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ORCIDPatrick Jaillet
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- affiliation: MIT, USA
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2020 – today
- 2023
[i72]Moïse Blanchard, Steve Hanneke, Patrick Jaillet:
Contextual Bandits and Optimistically Universal Learning. CoRR abs/2301.00241 (2023)- [i71]Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni:
Multi-channel Autobidding with Budget and ROI Constraints. CoRR abs/2302.01523 (2023) - [i70]Moïse Blanchard, Junhui Zhang, Patrick Jaillet:
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal. CoRR abs/2302.04963 (2023) - [i69]Gauthier Guinet, Saurabh Amin, Patrick Jaillet:
Effective Dimension in Bandit Problems under Censorship. CoRR abs/2302.06916 (2023) - [i68]Moïse Blanchard, Steve Hanneke, Patrick Jaillet:
Non-stationary Contextual Bandits and Universal Learning. CoRR abs/2302.07186 (2023) - 2022
- [j61]Supriyo Ghosh, Patrick Jaillet:
An iterative security game for computing robust and adaptive network flows. Comput. Oper. Res. 138: 105558 (2022) - [j60]Patrick Jaillet
, Gar Goei Loke, Melvyn Sim:
Strategic Workforce Planning Under Uncertainty. Oper. Res. 70(2): 1042-1065 (2022) - [j59]Mathieu Dahan, Saurabh Amin, Patrick Jaillet:
Probability Distributions on Partially Ordered Sets and Network Interdiction Games. Math. Oper. Res. 47(1): 458-484 (2022) - [c77]Sohil Shah, Saurabh Amin, Patrick Jaillet:
Optimal Information Provision for Strategic Hybrid Workers. CDC 2022: 3807-3814 - [c76]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. NeurIPS 2022 - [c75]Gauthier Guinet, Saurabh Amin, Patrick Jaillet:
Effective Dimension in Bandit Problems under Censorship. NeurIPS 2022 - [c74]Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet:
Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning. NeurIPS 2022 - [c73]Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet:
On provably robust meta-Bayesian optimization. UAI 2022: 475-485 - [i67]Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet:
Rectified Max-Value Entropy Search for Bayesian Optimization. CoRR abs/2202.13597 (2022) - [i66]Moïse Blanchard, Patrick Jaillet:
Universal Regression with Adversarial Responses. CoRR abs/2203.05067 (2022) - [i65]Sohil Shah, Saurabh Amin, Patrick Jaillet:
Optimal Information Provision for Strategic Hybrid Workers. CoRR abs/2205.02732 (2022) - [i64]Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Neural Bandit. CoRR abs/2205.14309 (2022) - [i63]Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet:
On Provably Robust Meta-Bayesian Optimization. CoRR abs/2206.06872 (2022) - [i62]The Viet Bui, Tien Mai, Patrick Jaillet:
Weighted Maximum Entropy Inverse Reinforcement Learning. CoRR abs/2208.09611 (2022) - [i61]Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni:
Fairness in the Autobidding World with Machine-learned Advice. CoRR abs/2209.04748 (2022) - [i60]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. CoRR abs/2210.06850 (2022) - [i59]Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet:
Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem. CoRR abs/2211.11063 (2022) - [i58]Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet:
Additional Results and Extensions for the paper "Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem". CoRR abs/2211.11065 (2022) - 2021
- [j58]Florian Delavernhe, Patrick Jaillet, André Rossi, Marc Sevaux:
Planning a multi-sensors search for a moving target considering traveling costs. Eur. J. Oper. Res. 292(2): 469-482 (2021) - [j57]Hossein Hashemi Doulabi, Patrick Jaillet, Gilles Pesant, Louis-Martin Rousseau:
Exploiting the Structure of Two-Stage Robust Optimization Models with Exponential Scenarios. INFORMS J. Comput. 33(1): 143-162 (2021) - [j56]Dawsen Hwang, Patrick Jaillet, Vahideh H. Manshadi:
Online Resource Allocation Under Partially Predictable Demand. Oper. Res. 69(3): 895-915 (2021) - [j55]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. J. Artif. Intell. Res. 70: 119-167 (2021) - [j54]Maaike Hoogeboom, Yossiri Adulyasak, Wout Dullaert, Patrick Jaillet:
The Robust Vehicle Routing Problem with Time Window Assignments. Transp. Sci. 55(2): 395-413 (2021) - [c72]Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet:
An Information-Theoretic Framework for Unifying Active Learning Problems. AAAI 2021: 9126-9134 - [c71]Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet:
Top-k Ranking Bayesian Optimization. AAAI 2021: 9135-9143 - [c70]Thanh Chi Lam, Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet:
Model Fusion for Personalized Learning. ICML 2021: 5948-5958 - [c69]Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Value-at-Risk Optimization with Gaussian Processes. ICML 2021: 8063-8072 - [c68]Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet:
Collaborative Bayesian Optimization with Fair Regret. ICML 2021: 9691-9701 - [c67]Haibin Yu, Dapeng Liu, Bryan Kian Hsiang Low, Patrick Jaillet:
Convolutional Normalizing Flows for Deep Gaussian Processes. IJCNN 2021: 1-6 - [c66]Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Optimizing Conditional Value-At-Risk of Black-Box Functions. NeurIPS 2021: 4170-4180 - [c65]Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Differentially Private Federated Bayesian Optimization with Distributed Exploration. NeurIPS 2021: 9125-9139 - [c64]Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet:
Learning to learn with Gaussian processes. UAI 2021: 1466-1475 - [c63]Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet:
Trusted-maximizers entropy search for efficient Bayesian optimization. UAI 2021: 1486-1495 - [i57]Saurabh Amin, Patrick Jaillet, Manxi Wu:
Efficient Carpooling and Toll Pricing for Autonomous Transportation. CoRR abs/2102.09132 (2021) - [i56]Haibin Yu, Dapeng Liu, Bryan Kian Hsiang Low, Patrick Jaillet:
Convolutional Normalizing Flows for Deep Gaussian Processes. CoRR abs/2104.08472 (2021) - [i55]Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Value-at-Risk Optimization with Gaussian Processes. CoRR abs/2105.06126 (2021) - [i54]Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab S. Mirrokni:
Bidding and Pricing in Budget and ROI Constrained Markets. CoRR abs/2107.07725 (2021) - [i53]Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet:
Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization. CoRR abs/2107.14465 (2021) - [i52]Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Differentially Private Federated Bayesian Optimization with Distributed Exploration. CoRR abs/2110.14153 (2021) - [i51]Tien Mai, Patrick Jaillet:
Robust Entropy-regularized Markov Decision Processes. CoRR abs/2112.15364 (2021) - 2020
- [j53]Julia Gaudio, Patrick Jaillet:
An improved lower bound for the Traveling Salesman constant. Oper. Res. Lett. 48(1): 67-70 (2020) - [j52]Anatolii Prokhorchuk, Justin Dauwels, Patrick Jaillet:
Estimating Travel Time Distributions by Bayesian Network Inference. IEEE Trans. Intell. Transp. Syst. 21(5): 1867-1876 (2020) - [c62]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Competitive Ratios for Online Multi-capacity Ridesharing. AAMAS 2020: 771-779 - [c61]Konstantina Mellou, Luke Marshall, Krishna Chintalapudi, Patrick Jaillet, Ishai Menache:
Optimizing Onsite Food Services at Scale. SIGSPATIAL/GIS 2020: 618-629 - [c60]Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho:
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games. ICML 2020: 2291-2301 - [c59]Trong Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low, Patrick Jaillet:
Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion. ICML 2020: 4282-4292 - [c58]Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Bayesian Optimization via Thompson Sampling. NeurIPS 2020 - [c57]Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang:
No-regret Learning in Price Competitions under Consumer Reference Effects. NeurIPS 2020 - [c56]Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet:
Variational Bayesian Unlearning. NeurIPS 2020 - [i50]Zhongxiang Dai, Yizhou Chen, Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho:
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games. CoRR abs/2006.16679 (2020) - [i49]Tien Mai, Patrick Jaillet:
A Relation Analysis of Markov Decision Process Frameworks. CoRR abs/2008.07820 (2020) - [i48]Youssef M. Aboutaleb, Moshe E. Ben-Akiva, Patrick Jaillet:
Learning Structure in Nested Logit Models. CoRR abs/2008.08048 (2020) - [i47]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. CoRR abs/2009.06051 (2020) - [i46]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Competitive Ratios for Online Multi-capacity Ridesharing. CoRR abs/2009.07925 (2020) - [i45]Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet:
Federated Bayesian Optimization via Thompson Sampling. CoRR abs/2010.10154 (2020) - [i44]Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet:
Variational Bayesian Unlearning. CoRR abs/2010.12883 (2020) - [i43]Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang:
No-regret Learning in Price Competitions under Consumer Reference Effects. CoRR abs/2011.03653 (2020) - [i42]Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet:
Top-k Ranking Bayesian Optimization. CoRR abs/2012.10688 (2020) - [i41]Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet:
An Information-Theoretic Framework for Unifying Active Learning Problems. CoRR abs/2012.10695 (2020)
2010 – 2019
- 2019
- [j51]Dimitris Bertsimas, Patrick Jaillet, Nikita Korolko:
The K-server problem via a modern optimization lens. Eur. J. Oper. Res. 276(1): 65-78 (2019) - [j50]Dimitris Bertsimas, Patrick Jaillet, Sébastien Martin:
Online Vehicle Routing: The Edge of Optimization in Large-Scale Applications. Oper. Res. 67(1): 143-162 (2019) - [j49]Dimitris Bertsimas, Arthur Delarue, Patrick Jaillet, Sébastien Martin:
Travel Time Estimation in the Age of Big Data. Oper. Res. 67(2): 498-515 (2019) - [j48]Itai Ashlagi, Maximilien Burq, Patrick Jaillet, Vahideh H. Manshadi:
On Matching and Thickness in Heterogeneous Dynamic Markets. Oper. Res. 67(4): 927-949 (2019) - [j47]Julia Gaudio, Saurabh Amin, Patrick Jaillet:
Exponential convergence rates for stochastically ordered Markov processes under perturbation. Syst. Control. Lett. 133 (2019) - [c55]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
ZAC: A Zone Path Construction Approach for Effective Real-Time Ridesharing. ICAPS 2019: 528-538 - [c54]Itai Ashlagi, Maximilien Burq, Chinmoy Dutta, Patrick Jaillet, Amin Saberi, Chris Sholley:
Edge Weighted Online Windowed Matching. EC 2019: 729-742 - [c53]Jinhong K. Guo, Alexander Karlovitz, Patrick Jaillet, Martin O. Hofmann:
The Price of Anarchy: Centralized versus Distributed Resource Allocation Trade-offs. ICAART (1) 2019: 146-153 - [c52]Zhongxiang Dai, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet:
Bayesian Optimization Meets Bayesian Optimal Stopping. ICML 2019: 1496-1506 - [c51]Supriyo Ghosh, Jing Yu Koh, Patrick Jaillet:
Improving Customer Satisfaction in Bike Sharing Systems through Dynamic Repositioning. IJCAI 2019: 5864-5870 - [c50]Haibin Yu, Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet:
Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression. IJCNN 2019: 1-8 - [c49]Haibin Yu, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Zhongxiang Dai:
Implicit Posterior Variational Inference for Deep Gaussian Processes. NeurIPS 2019: 14475-14486 - [i40]Dimitris Bertsimas, Arthur Delarue, Patrick Jaillet, Sébastien Martin:
The Price of Interpretability. CoRR abs/1907.03419 (2019) - [i39]Dimitris Bertsimas, Arthur Delarue, Patrick Jaillet, Sébastien Martin:
Optimal Explanations of Linear Models. CoRR abs/1907.04669 (2019) - [i38]Haibin Yu, Yizhou Chen, Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet:
Implicit Posterior Variational Inference for Deep Gaussian Processes. CoRR abs/1910.11998 (2019) - [i37]Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang:
Incentive-aware Contextual Pricing with Non-parametric Market Noise. CoRR abs/1911.03508 (2019) - [i36]Tien Mai, Kennard Chan, Patrick Jaillet:
Generalized Maximum Causal Entropy for Inverse Reinforcement Learning. CoRR abs/1911.06928 (2019) - [i35]Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet:
Inverse Reinforcement Learning with Missing Data. CoRR abs/1911.06930 (2019) - [i34]Supriyo Ghosh, Patrick Jaillet:
An Iterative Security Game for Computing Robust and Adaptive Network Flows. CoRR abs/1911.10505 (2019) - [i33]Tien Mai, Patrick Jaillet:
Robust Multi-product Pricing under General Extreme Value Models. CoRR abs/1912.09552 (2019) - 2018
- [j46]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Online spatio-temporal matching in stochastic and dynamic domains. Artif. Intell. 261: 71-112 (2018) - [j45]Virgile Galle, Cynthia Barnhart, Patrick Jaillet:
A new binary formulation of the restricted Container Relocation Problem based on a binary encoding of configurations. Eur. J. Oper. Res. 267(2): 467-477 (2018) - [j44]Virgile Galle, Cynthia Barnhart, Patrick Jaillet:
Yard Crane Scheduling for container storage, retrieval, and relocation. Eur. J. Oper. Res. 271(1): 288-316 (2018) - [j43]Arthur Flajolet, Sebastien Blandin, Patrick Jaillet:
Robust Adaptive Routing Under Uncertainty. Oper. Res. 66(1): 210-229 (2018) - [j42]Dawsen Hwang, Patrick Jaillet:
Online scheduling with multi-state machines. Networks 71(3): 209-251 (2018) - [j41]Ali Oran, Patrick Jaillet:
An Integrated Likelihood Formulation for Characterizing the Proximity of Position Measurements to Road Segments. IEEE Trans. Intell. Transp. Syst. 19(6): 1839-1854 (2018) - [j40]Virgile Galle, Vahideh H. Manshadi, S. Borjian Boroujeni, Cynthia Barnhart, Patrick Jaillet:
The Stochastic Container Relocation Problem. Transp. Sci. 52(5): 1035-1058 (2018) - [c48]Manxi Wu, Li Jin, Saurabh Amin, Patrick Jaillet:
Signaling Game-based Misbehavior Inspection in V2I-enabled Highway Operations. CDC 2018: 2728-2734 - [i32]Itai Ashlagi, Maximilien Burq, Patrick Jaillet, Amin Saberi:
Maximizing Efficiency in Dynamic Matching Markets. CoRR abs/1803.01285 (2018) - [i31]Manxi Wu, Li Jin, Saurabh Amin, Patrick Jaillet:
Signaling Game-based Misbehavior Inspection in V2I-enabled Highway Operations. CoRR abs/1803.08415 (2018) - [i30]Itai Ashlagi, Maximilien Burq, Chinmoy Dutta, Patrick Jaillet, Amin Saberi, Chris Sholley:
Maximum Weight Online Matching with Deadlines. CoRR abs/1808.03526 (2018) - [i29]Dawsen Hwang, Patrick Jaillet, Vahideh H. Manshadi:
Online Resource Allocation under Partially Predictable Demand. CoRR abs/1810.00447 (2018) - [i28]Mathieu Dahan, Saurabh Amin, Patrick Jaillet:
Probability Distributions on Partially Ordered Sets and Network Security Games. CoRR abs/1811.08516 (2018) - 2017
- [j39]Elisabeth Zehendner, Dominique Feillet, Patrick Jaillet:
An algorithm with performance guarantee for the Online Container Relocation Problem. Eur. J. Oper. Res. 259(1): 48-62 (2017) - [j38]Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet:
Dynamic Repositioning to Reduce Lost Demand in Bike Sharing Systems. J. Artif. Intell. Res. 58: 387-430 (2017) - [j37]Asrar Ahmed, Pradeep Varakantham, Meghna Lowalekar, Yossiri Adulyasak, Patrick Jaillet:
Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Processes (MDPs). J. Artif. Intell. Res. 59: 229-264 (2017) - [c47]Meghna Lowalekar, Pradeep Varakantham, Supriyo Ghosh, Sanjay Dominik Jena, Patrick Jaillet:
Online Repositioning in Bike Sharing Systems. ICAPS 2017: 200-208 - [c46]Michel X. Goemans, Swati Gupta, Patrick Jaillet:
Discrete Newton's Algorithm for Parametric Submodular Function Minimization. IPCO 2017: 212-227 - [c45]Anatolii Prokhorchuk, Vishnu Prasad Payyada, Justin Dauwels, Patrick Jaillet:
Estimating travel time distributions using copula graphical lasso. ITSC 2017: 1-6 - [c44]Jian Wen, Jinhua Zhao, Patrick Jaillet:
Rebalancing shared mobility-on-demand systems: A reinforcement learning approach. ITSC 2017: 220-225 - [c43]Arthur Flajolet, Patrick Jaillet:
Real-Time Bidding with Side Information. NIPS 2017: 5162-5172 - [c42]Ofer Dekel, Arthur Flajolet, Nika Haghtalab, Patrick Jaillet:
Online Learning with a Hint. NIPS 2017: 5299-5308 - [c41]Kelvin Lee, Anatolii Prokhorchuk, Justin Dauwels, Patrick Jaillet:
Estimation of travel time from taxi GPS data. SSCI 2017: 1-6 - [i27]Virgile Galle, Setareh Borjian Boroujeni, Vahideh H. Manshadi, Cynthia Barnhart, Patrick Jaillet:
The Stochastic Container Relocation Problem. CoRR abs/1703.04769 (2017) - [i26]Haibin Yu, Trong Nghia Hoang, Kian Hsiang Low, Patrick Jaillet:
Stochastic Variational Inference for Fully Bayesian Sparse Gaussian Process Regression Models. CoRR abs/1711.00221 (2017) - 2016
- [j36]Antoine Legrain, Patrick Jaillet:
A stochastic algorithm for online bipartite resource allocation problems. Comput. Oper. Res. 75: 28-37 (2016) - [j35]Patrick Jaillet, Jin Qi, Melvyn Sim:
Routing Optimization Under Uncertainty. Oper. Res. 64(1): 186-200 (2016) - [j34]Virgile Galle, S. Borjian Boroujeni, Vahideh H. Manshadi, Cynthia Barnhart, Patrick Jaillet:
An average-case asymptotic analysis of the Container Relocation Problem. Oper. Res. Lett. 44(6): 723-728 (2016) - [j33]Thibaut Vidal, Patrick Jaillet, Nelson Maculan:
A Decomposition Algorithm for Nested Resource Allocation Problems. SIAM J. Optim. 26(2): 1322-1340 (2016) - [j32]Muhammad Tayyab Asif, Nikola Mitrovic, Justin Dauwels, Patrick Jaillet:
Matrix and Tensor Based Methods for Missing Data Estimation in Large Traffic Networks. IEEE Trans. Intell. Transp. Syst. 17(7): 1816-1825 (2016) - [j31]Nikola Mitrovic, Aditya Narayanan, Muhammad Tayyab Asif, Ansar Rauf, Justin Dauwels, Patrick Jaillet:
On Centralized and Decentralized Architectures for Traffic Applications. IEEE Trans. Intell. Transp. Syst. 17(7): 1988-1997 (2016) - [j30]Yossiri Adulyasak, Patrick Jaillet:
Models and Algorithms for Stochastic and Robust Vehicle Routing with Deadlines. Transp. Sci. 50(2): 608-626 (2016) - [c40]Chun Kai Ling, Kian Hsiang Low, Patrick Jaillet:
Gaussian Process Planning with Lipschitz Continuous Reward Functions: Towards Unifying Bayesian Optimization, Active Learning, and Beyond. AAAI 2016: 1860-1866 - [c39]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Online Spatio-Temporal Matching in Stochastic and Dynamic Domains. AAAI 2016: 3271-3277 - [c38]Itai Ashlagi, Maximilien Burq, Patrick Jaillet, Vahideh H. Manshadi:
On Matching and Thickness in Heterogeneous Dynamic Markets. EC 2016: 765 - [i25]Swati Gupta, Michel X. Goemans, Patrick Jaillet:
Solving Combinatorial Games using Products, Projections and Lexicographically Optimal Bases. CoRR abs/1603.00522 (2016) - [i24]Itai Ashlagi, Maximilien Burq, Patrick Jaillet, Vahideh H. Manshadi:
On Matching and Thickness in Heterogeneous Dynamic Markets. CoRR abs/1606.03626 (2016) - [i23]