Selected publications by Patrick Jaillet

2024 journal articles, conference papers

Amin, S., P. Jaillet, H. Pulyassary, and M. Wu. "Market Design for Dynamic Pricing and Pooling in Capacitated Networks". Accepted, 20th Conference on Web and Internet Economics, WINE 2024, September 2024.

Blanchard, M., A. Jacquillat, and P. Jaillet. "Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem". Mathematics of Operations Research, 49(2), 1169-1191, 2024.

Blanchard, M., J. Zhang, and P. Jaillet. "Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal". Accepted, Mathematics of Operations Research, September 2024.

Deng, Y., N. Golrezaei, P. Jaillet, J. Liang, and V. Mirrokni. "Individual Welfare Guarantees in the Autobidding World with Machine-learned Advice". ACM Web Conference 2024.

Gilmour, S., S. Sapounas, K. Drakopoulos, P. Jaillet, G. Magiorkinis, and N. Trichakis. "On the Impact of Mass Screening for SARS-CoV-2 through Self-Testing in Greece". Frontiers in Public Health, section Infectious Diseases: Epidemiology and Prevention, 06 March 2024.

Jaillet, P., C. Podimata, and Z. Zhou. "Grace Period is All You Need: Individual Fairness without Revenue Loss in Revenue Management". Accepted, 20th Conference on Web and Internet Economics, WINE 2024, September 2024.

Jaillet, P., C. Podimata, A. Vakhutinsky, and Z. Zhou. "When Should you Offer an Upgrade: Online Upgrading Mechanisms for Resource Allocation". Accepted, 20th Conference on Web and Internet Economics, WINE 2024, September 2024.

Lin, X., Z. Wu, Z. Dai, W. Hu, Y. Shu, SK. Ng, P. Jaillet, and K.H. Low. "Use Your INSTINCT: INStruction optimization usIng Neural bandits Coupled with Transformers". 41st International Conference on Machine Learning, ICML 2024.

Luo, C. P. Chen, and P. Jaillet. "Portfolio Optimization Based on Almost Second-degree Stochastic Dominance". Accepted, Management Science, April 2024.

Nguyen, Q.P., K.H. Low, and P. Jaillet. "Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes". 12th International Conference on Learning Representations, ICLR 2024.

Nguyen, Q.P., W.T.H. Chew, L. Song, K.H. Low, and P. Jaillet. "Optimistic Bayesian Optimization with Unknown Constraints". 12th International Conference on Learning Representations, ICLR 2024.

Nguyen, Q.P., S. Gupta, S. Venkatesh, K.H. Low, and P. Jaillet. "Active Set Ordering". Accepted, 38th Conference on Neural Information Processing Systems, NeurIPS 2024, September 2024.

Sim, R., J. Fan, X. Tian, P. Jaillet, and K.H. Low. "Deletion-Anticipative Data Selection with a Limited Budget". 41st International Conference on Machine Learning, ICML 2024.

Tahmasebi, B., A. Soleymani, D. Bahri, S. Jegelka, and P. Jaillet. "A Universal Class of Sharpness-Aware Minimization Algorithms". 41st International Conference on Machine Learning, ICML 2024.

Wu, Z., X. Lin, Z. Dai, W. Hu, Y. Shu, S.K. Ng, P. Jaillet, and K.H. Low. "Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars". Accepted, 38th Conference on Neural Information Processing Systems, NeurIPS 2024, September 2024.

2024 book chapters

Dai, Z., F. X. Fan, C. Tan, T.N. Hoang, K.H. Low, and P. Jaillet. "Federated sequential decision making: Bayesian optimization, reinforcement learning, and beyond". Federated Learning: Theory and Practice, chapter 14, pages 257-279, Academic Press, 2024.

Lin, X., X. Xu, Z. Wu, R. Sim, S.-K. Ng, C.-S. Foo, P. Jaillet, T.N. Hoang, and K.H. Low. "Fairness in federated learning". Federated Learning: Theory and Practice, chapter 8, pages 143-160, Academic Press, 2024.

Sim, R. S. S. Tay, X. Xu, Y. Zhang, Z. Wu, X. Lin, S.-K. Ng, C.-S. Foo, P. Jaillet, T.N. Hoang, and K.H. Low. "Incentives in federated learning". Federated Learning: Theory and Practice, chapter 16, pages 299-309, Academic Press, 2024.

Wu, Z., X. Xu, R. Sim, Y. Shu, X. Lin, L. Agussurja, Z. Dai, S.-K. Ng, C.-H. Foo, P. Jaillet, T.N. Hoang, and K.H. Low. "Data valuation in federated learning". Federated Learning: Theory and Practice, chapter 15, pages 281-296, Academic Press, 2024.

2024 arxiv/ssrn papers

Blanchard, M. and P. Jaillet. "Near-Optimal Mechanisms for Resource Allocation Without Monetary Transfers". arXiv:2408.10066, August 2024.

Jaillet, P., C. Podimata, and Z. Zhou. "Grace Period is All You Need: Individual Fairness without Revenue Loss in Revenue Management". arXiv:2402.08533, February 2024.

Jaillet, P., C. Podimata, A. Vakhutinsky, and Z. Zhou. "When Should you Offer an Upgrade: Online Upgrading Mechanisms for Resource Allocation". arXiv:2402.08804, February 2024.

Lin, X., Z. Dai, A. Verma, S.K. Ng, P. Jaillet, and K.H. Low. "Prompt Optimization with Human Feedback". arXiv:2405.17346, May 2024.

Sim, R., Y. Zhang, T.N. Hoang, X. Xu, K.H. Low, and P. Jaillet. "Incentives in Private Collaborative Machine Learning". arXiv:2404.01676, April 2024.

Tahmasebi, B., A. Soleymani, D. Bahri, S. Jegelka, and P. Jaillet. "A Universal Class of Sharpness-Aware Minimization Algorithms". arXiv:2406.03682, June 2024.

Verma, A., Z. Dai, X. Lin, P. Jaillet, and K.H. Low. "Neural Dueling Bandits". arXiv:2407.17112, July 2024.

Wu, Z., X. Lin, Z. Dai, W. Hu, Y. Shu, S.K. Ng, P. Jaillet, and K.H. Low. "Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars". arXiv:2405.16122, May 2024.

2023 journal articles, conference papers

Ashlagi, I., M. Burq, C. Dutta, P. Jaillet, A. Saberi, and C. Sholley. "Edge Weighted Online Windowed Matching". Mathematics of Operations Research, 48(2), 999-1016, 2023.

Blanchard, M. and P. Jaillet. "Universal Regression with Adversial Responses". Annals of Statistics, 51(3), 1401-1426, 2023. ("Supplementary material".) (also "arXiv:2203.05067").

Blanchard, M., J. Zhang, and P. Jaillet. "Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal". 36th Annual Conference on Learning Theory, COLT 2023, 4696-4736.

Blanchard, M., J. Zhang, and P. Jaillet. "Memory-Constrained Algorithms for Convex Optimization". 37th Conference on Neural Information Processing Systems, NeurIPS 2023.

Dai, Z., Y. Shu, A. Verma, F.X. Fan, K.H. Low, and P. Jaillet. "Federated Neural Bandit". 11th International Conference on Learning Representations, ICLR 2023.

Dai, Z., G.K.R. Lau, A. Verma, Y. Shu, K.H. Low, and P. Jaillet. "Quantum Bayesian Optimization". 37th Conference on Neural Information Processing Systems, NeurIPS 2023. (also arXiv:2310.05373, October 2023.)

Dai, Z., Q.P. Nguyen, S. Tay, D. Urano, R.C.X. Leong, K.H. Low, and P. Jaillet. "Batch Bayesian Optimization for Replicable Experimental Design". 37th Conference on Neural Information Processing Systems, NeurIPS 2023. (also arXiv:2311.01195, November 2023.)

Deng, Y., N. Golrezaei, P. Jaillet, J. Liang, and V. Mirrokni. "Multi-channel Autobidding with Budget and ROI Constraints". 40th International Conference on Machine Learning, ICML 2023, 7617-7644.

Golrezaei, N., P. Jaillet, and J. Liang. "Incentive-aware Contextual Pricing with Non-parametric Market Noise". 26th International Conference on Artificial Intelligence and Statistics, AISTATS 2023, 9331-9361.

Golrezaei, N., P. Jaillet, J. Liang, and V. Mirrokni. "Pricing against a Budget and ROI Constrained Buyer". 26th International Conference on Artificial Intelligence and Statistics, AISTATS 2023, 9282-9307.

Lam, C.T., A. Verma, K.H. Low, and P. Jaillet. "Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation". 11th International Conference on Learning Representations, ICLR 2023.

Quinzan, F., A. Soleymani, C.R. Rojas, P. Jaillet, and S. Bauer. "DRCFS: Doubly Robust Causal Feature Selection". 40th International Conference on Machine Learning, ICML 2023, 28468-28491.

Sim, R., Y. Zhang, T.N. Hoang, X. Xu, K.H. Low, and P. Jaillet. "Incentives in Private Collaborative Machine Learning". 37th Conference on Neural Information Processing Systems, NeurIPS 2023.

Shah, S., S. Amin, and P. Jaillet. "Information Disclosure about Booster Efficacy in a Non-Stationary Environment". 62nd IEEE Annual Conference on Decision and Control, CDC 2023.

Shu, Y., Z. Dai, W. Sng, A. Verma, P. Jaillet, and K.H. Low. "Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation". 11th International Conference on Learning Representations, ICLR 2023.

2023 arxiv/ssrn papers

Amin, S., P. Jaillet, H. Pulyassary, and M. Wu. "Market Design for Dynamic Pricing and Pooling in Capacitated Networks". arXiv:2307.03994v2, November 2023.

Blanchard, M., S. Hanneke, and P. Jaillet. "Adversarial Rewards in Universal Learning for Contextual Bandits". arXiv:2302.07186, June 2023.

Blanchard, M., J. Zhang, and P. Jaillet. "Memory-Constrained Algorithms for Convex Optimization via Recursive Cutting-Planes". arXiv:2306.10096, June 2023.

Gilmour, S., S. Sapounas, K. Drakopoulos, P. Jaillet, G. Magiorkinis, and N. Trichakis. "On the Impact of Mass Screening for SARS-CoV-2 through Self-Testing in Greece". medRxiv, February 2023.

Golrezaei, N., P. Jaillet, and Z. Zhou. "Online Resource Allocation with Convex-set Machine-Learned Advice". arXiv:2306.12282, June 2023.

Hanashiro, R. and P. Jaillet. "Distribution-Dependent Rates for Multi-Distribution Learning". arXiv:2312.13130, December 2023.

Lin, X., Z. Wu, Z. Dai, W. Hu, Y. Shu, SK. Ng, P. Jaillet, and K.H. Low. "Use Your INSTINCT: INStruction Tuning using Neural bandits Coupled with Transformers". arXiv:2310.02905, October 2023.

Shah, S., S. Amin, and P. Jaillet. "Information Design for Hybrid Work under Infectious Disease Transmission Risk". arXiv:2312.04073, December 2023.

Xu, A., C. Yan, C.Y. Goh, and P. Jaillet. "A Locational Demand Model for Bike Sharing". Also available at SSRN, May 2023.

Zhang, J. and P. Jaillet. "Secretary Problems with Random Number of Candidates: How Prior Distributional Information Helps". arXiv:2310.07884, October 2023.

2022 journal articles, conference papers, and arxiv/ssrn papers

Blanchard, M., S. Hanneke, and P. Jaillet. "Contextual Bandits and Optimistically Universal Learning". arXiv:2301.00241, December 2022.

Blanchard, M., A. Jacquillat, and P. Jaillet. "Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem". arXiv:2211.11063, November 2022. ("additional results and extensions".)

Bui, V., T. Mai, and P. Jaillet. "Weighted Maximum Entropy Inverse Reinforcement Learning". arXiv:2208.09611, August 2022.

Dahan, M., S. Amin, and P. Jaillet. "Probability Distributions on Partially Ordered Sets and Network Security Games". Mathematics of Operations Research, 47(1), 458-484, 2022.

Dai, Z., Y. Chen, H. Yu, K.H. Low, and P. Jaillet. "On Provably Robust Meta-Bayesian Optimization". 38th Conference on Uncertainty in Artificial Intelligence, UAI 2022, 475-485. ("Supplementary material".)

Dai, Z., Y. Shu, K.H. Low, and P. Jaillet. "Sample-Then-Optimize Batch Neural Thompson Sampling". 36th Conference on Neural Information Processing Systems, NeurIPS 2022, 23331-23344.

Dai, Z., Y. Shu, A. Verma, F.X. Fan, K.H. Low, and P. Jaillet. "Federated Neural Bandit". arXiv:2205.14309, May 2022.

Deng, Y., N. Golrezaei, P. Jaillet, J. Liang, and V. Mirrokni. "Fairness in the Autobidding-world with Machine-learned Advice". arXiv:2209.04748, September 2022.

Ghosh, S. and P. Jaillet. "An Iterative Security Game for Computing Robust and Adaptive Network Flows". Computers & Operations Research, 138, 2022.

Golrezaei, N., P. Jaillet, and Z. Zhou. "Online Resource Allocation with Samples". arXiv:2210.04774, October 2022.

Guinet, G., S. Amin, and P. Jaillet. "Effective Dimension in Bandits Problems under Censorship". 36th Conference on Neural Information Processing Systems, NeurIPS 2022, 5243-5255.

Jaillet, P., S.D. Jena, T.S. Ng, and M. Sim. "Satisficing Models Under Uncertainty". INFORMS Journal on Optimization, 4(4), 347-372, 2022.

Jaillet, P., G.G. Loke, and M. Sim. "Strategic Workforce Planning Under Uncertainty". Operations Research, 70(2), 1042-1065, 2022.

Nguyen, Q.P., K.H. Low, and P. Jaillet. "Rectifed Max-Value Entropy Search for Bayesian Optimization". arXiv:2202.13597, February 2022.

Nguyen, Q.P., K.H. Low, and P. Jaillet. "Trade-off between Payoff and Model Rewards in Fair Collaborative Machine Learning". 36th Conference on Neural Information Processing Systems, NeurIPS 2022, 30542-30553.

Shah, S., S. Amin, and P. Jaillet. "Optimal Information Provision for Strategic Hybrid Workers". 61st IEEE Annual Conference on Decision and Control, CDC 2022, 3807-3814.

2021 journal articles, conference papers, and arxiv/ssrn papers

Amin, S., P. Jaillet, and M. Wu. "Efficient Carpooling and Toll Pricing for Autonomous Transportation". arXiv:2102.09132, February 2021.

Dai, Z., K.H. Low, and P. Jaillet. "Differentially Private Federated Bayesian Optimization with Distributed Exploration". 35th Conference on Neural Information Processing Systems, NeurIPS 2021.

Delavernhe, F., P. Jaillet, A. Rossi, and M. Sevaux. "Planning a Multi-sensors Search for a Moving Target". European Journal of Operational Research, 292(2), 469-482, 2021.

Doulabi, H.H., P. Jaillet, G. Pesant, and L.M. Rousseau. "Exploiting the Structure of Two-Stage Robust Optimization Models with Exponential Scenarios". INFORMS Journal on Computing, 33(1), 143-162, 2021.

Golrezaei, N., P. Jaillet, J. Liang, and V. Mirrokni "Bidding and Pricing in Budget and ROI Constrained Markets". arXiv:2107.07725, July 2021.

Hwang, D., P. Jaillet, and V. Manshadi. "Online Resource Allocation under Partially Predictable Demand". Operations Research, 69(3), 895-915, 2021.

Hoogeboom, M., Y. Adulyasak, W. Dullaert, and P. Jaillet. "The Robust Vehicle Routing Problem with Time Window Assignments". Transportation Science, 55(2), 395-413, 2021.

Lam, C.T., N. Hoang, K.H. Low, and P. Jaillet. "Model Fusion for Personalized Learning". 38th International Conference on Machine Learning, ICML 2021, 5948-5958.

Lowalekar, M., P. Varakantham, and P. Jaillet. "Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ride Sharing". Journal of Artificial Intelligence Research, 70, 119-167, 2021.

Mai, T. and P. Jaillet. "Robust Entropy-regularized Markov Decision Processes". arXiv:2112.15364, December 2021.

Nguyen, Q.P., K.H. Low, and P. Jaillet. "An Information-Theoretic Framework for Unifying Active Learning Problems". 35th Conference on Artificial Intelligence, AAAI 2021, 9126-9134.

Nguyen, Q.P., K.H. Low, and P. Jaillet. "Learning to learn with Gaussian Processes". 37th Conference on Uncertainty in Artificial Intelligence, UAI 2021, 1466-1475.

Nguyen, Q.P., Z. Dai, K.H. Low, and P. Jaillet. "Value-at-Risk Optimization with Gaussian Processes". 38th International Conference on Machine Learning, ICML 2021, 8063-8072.

Nguyen, Q.P., Z. Dai, K.H. Low, and P. Jaillet. "Optimizing Conditional Value-at-Risk of Black-Box Functions". 35th Conference on Neural Information Processing Systems, NeurIPS 2021.

Nguyen, Q.P., S. Tay, K.H. Low, and P. Jaillet. "Top-k Ranking Bayesian Optimization". 35th Conference on Artificial Intelligence, AAAI 2021, 9135-9143.

Nguyen, Q.P., Z. Wu, K.H. Low, and P. Jaillet. "Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization". 37th Conference on Uncertainty in Artificial Intelligence, UAI 2021, 1486-1495.

Prokhorchuk, A., N. Mitrovic, U. Muhammad, A. Stevanovic, M.T. Asif, J. Dauwels, and P. Jaillet. "Estimating the Impact of High-Fidelity Rainfall Data on Traffic Conditions and Traffic Prediction". Transportation Research Record, 2675(11), 1285-1300, 2021.

Sim, R., Y. Zhang, K.H. Low, and P. Jaillet. "Collaborative Bayesian Optimization with Fair Regret". 38th International Conference on Machine Learning, ICML 2021, 9691-9701.

Yu, H., Q.P. Nguyen, K.H. Low, and P. Jaillet. "Convolutional Normalizing Flows for Deep Gaussian Processes". International Joint Conference on Neural Networks, IJCNN 2021.

2020 journal articles, conference papers, and arxiv/ssrn papers

Aboutaleb, Y., M. Ben Akiva, and P. Jaillet. "Learning Structure in Nested Logit Models". arXiv:2008.08048, August 2020.

Dai, Z., Y. Chen, K.H. Low, P. Jaillet, and T.H. Ho. "R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games". 37th International Conference on Machine Learning, ICML 2020, 2291-2301. ("Supplementary material".)

Dai, Z., K.H. Low, and P. Jaillet. "Federated Bayesian Optimization via Thompson Sampling". 34th Conference on Neural Information Processing Systems, NeurIPS 2020, 9687-9699.

Gaudio, J. and P. Jaillet. "An Improved Lower Bound for the Traveling Salesman Constant". Operations Research Letters, 48, 67-70, 2020.

Golrezaei, N., P. Jaillet, and J. Liang. "No-regret Learning in Price Competitions under Consumer Reference Effects". 34th Conference on Neural Information Processing Systems, NeurIPS 2020, 21416-21427.

Hoang, N., C.T. Lam, K.H. Low, and P. Jaillet. "Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion". 37th International Conference on Machine Learning, ICML 2020, 4282-4292. ("Supplementary material".)

Lowalekar, M., P. Varakantham, and P. Jaillet. "Competitive Ratios for Online Multi-capacity Ridesharing". 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020, 771-779.

Mai, T. and P. Jaillet. "A Relation Analysis of Markov Decision Process Frameworks". arXiv:2008.07820, August 2020.

Mellou, K., L. Marshall, K. Chintalapudi, P. Jaillet, and I. Menache. "Optimizing Onsite Food Services at Scale". 28th International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL 2020, 618-629.

Nguyen, Q.P., K.H. Low, and P. Jaillet. "Variational Bayesian Unlearning". 34th Conference on Neural Information Processing Systems, NeurIPS 2020, 16025-16036.

Prokhorchuk, A., J. Dauwels, and P. Jaillet. "Estimating Travel Time Distributions by Bayesian Network Inference". IEEE Transactions on Intelligent Transportation Systems, 21(5), 1867-1876, 2020.

2019 journal articles, conference papers, and arxiv/ssrn papers

Ashlagi, I., M. Burq, P. Jaillet, and V. Manshadi. "On Matching and Thickness in Heterogeneous Dynamic Markets". Operations Research, 67(4), 927-949, 2019.

Ashlagi, I., M. Burq, C. Dutta, P. Jaillet, A. Saberi, and C. Sholley. "Edge Weighted Online Windowed Matching". 19th ACM Conference on Economics and Computation, EC 2019, 729-742.

Bertsimas, D., A. Delarue, P. Jaillet, and S. Martin. "Travel Time Estimation in the Age of Big Data". Operations Research, 67(2), 498-515, 2019.

Bertsimas, D., A. Delarue, P. Jaillet, and S. Martin. "Optimal Explanations of Linear Models". arXiv:1907.04669, July 2019.

Bertsimas, D., A. Delarue, P. Jaillet, and S. Martin. "The Price of Interpretability". arXiv:1907.03419, July 2019.

Bertsimas, D., P. Jaillet, and N. Korolko. "The K-Server Problem via a Modern Optimization Lens". European Journal of Operational Research, 276(1), 65-78, 2019.

Bertsimas, D., P. Jaillet, and S. Martin. "Online Vehicle Routing: The Edge of Optimization in Large-Scale Applications". Operations Research, 67(1), 143-162, 2019.

Dai, Z., H. Yu, K.H. Low, and P. Jaillet. "Bayesian Optimization Meets Bayesian Optimal Stopping". 36th International Conference on Machine Learning, ICML 2019, 1496-1506. "Supplementary material".

Gaudio, J., S. Amin, and P. Jaillet. "Exponential Convergence Rates for Stochastically Ordered Markov Processes under Perturbation". Systems and Control Letters, 133, 104515, 2019.

Ghosh, S., J.Y. Koh, and P. Jaillet. "Improving Customer Satisfaction in Bike Sharing Systens through Dynamic Repositioning". 28th International Joint Conference on Artificial Intelligence, IJCAI 2019, 5864-5870.

Golrezaei, N., P. Jaillet, and J. Liang. "Incentive-aware Contextual Pricing with Non-parametric Market Noise". arXiv:1911.03508, November 2019.

Lowalekar, M., P. Varakantham, and P. Jaillet. "ZAC: A Zone pAth Construction Approach for Effective Real Time Ride Sharing". 29th International Conference on Automated Planning and Scheduling, ICAPS 2019, 528-538. (winner of the ICAPS 2019 Best Applications Paper Award.)

Mai, T., K. Chan, and P. Jaillet. "Generalized Maximum Causal Entropy for Inverse Reinforcement Learning". arXiv:1911.06928, November 2019.

Mai, T. and P. Jaillet. "Robust Multi-product Pricing under General Extreme Value Models". arXiv:1912.09552, December 2019.

Mai, T., Q.P. Nguyen, K.H. Low, and P. Jaillet. "Inverse Reinforcement Learning with Missing Data". arXiv:1911.06930, November 2019.

Mellou, K. and P. Jaillet. "Dynamic Resource Redistribution and Demand Estimation: An Application to Bike Sharing Systems". Also available at SSRN, February 2019.

Prokhorchuk, A., J. Dauwels, and P. Jaillet. "Stochastic Dynamic Pricing for Same-Day Delivery Routing". arXiv:1912.02946, December 2019.

Vidal, T., D. Gribel, and P. Jaillet. "Separable convex optimization with nested lower and upper constraints". INFORMS Journal on Optimization, 1(1), 71-90, 2019.

Yu, H., Y. Chen, Z. Dai, K.H. Low, and P. Jaillet. "Implicit Posterior Variational Inference for Deep Gaussian Processes". Spotlight, 33rd Annual Conference on Neural Information Processing Systems, NeurIPS 2019. "Appendix".

Yu, H., T.N. Hoang, K.H. Low, and P. Jaillet. "Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression". International Joint Conference on Neural Networks, IJCNN 2019.

2018 journal articles, conference papers, and arxiv/ssrn papers

Ashlagi, I., M. Burq, C. Dutta, P. Jaillet, A. Saberi, and C. Sholley. "Maximum Weight Online Matching with Deadlines". arXiv:1808.03526, August 2018.

Ashlagi, I., M. Burq, P. Jaillet, and A. Saberi. "Maximizing Efficiency in Dynamic Matching Markets". arXiv:1803.01285, March 2018.

Dahan, M., S. Amin, and P. Jaillet. "Probability Distributions on Partially Ordered Sets and Network Security Games". arXiv:1811.08516, November 2018.

Flajolet, A., S. Blandin, and P. Jaillet. "Robust Adaptive Routing under Uncertainty". Operations Research, 66(1), 210-229, 2018.

Galle, V., C. Barnhart, and P. Jaillet. "A New Binary Formulation of the Restricted Container Relocation Problem Based on a Binary Encoding of Configurations". European Journal of Operational Research, 267(2), 467-477, 2018.

Galle, V., C. Barnhart, and P. Jaillet. "Yard Crane Scheduling for Container Storage, Retrieval, and Relocation". European Journal of Operational Research, 271(1), 288-316, 2018.

Galle, V., V. Manshadi, S. Borjian, C. Barnhart, and P. Jaillet. "The Stochastic Container Relocation Problem". Transportation Science, 52(5), 1035-1058, 2018.

Gaudio, J,, S. Amin, and P. Jaillet. "Exponential Convergence Rates for Stochastically Ordered Markov Processes with Random Initial Conditions". arXiv:1810.07732, October 2018.

Hwang, D. and P. Jaillet. "Online Scheduling with Multi-State Machines". Networks, 71(3), 209-251, 2018.

Hwang, D., P. Jaillet, and V. Manshadi. "Online Resource Allocation under Partially Predictable Demand". arXiv:1810.00447. Also available at SSRN, September 2018.

Jaillet, P., G.G. Loke, and M. Sim. "Risk-based Manpower Planning: A Tractable Multi-period Model". May 2018.

Lowalekar, M., P. Varakantham, and P. Jaillet. "Online Spatio-Temporal Matching in Stochastic and Dynamic Domains". Artifical Intelligence, 261, 71-112, 2018.

Oran, A. and P. Jaillet. "An Integrated Likelihood Formulation for Characterizing the Proximity of Position Measurements to Road Segments". IEEE Transactions on Intelligent Transportation Systems, 19(6), 1839-1854, 2018.

Wu, M., L. Jin, S. Amin, and P. Jaillet. "Signaling Game-based Misbehavior Inspection in V21-enabled Highway Operations". IEEE 57st Annual Conference on Decision and Control, CDC 2018, 2728-2734.

2017 journal articles, conference papers, and some arxiv papers

Ahmed, A., P. Varakantham, M. Lowalekar, Y. Adulyasak and P. Jaillet. "Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Problems (MDPs)". Journal of Artificial Intelligence Research, 59, 229-264, 2017.

Dekel, O., A. Flajolet, N. Haghtalab, and P. Jaillet. "Online Learning with a Hint". 31st Annual Conference on Neural Information Processing Systems, NeurIPS 2017, 5299-5308.

Flajolet, A. and P. Jaillet."Real-Time Bidding with Side Information". 31st Annual Conference on Neural Information Processing Systems, NeurIPS 2017, 5162-5172.

Flajolet, A. and P. Jaillet. "Logarithmic Regret Bounds for Bandits with Knapsacks". arXiv:1510.01800v4, April 2017.

Ghosh, S., P. Varakantham, Y. Adulyasak, and P. Jaillet. "Dynamic Redeployment to Reduce Lost Demand in Bike Sharing Systems". Journal of Artificial Intelligence Research, 58, 387-430, 2017.

Goemans, M., S. Gupta, and P. Jaillet. "Newton's Method for Parametric Submodular Function Minimization". 19th Conference on Integer Programming and Combinatorial Optimization, IPCO 2017, 212-227.

Goh, C.Y. and P. Jaillet. "Structured Prediction by Conditional Risk Minimization". arXiv:1611.07096, February 2017.

Lowalekar, M., P. Varakantham, S. Ghosh, S. Jena, and P. Jaillet. "Online Repositioning in Bike Sharing Systems". 27th International Conference on Automated Planning and Scheduling, ICAPS 2017.

Zehendner, E., D. Feillet and P. Jaillet. "An Algorithm with Performance Guarantee for the Online Container Relocation Problem". European Journal of Operational Research, 259, 48-62, 2017.

2016 journal articles and conference papers

Adulyasak, Y. and P. Jaillet."Models and Algorithms for Stochastic and Robust Vehicle Routing with Deadlines". Transportation Science, 50(2), 608-626, 2016.

Asif, M.T., N. Mitrovic, J. Dauwels, and P. Jaillet. "Matrix and Tensor Based Methods for Missing Data Estimation in Large Traffic Networks". IEEE Transactions on Intelligent Transportation Systems, 17(7), 1816-1825, 2016.

Galle, V., S. Borjian Boroujeni, V. Manshadi, C. Barnhart, and P. Jaillet. "An average-case asymptotic analysis of the Container Relocation Problem". Operations Research Letters, 44(6), 723-728, 2016.

Jaillet, P., J. Qi, and M. Sim. "Routing Optimization under Uncertainty". Operations Research, 64, 186-200, 2016.

Legrain, A. and P. Jaillet. "A Stochastic Algorithm for Online Bipartite Resource Allocation Problems". Computers and Operations Research, 75, 28-37, 2016.

Ling, C.K., K.H. Low, and P. Jaillet. "Gaussian Process Planning with Lipschitz Continuous Reward Functions". 30th AAAI Conference on Artificial Intelligence, AAAI 2016, 1860-1866.

Lowalekar, M., P. Varakantham, and P. Jaillet. "Online Spatio-Temporal Matching in Stochastic and Dynamic Domains". 30th AAAI Conference on Artificial Intelligence, AAAI 2016, 3271-3277.

Mitrovic, N., A. Narayanan, M.T. Asif, A. Rauf, J. Dauwels, and P. Jaillet. "On Centralizd and Decentralized Architectures for Traffic Applications". IEEE Transactions on Intelligent Transportation Systems, 17(7), 1988-1997, 2016.

Vidal, T., P. Jaillet, and N. Maculan. "A Decomposition Algorithm for Nested Resource Allocation Problems". SIAM Journal on Optimization, 26(2), 1322-1340, 2016.

2015 journal articles and conference papers

Adulyasak, Y., P. Varakantham, A. Ahmed, and P. Jaillet. "Solving Uncertain MDPs with Objectives that are Separable over Instantiations of Model Uncertainty". 29th AAAI Conference on Artificial Intelligence, AAAI 2015, 3454-3460.

Asif, M.T., K. Srinivasan, N. Mitrovic, J. Dauwels, and P. Jaillet. "Near-Losses Compression for Large Traffic Networks". IEEE Transactions on Intelligent Transportation Systems, 16(4), 1817-1826, 2015.

Borjian, S., V. Manshadi, C. Barnhart, and P. Jaillet. "Managing Relocation and Delay in Container Terminals with Flexible Service Policies". arXiv:1503.01535v1, March 2015.

Borjian, S., V. Galle, V. Manshadi, C. Barnhart, and P. Jaillet. "Container Relocation Problem: Approximation, Asymptotic, and Incomplete Information". arXiv:1505.04229v2, October 2015.

Chen, J., K.H. Low, and P. Jaillet. "Gaussian Process Decentralized Data Fusion and Active Sensing for Spatiotemporal Traffic Modeling and Prediction in Mobility-on-Demand Systems". IEEE Transactions on Automation Science and Engineering, 12, 901-921, 2015.

Ghosh, S., P. Varakantham, Y. Adulyasak, and P. Jaillet. "Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems". 25th International Conference on Automated Planning and Scheduling, ICAPS 2015, 79-87.

Lin, M. and P. Jaillet. "On the Quickest Flow Problem in Dynamic Networks - A Parametric Min-Cost Flow Approach". Proceedings of the ACM-SIAM Symposium on Discrete Algorithms, SODA 2015, 1343-1356.

Low, K.H., J. Yu, J. Chen, and P. Jaillet. "Parallel Gaussian Process Regression for Big Data: Low-Rank Representation Meets Markov Approximation". 29th AAAI Conference on Artificial Intelligence, AAAI 2015, 2821-2827.

Mastin, A. and P. Jaillet. "Average-Case Performance of Rollout Algorithms for Knapsack Problems". Journal of Optimization Theory and Applications, 165, 964-984, 2015. "Supplementary material".

Mastin, A., P. Jaillet, and S. Chin. "Randomized Minmax Regret for Combinatorial Optimization under Uncertainty". 26th International Symposium on Algorithms and Computation, ISAAC 2015, 491-501.

Mitrovic, N., M.T. Asif, J. Dauwels, and P. Jaillet. "Low-dimensional Models for Compression, Compressed Sensing, and Prediction of Large-Scale Traffic Data". IEEE Transactions on Intelligent Transportation Systems, 16(5), 2949-2954, 2015.

Narayanan, A., N. Mitrovic, M.T. Asif, J. Dauwels and P. Jaillet. "Travel Time Estimation using Speed Predictions". 18th International IEEE Conference on Intelligent Transportation Systems, ITSC 2015, 2256-2261.

Nguyen, Q.P., K.H. Low, and P. Jaillet. "Inverse Reinforcement Learning with Locally Consistent Reward Functions". 29th Annual Conference on Neural Information Processing Systems, NIPS 2015, 1738-1746.

2014 journal articles and conference papers

Ansar, R., P. Sarampakhul, S. Ghosh, N. Mitrovic, M.T. Asif, J. Dauwels, and P. Jaillet. "Evaluation of Smart-Phone Performance for Real-Time Traffic Prediction". 17th International IEEE Annual Conference on Intelligent Transportation Systems, ITSC 2014, 3010--3015.

Asif, M.T., J. Dauwels, C.Y. Goh, A. Oran, E. Fathi, M. Xu, M.M. Dhanya, N. Mitrovic, and P. Jaillet. "Spatial and Temporal Patterns in Large-Scale Traffic Speed Prediction". IEEE Transactions on Intelligent Transportation Systems, 15, 797-804, 2014.

Dauwels, J., A. Aslam, M.T. Asif, X. Zhao, N. Mitrovic, A. Cichocki, and P. Jaillet. "Predicting Traffic Speed in Urban Transportation Subnetworks for Multiple Horizons". 13th International Conference on Control, Automation, Robotics and Vision, ICARCV 2014, 547-552.

Hoang, T.N., K.H. Low, P. Jaillet, and M. Kankanhalli. "Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes". 31st International Conference on Machine Learning, ICML 2014, 739-747.

Hoang, T.N., K.H. Low, P. Jaillet, and M. Kankanhalli. "Active Learning is Planning: Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes". European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Nectar track, ECML/PKDD 2014, 494-498.

Holleczek, T., L. Yu, J.K. Lee, O. Senn, C. Ratti, and P. Jaillet. "Detecting Weak Public Transport Connections from Cellphone and Public Transport Data". 3rd Academy of Science and Engineering (ASE) Conference on Big Data Science and Computing, BigDataScience2014.

Jaillet, P. and X. Lu. "Online Traveling Salesman Problems with Rejection Options". Networks, 64, 84-95, 2014.

Jaillet, P. and X. Lu. "Online Stochastic Matching: New Algorithms with Better Bounds". Mathematics of Operations Research, 39, 624-646, 2014.

Jaillet, P., J. Soto, and R. Zenklusen. "Advances on Matroid Secretary Problems: Free Order Model and Laminar Case". arXiv:1207.1333v2, June 2014.

Jere, S., J. Dauwels, M.T. Asif, N. Mitrovic, A. Cichocki, and P. Jaillet. "Extracting Commuting Patterns in Railway Networks through Matrix Decompositions". 13th International Conference on Control, Automation, Robotics and Vision, ICARCV 2014, 541-546.

Mitrovic, N., M.T. Asif, J. Dauwels, and P. Jaillet. "Compressed Prediction of Large-Scale Urban Traffic". IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, 5984--5988.

Mohan, D.M., M.T. Asif, N. Mitrovic, J. Dauwels, and P. Jaillet. "Wavelets on Graphs with Application to Transportation Networks". 17th International IEEE Annual Conference on Intelligent Transportation Systems, ITSC 2014, 1702--1712.

Ouyang, R., K.H. Low, J. Chen, and P. Jaillet. "Multi-Robot Active Sensing of Non-Stationary Gaussian Process-Based Environmental Phenomena". 13th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2014, 573-580.

Varakantham, P., Y. Adulyasak, and P. Jaillet. "Decentralized Stochastic Planning and Anonymity in Interactions". 28th AAAI Conference on Artificial Intelligence, AAAI 2014, 2505-2512.

2013 journal articles and conference papers

Ahmed, A., P. Varakantham, Y. Adulyasak, and P. Jaillet. "Regret based Robust Solutions for Uncertain Markov Decision Processes". Advances in Neural Information Processing Systems 26, NIPS 2013, 881-889.

Ashlagi, I., P. Jaillet, and V. Manshadi. "Kidney Exchange in Dynamic Sparse Heterogenous Pools". arXiv:1301.3509v2, April 2013.

Asif, M.T., N. Mitrovic, L. Garg, J. Dauwels, and P. Jaillet. "Low-Dimensional Models for Missing Data Imputation in Road Networks". IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013, 3527-3531.

Asif, M.T., K. Srinivasan, J. Dauwels, and P. Jaillet. "Data Compression Techniques for Urban Traffic Data". IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems, CIVTS 2013, 44--49.

Chen, J., N. Cao, K.H. Low, R. Ouyang, K.Y. Tan, and P. Jaillet. "Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations". 29th Conference on Uncertainty in Artificial Intelligence, UAI 2013, 152-161.

Gopi, G., J. Dauwels, M.T. Asif, S. Ashwin, N. Mitrovic, U. Rasheed, and P. Jaillet. "Bayesian Support Vector Regression for Traffic Speed Prediction with Error Bars". 16th International IEEE Annual Conference on Intelligent Transportation Systems, ITSC 2013, 136-141.

Jaillet, P., J. Soto, and R. Zenklusen. "Advances on Matroid Secretary Problems: Free Order Model and Laminar Case". 16th Conference on Integer Programming and Combinatorial Optimization, IPCO 2013, 254-265.

Mitrovic, N., M.T. Asif, U. Rasheed, J. Dauwels, and P. Jaillet. "CUR Decomposition for Compression and Compressed Sensing of Large-Scale Traffic Data". 16th International IEEE Annual Conference on Intelligent Transportation Systems, ITSC 2013, 1475-1480.

Oran, A. and P. Jaillet. "An HMM-based Map-Matching Method with Cumulative Proximity-Weight Formulations". International Conference on Connected Vehicles and Expo, ICCVE 2013, 480--485.

Oran, A. and P. Jaillet. "A Precise Proximity-Weight Formulation for Map Matching Algorithms". 10th Workshop on Positioning Navigation and Communication, WPNC 2013, 1--6.

2012 journal articles and conference papers

Asif, M.T., J. Dauwels, C.Y. Goh, A. Oran, E. Fathi, M. Xu, M. M. Dhanya, N. Mitrovic, and P. Jaillet. "Unsupervised learning based performance analysis of n-support vector regression for speed prediction of a large road network". 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012, 983--988.

Chen, J., K.H. Low, K.Y. Tan, A. Oran, P. Jaillet, J. Dolan, and G. Sukhatme. "Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena". 28th Conference on Uncertainty in Artificial Intelligence, UAI 2012, 163-173.

Goh, C.Y., J. Dauwels, N. Mitrovic, M. T. Asif, A. Oran, and P. Jaillet. "Online map-matching based on Hidden Markov model for real-time traffic sensing applications". 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012, 776--781.

Jaillet, P. and X. Lu. "Near-Optimal Online Algorithms for Dynamic Resource Allocations". arXiv:1208.2596v1, August 2012.

Mastin, A. and P. Jaillet. "Loss Bounds for Uncertain Transition Probabilities in Markov Decision". IEEE 51st Annual Conference on Decision and Control, CDC 2012, 6708-6715.

Oran, A., K.C. Tan, B.H. Ooi, M. Sim, and P. Jaillet. "Location and Routing Models for Emergency Response Plans with Priorities". 7th Security Conference, Future Security 2012, 129--140.

Yu, J., K.H. Low, A. Oran, and P. Jaillet. "Hierarchical Bayesian Nonparametric Approach to Modeling and Learning the Wisdom of Crowds of Urban Traffic Route Planning Agents". IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, WI-IAT 2012, 478--485.

selected older publications

Jaillet, P. and X. Lu. "Online Traveling Salesman Problems with Service Flexibility". Networks, 58, 137-146, 2011.

Jaillet, P. and X. Lu. "Online Resource Allocation Problems". MIT, 2011.

Tulabandhula, T., C. Rudin, and P. Jaillet. "The Machine Learning and Traveling Repairman Problem". 2nd International Conference on Algorithmic Decision Theory, ADT 2011, 262-276. (also available at DSpace@MIT)

Tulabandhula, T., C. Rudin, and P. Jaillet. "Machine Learning and the Traveling Repairman". MIT, 2011. (also available at arXiv:1104.5061v1)

Jaillet, P. and M. Wagner. "Almost Sure Asymptotic Optimality for Online Routing and Machine Scheduling Problems". Networks, 55, 2-12, 2010.

Jaillet, P. and M. Wagner. "Generalized Online Routing: New Competitive Ratios, Resource Augmentation and Asymptotic Analyses". Operations Research, 56, 745-757, 2008. (e-companion appendix).

Figliozzi, M., H. Mahmassani and P. Jaillet "Pricing in Dynamic Vehicle Routing Problems". Transportation Science, 41, 302-318, 2007.

Jaillet, P. and M. Wagner. "Online Routing Problems: Value of Advanced Information as Improved Competitive Ratios". Transportation Science, 40, 200-210, 2006.

Jaillet, P., E. Ronn and S. Tompaidis. "Valuation of Commodity-Based Swing Options". Management Science, 50, 909-921, 2004.

J. Yang, P. Jaillet and H. Mahmassani. "Real-Time Multi-Vehicle Truckload Pick-Up and Delivery Problem". Transportation Science, 38, 135-148, 2004.

Jaillet, P., J. Bard, L. Huang and M. Dror. "Delivery Cost Approximations for Inventory Routing Problems in a Rolling Horizon Framework". Transportation Science, 36, 292-300, 2002.

Jaillet, P. and M. Stafford. "Online Searching". Operations Research, 49, 501-516, 2001.

Bard, J., L. Huang, M. Dror and P. Jaillet. "A Branch and Cut Algorithm for the VRP\ with Satellite Facilities". IIE Transactions on Operations Engineering , 30, 821-834, 1998.

Bard, J., L. Huang, P. Jaillet and M. Dror. "A Decomposition Approach to the Inventory Routing Problem with Satellite Facilities". Transportation Science, 32, 189-203, 1998.

Jaillet, P., G. Song and G. Yu. "Airline Network Design and Hub Location Problems". Location Science, 4, 195-211, 1996.

Jaillet, P. "On Properties of Geometric Random Problems in the Plane". Annals of Operations Research, 61, 1-20, 1995.

Goldschmidt, O., P. Jaillet and R. Lasota. "On Reliability of Graphs with Node Failures". Networks, 24, 251-259, 1994.

Jaillet, P. "Rate of Convergence for the Euclidean Minimum Spanning Tree Limit Law". Operations Research Letters, 14, 73-78, 1993.

Jaillet, P. "Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant". Annals of Applied Probability, 3, 582-592, 1993.

Jaillet, P. "Analysis of Probabilistic Combinatorial Optimization Problems in Euclidean Spaces". Mathematics of Operations Research, 18, 51--71, 1993.

Jaillet, P. "Shortest Path Problems With Nodes Failures". Networks, 22, 589--605, 1992.

Jaillet, P. "Rates of Convergence for Quasi-Additive Smooth Euclidean Functionals and Application to Combinatorial Optimization Problems". Mathematics of Operations Research, 17, 965--980, 1992.

Jaillet, P., D. Lamberton and B. Lapeyre. "Variational Inequalities and the Pricing of American Options". Acta Applicandae Mathematica, 21, 263--289, 1990.

Bertsimas, D., P. Jaillet and A. Odoni. "A Priori Optimization". Operations Research, 38, 1019--1033, 1990.

Jaillet, P. "A Priori Solution of a Traveling Salesman Problem in Which a Random Subset of the Customers are Visited". Operations Research, 36, 929--936, 1988.

some technical notes/reports

Jaillet, P. and M. Wagner. "A Note on "News from the Online Traveling Repairman" by Krumke et al.". Short note. (July 2004).

Jaillet, P., E. Ronn and S. Tompaidis. "On the Existence of a Unique Optimal Threshold Value for the Early Exercise of Call Options". Technical note. (July 2003).

phd thesis

Jaillet, P. "Probabilistic Traveling Salesman Problems". PhD thesis, MIT (1985). [warning, a scanned pdf file, size about 14.5MB]