incentivizing exploration. EC 2014: 5-22 - [c18]Stephen Pallone, Peter I. Frazier, Shane G. Henderson:
Multisection: parallelized bisection. WSC 2014: 3773-3784 - [c17]Weici Hu, Peter I. Frazier, Jing Xie:
Parallel bayesian policies for finite-horizon multiple comparisons with a known standard. WSC 2014: 3904-3915 - [i4]Ilya O. Ryzhov, Peter I. Frazier, Warren B. Powell:
A New Optimal Stepsize For Approximate Dynamic Programming. CoRR abs/1407.2676 (2014) - [i3]Weidong Han, Peter I. Frazier, Bruno M. Jedynak:
Twenty Questions for Localizing Multiple Objects by Counting: Bayes Optimal Policies for Entropy Loss. CoRR abs/1407.4446 (2014) - [i2]Xiaoting Zhao, Peter I. Frazier:
Exploration vs. Exploitation in the Information Filtering Problem. CoRR abs/1407.8186 (2014) - [i1]Xiaoting Zhao, Peter I. Frazier:
A Markov Decision Process Analysis of the Cold Start Problem in Bayesian Information Filtering. CoRR abs/1410.7852 (2014) - 2013
- [j15]Scott C. Clark, Rob Egan, Peter I. Frazier, Zhong Wang:
ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies. Bioinform. 29(4): 435-443 (2013) - [j14]Jing Xie, Peter I. Frazier:
Sequential Bayes-Optimal Policies for Multiple Comparisons with a Known Standard. Oper. Res. 61(5): 1174-1189 (2013) - [j13]Rolf Waeber, Peter I. Frazier, Shane G. Henderson:
Bisection Search with Noisy Responses. SIAM J. Control. Optim. 51(3): 2261-2279 (2013) - [c16]Raphael Sznitman, Aurélien Lucchi, Peter I. Frazier, Bruno Jedynak, Pascal Fua:
An Optimal Policy for Target Localization with Application to Electron Microscopy. ICML (1) 2013: 1-9 - [c15]Jing Xie, Peter I. Frazier:
Upper bounds on the Bayes-optimal procedure for ranking & selection with independent normal priors. WSC 2013: 877-887 - 2012
- [j12]Ilya O. Ryzhov, Warren B. Powell, Peter I. Frazier:
The Knowledge Gradient Algorithm for a General Class of Online Learning Problems. Oper. Res. 60(1): 180-195 (2012) - [j11]Bruno Jedynak, Peter I. Frazier, Raphael Sznitman:
Twenty Questions with Noise: Bayes Optimal Policies for Entropy Loss. J. Appl. Probab. 49(1): 114-136 (2012) - [j10]Stephen E. Chick, Peter I. Frazier:
Sequential Sampling with Economics of Selection Procedures. Manag. Sci. 58(3): 550-569 (2012) - [j9]Rolf Waeber, Peter I. Frazier, Shane G. Henderson:
A Framework for Selecting a Selection Procedure. ACM Trans. Model. Comput. Simul. 22(3): 16:1-16:23 (2012) - [c14]Jing Xie, Peter I. Frazier, Sethuraman Sankaran, Alison L. Marsden, Saleh Elmohamed:
Optimization of computationally expensive simulations with Gaussian processes and parameter uncertainty: Application to cardiovascular surgery. Allerton Conference 2012: 406-413 - [c13]Peter I. Frazier:
Optimization via simulation with Bayesian statistics and dynamic programming. WSC 2012: 7:1-7:16 - [c12]Peter I. Frazier, Bruno Jedynak, Li Chen:
Sequential screening: a Bayesian dynamic programming analysis of optimal group-splitting. WSC 2012: 50:1-50:12 - 2011
- [j8]Diana M. Negoescu, Peter I. Frazier, Warren B. Powell:
The Knowledge-Gradient Algorithm for Sequencing Experiments in Drug Discovery. INFORMS J. Comput. 23(3): 346-363 (2011) - [j7]David M. Blei, Peter I. Frazier:
Distance Dependent Chinese Restaurant Processes. J. Mach. Learn. Res. 12: 2461-2488 (2011) - [j6]Martijn R. K. Mes, Warren B. Powell, Peter I. Frazier:
Hierarchical Knowledge Gradient for Sequential Sampling. J. Mach. Learn. Res. 12: 2931-2974 (2011) - [j5]Peter I. Frazier, Warren B. Powell:
Consistency of Sequential Bayesian Sampling Policies. SIAM J. Control. Optim. 49(2): 712-731 (2011) - [j4]Warren R. Scott, Peter I. Frazier, Warren B. Powell:
The Correlated Knowledge Gradient for Simulation Optimization of Continuous Parameters using Gaussian Process Regression. SIAM J. Optim. 21(3): 996-1026 (2011) - [c11]Peter I. Frazier, Jing Xie, Stephen E. Chick:
Value of information methods for pairwise sampling with correlations. WSC 2011: 3979-3991 - [c10]Rolf Waeber, Peter I. Frazier, Shane G. Henderson:
A Bayesian approach to stochastic root finding. WSC 2011: 4038-4050 - [c9]Peter I. Frazier, Aleksandr M. Kazachkov:
Guessing preferences: a new approach to multi-attribute ranking and selection. WSC 2011: 4324-4336 - 2010
- [j3]Peter I. Frazier, Warren B. Powell:
Paradoxes in Learning and the Marginal Value of Information. Decis. Anal. 7(4): 378-403 (2010) - [c8]David M. Blei, Peter I. Frazier:
Distance dependent Chinese restaurant processes. ICML 2010: 87-94 - [c7]Rolf Waeber, Peter I. Frazier, Shane G. Henderson:
Performance measures for Ranking and Selection procedures. WSC 2010: 1235-1245 - [c6]Ilya O. Ryzhov, Peter I. Frazier, Warren B. Powell:
On the robustness of a one-period look-ahead policy in multi-armed bandit problems. ICCS 2010: 1635-1644
2000 – 2009
- 2009
- [j2]Peter I. Frazier, Warren B. Powell, Savas Dayanik:
The Knowledge-Gradient Policy for Correlated Normal Beliefs. INFORMS J. Comput. 21(4): 599-613 (2009) - [c5]Peter I. Frazier, Warren B. Powell, Savas Dayanik, Paul B. Kantor:
Approximate Dynamic Programming in Knowledge Discovery for Rapid Response. HICSS 2009: 1-10 - [c4]Peter I. Frazier, Warren B. Powell, Hugo P. Simão:
Simulation Model Calibration with Correlated Knowledge-gradients. WSC 2009: 339-351 - [c3]Stephen E. Chick, Peter I. Frazier:
The Conjunction of the Knowledge Gradient and the Economic Approach to Simulation Selection. WSC 2009: 528-539 - 2008
- [j1]Peter I. Frazier, Warren B. Powell, Savas Dayanik:
A Knowledge-Gradient Policy for Sequential Information Collection. SIAM J. Control. Optim. 47(5): 2410-2439 (2008) - [c2]Peter I. Frazier, Warren B. Powell:
The knowledge-gradient stopping rule for ranking and selection. WSC 2008: 305-312 - 2007
- [c1]Peter I. Frazier, Angela J. Yu:
Sequential Hypothesis Testing under Stochastic Deadlines. NIPS 2007: 465-472
Coauthor Index
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