Phebe Vayanos - RankMe

65 papers A* 9A 6B 2C 3Misc 1Journal 28Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Robust Optimization with Decision-Dependent Information Discovery. Manag. Sci. Phebe Vayanos, Angelos Georghiou, Han Yu
2025	J	`jnl`	Making a Case for Research Collaboration Between Artificial Intelligence and Operations Research Experts. CoRR Radhika Kulkarni, Gianluca Brero, Yu Ding, Swati Gupta, Sven Koenig, Ramayya Krishnan, Thiago Serra, Phebe Vayanos, Segev Wasserkrug, Holly Wiberg
2025	A	`conf`	Mixed-Feature Logistic Regression Robust to Distribution Shifts. AISTATS Qingshi Sun, Nathan Justin, Andrés Gómez, Phebe Vayanos
2025	J	`jnl`	Mixed-Integer Optimization for Responsible Machine Learning. CoRR Nathan Justin, Qingshi Sun, Andrés Gómez, Phebe Vayanos
2025	J	`jnl`	Mixed-feature Logistic Regression Robust to Distribution Shifts. CoRR Qingshi Sun, Nathan Justin, Andres Gomez, Phebe Vayanos
2025	J	`jnl`	Strong Optimal Classification Trees. Oper. Res. Sina Aghaei, Andrés Gómez, Phebe Vayanos
2025	J	`jnl`	Toward AI Matching Policies in Homeless Services: A Qualitative Study with Policymakers. CoRR Caroline M. Johnston, Olga Koumoundouros, Angel Hsing-Chi Hwang, Laura Onasch-Vera, Eric Rice, Phebe Vayanos
2024	A*	`conf`	Learning Fair Policies for Multi-Stage Selection Problems from Observational Data. AAAI Zhuangzhuang Jia, Grani A. Hanasusanto, Phebe Vayanos, Weijun Xie
2023	—	`conf`	Deploying a Robust Active Preference Elicitation Algorithm on MTurk: Experiment Design, Interface, and Evaluation for COVID-19 Patient Prioritization. EAAMO Caroline M. Johnston, Patrick Vossler, Simon Blessenohl, Phebe Vayanos
2023	J	`jnl`	Deploying a Robust Active Preference Elicitation Algorithm: Experiment Design, Interface, and Evaluation for COVID-19 Patient Prioritization. CoRR Caroline M. Johnston, Patrick Vossler, Simon Blessenohl, Phebe Vayanos
2023	A*	`conf`	Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results. AAAI Nathanael Jo, Bill Tang, Kathryn Dullerud, Sina Aghaei, Eric Rice, Phebe Vayanos
2023	J	`jnl`	Learning Fair Policies for Multi-stage Selection Problems from Observational Data. CoRR Zhuangzhuang Jia, Grani A. Hanasusanto, Phebe Vayanos, Weijun Xie
2023	J	`jnl`	Learning Optimal Classification Trees Robust to Distribution Shifts. CoRR Nathan Justin, Sina Aghaei, Andrés Gómez, Phebe Vayanos
2023	C	`conf`	Learning Optimal Fair Decision Trees: Trade-offs Between Interpretability, Fairness, and Accuracy. AIES Nathanael Jo, Sina Aghaei, Jack Benson, Andrés Gómez, Phebe Vayanos
2023	J	`jnl`	Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment. CoRR Bill Tang, Çagil Koçyigit, Eric Rice, Phebe Vayanos
2023	J	`jnl`	ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription. CoRR Patrick Vossler, Sina Aghaei, Nathan Justin, Nathanael Jo, Andrés Gómez, Phebe Vayanos
2022	J	`jnl`	Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results. CoRR Nathanael Jo, Bill Tang, Kathryn Dullerud, Sina Aghaei, Eric Rice, Phebe Vayanos
2022	J	`jnl`	Learning Optimal Fair Classification Trees. CoRR Nathanael Jo, Sina Aghaei, Jack Benson, Andrés Gómez, Phebe Vayanos
2022	—	`conf`	Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery. FAccT Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice
2022	J	`jnl`	Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery. CoRR Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice
2022	J	`jnl`	ROC++: Robust Optimization in C++. INFORMS J. Comput. Phebe Vayanos, Qing Jin, George Elissaios
2021	A*	`conf`	Fair Influence Maximization: a Welfare Optimization Approach. AAAI Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe
2021	J	`jnl`	Learning Optimal Prescriptive Trees from Observational Data. CoRR Nathanael Jo, Sina Aghaei, Andrés Gómez, Phebe Vayanos
2021	J	`jnl`	Strong Optimal Classification Trees. CoRR Sina Aghaei, Andrés Gómez, Phebe Vayanos
2020	J	`jnl`	Active Preference Elicitation via Adjustable Robust Optimization. CoRR Phebe Vayanos, Duncan C. McElfresh, Yingxiao Ye, John Paul Dickerson, Eric Rice
2020	—	`conf`	Exploiting Bounded Rationality in Risk-Based Cyber Camouflage Games. GameSec Omkar Thakoor, Shahin Jabbari, Palvi Aggarwal, Cleotilde Gonzalez, Milind Tambe, Phebe Vayanos
2020	J	`jnl`	Exploring Algorithmic Fairness in Robust Graph Covering Problems. CoRR Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe
2020	J	`jnl`	Fair Influence Maximization: A Welfare Optimization Approach. CoRR Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Eric Rice, Milind Tambe
2020	—	`ch.`	Game Theoretic Cyber Deception to Foil Adversarial Network Reconnaissance. Adaptive Autonomous Secure Cyber Systems Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Phebe Vayanos
2020	J	`jnl`	Learning Optimal Classification Trees: Strong Max-Flow Formulations. CoRR Sina Aghaei, Andrés Gómez, Phebe Vayanos
2019	—	`conf`	Cyber Camouflage Games for Strategic Deception. GameSec Omkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld, Fei Fang
2019	A*	`conf`	Exploring Algorithmic Fairness in Robust Graph Covering Problems. NeurIPS Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe
2019	A	`conf`	General-Sum Cyber Deception Games under Partial Attacker Valuation Information. AAMAS Omkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld
2019	A*	`conf`	Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making. AAAI Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos
2019	J	`jnl`	Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making. CoRR Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos
2019	—	`conf`	Learning to Signal in the Goldilocks Zone: Improving Adversary Compliance in Security Games. ECML/PKDD (1) Sarah Cooney, Kai Wang, Elizabeth Bondi, Thanh Hong Nguyen, Phebe Vayanos, Hailey Winetrobe, Edward A. Cranford, Cleotilde Gonzalez, Christian Lebiere, Milind Tambe
2019	J	`jnl`	Robust Multiclass Queuing Theory for Wait Time Estimation in Resource Allocation Systems. Manag. Sci. Chaithanya Bandi, Nikolaos Trichakis, Phebe Vayanos
2019	A	`conf`	Robust Peer-Monitoring on Graphs with an Application to Suicide Prevention in Social Networks. AAMAS Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Milind Tambe
2019	J	`jnl`	Social Network Based Substance Abuse Prevention via Network Modification (A Preliminary Study). CoRR Aida Rahmattalabi, Anamika Barman-Adhikari, Phebe Vayanos, Milind Tambe, Eric Rice, Robin Baker
2019	J	`jnl`	Street-Level Realities of Data Practices in Homeless Services Provision. Proc. ACM Hum. Comput. Interact. Naveena Karusala, Jennifer Wilson, Phebe Vayanos, Eric Rice
2019	A	`conf`	Warning Time: Optimizing Strategic Signaling for Security Against Boundedly Rational Adversaries. AAMAS Sarah Cooney, Phebe Vayanos, Thanh Hong Nguyen, Cleotilde Gonzalez, Christian Lebiere, Edward A. Cranford, Milind Tambe
2018	—	`conf`	A Robust Optimization Approach to Designing Near-Optimal Strategies for Constant-Sum Monitoring Games. GameSec Aida Rahmattalabi, Phebe Vayanos, Milind Tambe
2018	A	`conf`	Deceiving Cyber Adversaries: A Game Theoretic Approach. AAMAS Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Long Tran-Thanh, Phebe Vayanos, Yevgeniy Vorobeychik
2018	B	`conf`	Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources. CPAIOR Mohammad Javad Azizi, Phebe Vayanos, Bryan Wilder, Eric Rice, Milind Tambe
2018	A	`conf`	Equilibrium Refinement in Security Games with Arbitrary Scheduling Constraints. AAMAS Kai Wang, Qingyu Guo, Phebe Vayanos, Milind Tambe, Bo An
2018	—	`conf`	From Empirical Analysis to Public Policy: Evaluating Housing Systems for Homeless Youth. ECML/PKDD (3) Hau Chan, Eric Rice, Phebe Vayanos, Milind Tambe, Matthew Morton
2018	—	`conf`	Imbalanced Collusive Security Games. GameSec Han-Ching Ou, Milind Tambe, Bistra Dilkina, Phebe Vayanos
2018	A*	`conf`	Influence Maximization for Social Network Based Substance Abuse Prevention. AAAI Aida Rahmattalabi, Anamika Barman-Adhikari, Phebe Vayanos, Milind Tambe, Eric Rice, Robin Baker
2018	B	`conf`	Learning about Cyber Deception through Simulations: Predictions of Human Decision Making with Deceptive Signals in Stackelberg Security Games. CogSci Edward A. Cranford, Christian Lebiere, Cleotilde Gonzalez, Sarah Cooney, Phebe Vayanos, Milind Tambe
2018	C	`conf`	Partially Generative Neural Networks for Gang Crime Classification with Partial Information. AIES Sungyong Seo, Hau Chan, P. Jeffrey Brantingham, Jorja Leap, Phebe Vayanos, Milind Tambe, Yan Liu
2018	A*	`conf`	Strategic Coordination of Human Patrollers and Mobile Sensors With Signaling for Security Games. AAAI Haifeng Xu, Kai Wang, Phebe Vayanos, Milind Tambe
2018	A*	`conf`	The Price of Usability: Designing Operationalizable Strategies for Security Games. IJCAI Sara Marie McCarthy, Corine M. Laan, Kai Wang, Phebe Vayanos, Arunesh Sinha, Milind Tambe
2018	C	`conf`	Utilizing Housing Resources for Homeless Youth Through the Lens of Multiple Multi-Dimensional Knapsacks. AIES Hau Chan, Long Tran-Thanh, Bryan Wilder, Eric Rice, Phebe Vayanos, Milind Tambe
2017	—	`conf`	Evidence From the Past: AI Decision Aids to Improve Housing Systems for Homeless Youth. AAAI Fall Symposia Hau Chan, Eric Rice, Phebe Vayanos, Milind Tambe, Matthew Morton
2017	—	`conf`	Explanation Systems for Influence Maximization Algorithms. SocInf@IJCAI Amulya Yadav, Aida Rahmattalabi, Ece Kamar, Phebe Vayanos, Milind Tambe, Venil Loyd Noronha
2017	A*	`conf`	Staying Ahead of the Game: Adaptive Robust Optimization for Dynamic Allocation of Threat Screening Resources. IJCAI Sara Marie McCarthy, Phebe Vayanos, Milind Tambe
2013	—	`—`	Decision rule approximations for dynamic optimization under uncertainty. Phebe Vayanos
2012	J	`jnl`	A constraint sampling approach for multi-stage robust optimization. Autom. Phebe Vayanos, Daniel Kuhn, Berç Rustem
2011	—	`conf`	Decision rules for information discovery in multi-stage stochastic programming. CDC/ECC Phebe Vayanos, Daniel Kuhn, Berç Rustem
2010	J	`jnl`	Characterisation of Signal Modality: Exploiting Signal Nonlinearity in Machine Learning and Signal Processing. J. Signal Process. Syst. Beth Jelfs, Soroush Javidi, Phebe Vayanos, Danilo P. Mandic
2008	J	`jnl`	Online Detection of the Modality of Complex-Valued Real World Signals. Int. J. Neural Syst. Danilo P. Mandic, Phebe Vayanos, Mo Chen, Su Lee Goh
2008	Misc	`conf`	Online tracking of the degree of nonlinearity within complex signals. ICASSP Danilo P. Mandic, Phebe Vayanos, Soroush Javidi, Beth Jelfs, Kazuyuki Aihara
2007	—	`conf`	Collaborative Adaptive Learning using Hybrid Filters. ICASSP (3) Danilo P. Mandic, Phebe Vayanos, Christos Boukis, Beth Jelfs, Su Lee Goh, Temujin Gautama, Tomasz M. Rutkowski
2007	—	`conf`	Exploiting Nonlinearity in Adaptive Signal Processing. NOLISP Phebe Vayanos, Mo Chen, Beth Jelfs, Danilo P. Mandic
2006	—	`conf`	An Online Method for Detecting Nonlinearity Within a Signal. KES (3) Beth Jelfs, Phebe Vayanos, Mo Chen, Su Lee Goh, Christos Boukis, Temujin Gautama, Tomasz M. Rutkowski, Tony Kuh, Danilo P. Mandic