Vasilis Syrgkanis

204 papers A* 57A 3B 2C 1Journal 124Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Estimation and Inference in Conditional Moment Models via the Discrepancy Principle. CoRR Jiyuan Tan, Vasilis Syrgkanis
2026	J	`jnl`	CausalReasoningBenchmark: A Real-World Benchmark for Disentangled Evaluation of Causal Identification and Estimation. CoRR Ayush Sawarni, Jiyuan Tan, Vasilis Syrgkanis
2026	J	`jnl`	Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration. Trans. Mach. Learn. Res. Dung Daniel T. Ngo, Keegan Harris, Anish Agarwal, Vasilis Syrgkanis, Zhiwei Steven Wu
2026	J	`jnl`	Post Reinforcement Learning Inference. Oper. Res. Vasilis Syrgkanis, Ruohan Zhan
2026	J	`jnl`	Prescriptive Scaling Reveals the Evolution of Language Model Capabilities. CoRR Hanlin Zhang, Jikai Jin, Vasilis Syrgkanis, Sham M. Kakade
2026	J	`jnl`	Statistical Inference and Learning for Shapley Additive Explanations (SHAP). CoRR Justin Whitehouse, Ayush Sawarni, Vasilis Syrgkanis
2025	A*	`conf`	A Meta-learner for Heterogeneous Effects in Difference-in-Differences. ICML Hui Lan, Haoge Chang, Eleanor Wiske Dillon, Vasilis Syrgkanis
2025	J	`jnl`	A Meta-learner for Heterogeneous Effects in Difference-in-Differences. CoRR Hui Lan, Haoge Chang, Eleanor Dillon, Vasilis Syrgkanis
2025	J	`jnl`	Detecting clinician implicit biases in diagnoses using proximal causal inference. CoRR Kara Liu, Russ Altman, Vasilis Syrgkanis
2025	J	`jnl`	Direct Preference Optimization with Unobserved Preference Heterogeneity: The Necessity of Ternary Preferences. CoRR Keertana Chidambaram, Karthik Vinary Seetharaman, Vasilis Syrgkanis
2025	J	`jnl`	Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning. CoRR Jikai Jin, Vasilis Syrgkanis, Sham M. Kakade, Hanlin Zhang
2025	J	`jnl`	Estimation of Treatment Effects in Extreme and Unobserved Data. CoRR Jiyuan Tan, Jose H. Blanchet, Vasilis Syrgkanis
2025	J	`jnl`	Inference on Optimal Policy Values and Other Irregular Functionals via Smoothing. CoRR Justin Whitehouse, Morgane Austern, Vasilis Syrgkanis
2025	J	`jnl`	It's Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation. CoRR Jikai Jin, Lester Mackey, Vasilis Syrgkanis
2025	J	`jnl`	Learning Treatment Representations for Downstream Instrumental Variable Regression. CoRR Shiangyi Lin, Hui Lan, Vasilis Syrgkanis
2025	A*	`conf`	Orthogonal Causal Calibration (Extended Abstract). COLT Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu
2025	J	`jnl`	Policy Learning with Abstention. CoRR Ayush Sawarni, Jikai Jin, Justin Whitehouse, Vasilis Syrgkanis
2025	J	`jnl`	Preference Learning with Response Time. CoRR Ayush Sawarni, Sahasrajit Sarmasarkar, Vasilis Syrgkanis
2025	J	`jnl`	Sharp Structure-Agnostic Lower Bounds for General Functional Estimation. CoRR Jikai Jin, Vasilis Syrgkanis
2025	A*	`conf`	Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation (Extended Abstract). COLT Jikai Jin, Vasilis Syrgkanis
2024	A*	`conf`	Adaptive Instrument Design for Indirect Experiments. ICLR Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
2024	J	`jnl`	Applied Causal Inference Powered by ML and AI. CoRR Victor Chernozhukov, Christian Hansen, Nathan Kallus, Martin Spindler, Vasilis Syrgkanis
2024	J	`jnl`	Automatic Doubly Robust Forests. CoRR Zhaomeng Chen, Junting Duan, Victor Chernozhukov, Vasilis Syrgkanis
2024	J	`jnl`	Causal Inference under Incentives: An Annotated Reading List. SIGecom Exch. Keegan Harris, Vasilis Syrgkanis
2024	A	`conf`	Causal Q-Aggregation for CATE Model Selection. AISTATS Hui Lan, Vasilis Syrgkanis
2024	A*	`conf`	Consistency of Neural Causal Partial Identification. NeurIPS Jiyuan Tan, Jose H. Blanchet, Vasilis Syrgkanis
2024	J	`jnl`	Consistency of Neural Causal Partial Identification. CoRR Jiyuan Tan, Jose H. Blanchet, Vasilis Syrgkanis
2024	J	`jnl`	Direct Preference Optimization With Unobserved Preference Heterogeneity. CoRR Keertana Chidambaram, Karthik Vinay Seetharaman, Vasilis Syrgkanis
2024	J	`jnl`	Dynamic Local Average Treatment Effects. CoRR Ravi B. Sojitra, Vasilis Syrgkanis
2024	A*	`conf`	Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation. ICLR Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis
2024	A*	`conf`	Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity. NeurIPS Jikai Jin, Vasilis Syrgkanis
2024	J	`jnl`	Orthogonal Causal Calibration. CoRR Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu
2024	J	`jnl`	Personalized Adaptation via In-Context Preference Learning. CoRR Allison Lau, Younwoo Choi, Vahid Balazadeh Meresht, Keertana Chidambaram, Vasilis Syrgkanis, Rahul G. Krishnan
2024	J	`jnl`	Predicting Long Term Sequential Policy Value Using Softer Surrogates. CoRR Hyunji Nam, Allen Nie, Ge Gao, Vasilis Syrgkanis, Emma Brunskill
2024	J	`jnl`	Regularized DeepIV with Model Selection. CoRR Zihao Li, Hui Lan, Vasilis Syrgkanis, Mengdi Wang, Masatoshi Uehara
2024	A*	`conf`	Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity. NeurIPS Vahid Balazadeh Meresht, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan, Vasilis Syrgkanis
2024	J	`jnl`	Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity. CoRR Vahid Balazadeh Meresht, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan, Vasilis Syrgkanis
2024	J	`jnl`	Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation. CoRR Jikai Jin, Vasilis Syrgkanis
2024	J	`jnl`	Switchback Price Experiments with Forward-Looking Demand. CoRR Yifan Wu, Ramesh Johari, Vasilis Syrgkanis, Gabriel Y. Weintraub
2024	J	`jnl`	Taking a Moment for Distributional Robustness. CoRR Jabari Hastings, Christopher Jung, Charlotte Peale, Vasilis Syrgkanis
2023	J	`jnl`	Adaptive Instrument Design for Indirect Experiments. CoRR Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
2023	J	`jnl`	Causal Q-Aggregation for CATE Model Selection. CoRR Hui Lan, Vasilis Syrgkanis
2023	J	`jnl`	Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration. CoRR Dung Daniel T. Ngo, Keegan Harris, Anish Agarwal, Vasilis Syrgkanis, Zhiwei Steven Wu
2023	J	`jnl`	Inference on Optimal Dynamic Policies via Softmax Approximation. CoRR Qizhao Chen, Morgane Austern, Vasilis Syrgkanis
2023	A*	`conf`	Inference on Strongly Identified Functionals of Weakly Identified Functions. COLT Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023	J	`jnl`	Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity. CoRR Jikai Jin, Vasilis Syrgkanis
2023	J	`jnl`	Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness. CoRR Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023	A*	`conf`	Minimax Instrumental Variable Regression and L COLT Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023	J	`jnl`	Post-Episodic Reinforcement Learning Inference. CoRR Vasilis Syrgkanis, Ruohan Zhan
2023	J	`jnl`	Source Condition Double Robust Inference on Functionals of Inverse Problems. CoRR Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2022	J	`jnl`	Automatic Debiased Machine Learning for Dynamic Treatment Effects. CoRR Rahul Singh, Vasilis Syrgkanis
2022	J	`jnl`	Bayesian Exploration: Incentivizing Exploration in Bayesian Games. Oper. Res. Yishay Mansour, Alex Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu
2022	A*	`conf`	Debiased Machine Learning without Sample-Splitting for Stable Estimators. NeurIPS Qizhao Chen, Vasilis Syrgkanis, Morgane Austern
2022	J	`jnl`	Debiased Machine Learning without Sample-Splitting for Stable Estimators. CoRR Qizhao Chen, Vasilis Syrgkanis, Morgane Austern
2022	J	`jnl`	Empirical Analysis of Model Selection for Heterogenous Causal Effect Estimation. CoRR Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis
2022	J	`jnl`	Learning in auctions: Regret is hard, envy is easy. Games Econ. Behav. Constantinos Daskalakis, Vasilis Syrgkanis
2022	J	`jnl`	Multi-Item Nontruthful Auctions Achieve Good Revenue. SIAM J. Comput. Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy
2022	—	`conf`	Non-parametric Inference Adaptive to Intrinsic Dimension. CLeaR Khashayar Khosravi, Greg Lewis, Vasilis Syrgkanis
2022	A*	`conf`	Partial Identification of Treatment Effects with Implicit Generative Models. NeurIPS Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G. Krishnan
2022	J	`jnl`	Partial Identification of Treatment Effects with Implicit Generative Models. CoRR Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G. Krishnan
2022	A*	`conf`	RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests. ICML Victor Chernozhukov, Whitney Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
2022	A*	`conf`	Robust Generalized Method of Moments: A Finite Sample Viewpoint. NeurIPS Dhruv Rohatgi, Vasilis Syrgkanis
2022	J	`jnl`	Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime. CoRR Anish Agarwal, Vasilis Syrgkanis
2022	—	`conf`	Towards efficient representation identification in supervised learning. CLeaR Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas
2022	J	`jnl`	Towards efficient representation identification in supervised learning. CoRR Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas
2021	J	`jnl`	Adversarial Estimation of Riesz Representers. CoRR Victor Chernozhukov, Whitney Newey, Rahul Singh, Vasilis Syrgkanis
2021	A*	`conf`	Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection. NeurIPS Morgane Austern, Vasilis Syrgkanis
2021	A*	`conf`	Bid Prediction in Repeated Auctions with Learning. WWW Gali Noti, Vasilis Syrgkanis
2021	A*	`conf`	Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber. KDD Vasilis Syrgkanis, Greg Lewis, Miruna Oprescu, Maggie Hei, Keith Battocchi, Eleanor Dillon, Jing Pan, Yifeng Wu, Paul Lo, Huigang Chen, Totte Harinen, Jeong-Yoon Lee
2021	J	`jnl`	Combinatorial Assortment Optimization. ACM Trans. Economics and Comput. Nicole Immorlica, Brendan Lucier, Jieming Mao, Vasilis Syrgkanis, Christos Tzamos
2021	J	`jnl`	DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions. CoRR Amit Sharma, Vasilis Syrgkanis, Cheng Zhang, Emre Kiciman
2021	A*	`conf`	Double/Debiased Machine Learning for Dynamic Treatment Effects. NeurIPS Greg Lewis, Vasilis Syrgkanis
2021	A*	`conf`	Dynamically Aggregating Diverse Information. EC Annie Liang, Xiaosheng Mu, Vasilis Syrgkanis
2021	A*	`conf`	Estimating the Long-Term Effects of Novel Treatments. NeurIPS Keith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu, Vasilis Syrgkanis
2021	J	`jnl`	Evidence-Based Policy Learning. CoRR Jann Spiess, Vasilis Syrgkanis
2021	A*	`conf`	Incentivizing Compliance with Algorithmic Instruments. ICML Dung Daniel T. Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu
2021	J	`jnl`	Incentivizing Compliance with Algorithmic Instruments. CoRR Dung Daniel T. Ngo, Logan Stapleton, Vasilis Syrgkanis, Zhiwei Steven Wu
2021	A*	`conf`	Knowledge Distillation as Semiparametric Inference. ICLR Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey
2021	J	`jnl`	Knowledge Distillation as Semiparametric Inference. CoRR Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey
2021	J	`jnl`	Omitted Variable Bias in Machine Learned Causal Models. CoRR Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis
2021	J	`jnl`	RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests. CoRR Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
2021	J	`jnl`	Robust Generalized Method of Moments: A Finite Sample Viewpoint. CoRR Dhruv Rohatgi, Vasilis Syrgkanis
2020	J	`jnl`	Asymptotics of the Empirical Bootstrap Method Beyond Asymptotic Normality. CoRR Morgane Austern, Vasilis Syrgkanis
2020	J	`jnl`	Bayesian Incentive-Compatible Bandit Exploration. Oper. Res. Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis
2020	J	`jnl`	Bid Prediction in Repeated Auctions with Learning. CoRR Gali Noti, Vasilis Syrgkanis
2020	J	`jnl`	Double/Debiased Machine Learning for Dynamic Treatment Effects. CoRR Greg Lewis, Vasilis Syrgkanis
2020	A*	`conf`	Estimation and Inference with Trees and Forests in High Dimensions. COLT Vasilis Syrgkanis, Manolis Zampetakis
2020	J	`jnl`	Estimation and Inference with Trees and Forests in High Dimensions. CoRR Vasilis Syrgkanis, Manolis Zampetakis
2020	A*	`conf`	Minimax Estimation of Conditional Moment Models. NeurIPS Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
2020	J	`jnl`	Minimax Estimation of Conditional Moment Models. CoRR Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
2020	J	`jnl`	Oracle-efficient Online Learning and Auction Design. J. ACM Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2020	A*	`conf`	Simple, Credible, and Approximately-Optimal Auctions. EC Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy
2020	J	`jnl`	Simple, Credible, and Approximately-Optimal Auctions. CoRR Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy
2020	A*	`conf`	Statistical Learning with a Nuisance Component (Extended Abstract). IJCAI Dylan J. Foster, Vasilis Syrgkanis
2019	J	`jnl`	Dynamically Aggregating Diverse Information. CoRR Annie Liang, Xiaosheng Mu, Vasilis Syrgkanis
2019	J	`jnl`	Information Asymmetries in Common-Value Auctions with Discrete Signals. Math. Oper. Res. Vasilis Syrgkanis, David Kempe, Éva Tardos
2019	A*	`conf`	Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing. NeurIPS Jonas Mueller, Vasilis Syrgkanis, Matt Taddy
2019	A*	`conf`	Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments. NeurIPS Vasilis Syrgkanis, Victor Lei, Miruna Oprescu, Maggie Hei, Keith Battocchi, Greg Lewis
2019	J	`jnl`	Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments. CoRR Vasilis Syrgkanis, Victor Lei, Miruna Oprescu, Maggie Hei, Keith Battocchi, Greg Lewis
2019	J	`jnl`	Non-Parametric Inference Adaptive to Intrinsic Dimension. CoRR Khashayar Khosravi, Greg Lewis, Vasilis Syrgkanis
2019	A*	`conf`	Orthogonal Random Forest for Causal Inference. ICML Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu
2019	J	`jnl`	Orthogonal Statistical Learning. CoRR Dylan J. Foster, Vasilis Syrgkanis
2019	A*	`conf`	Semi-Parametric Efficient Policy Learning with Continuous Actions. NeurIPS Victor Chernozhukov, Mert Demirer, Greg Lewis, Vasilis Syrgkanis
2019	J	`jnl`	Semi-Parametric Efficient Policy Learning with Continuous Actions. CoRR Mert Demirer, Vasilis Syrgkanis, Greg Lewis, Victor Chernozhukov
2019	A*	`conf`	Statistical Learning with a Nuisance Component. COLT Dylan J. Foster, Vasilis Syrgkanis
2018	A*	`conf`	Accurate Inference for Adaptive Linear Models. ICML Yash Deshpande, Lester W. Mackey, Vasilis Syrgkanis, Matt Taddy
2018	J	`jnl`	Adversarial Generalized Method of Moments. CoRR Greg Lewis, Vasilis Syrgkanis
2018	—	`conf`	Combinatorial Assortment Optimization. WINE Nicole Immorlica, Brendan Lucier, Jieming Mao, Vasilis Syrgkanis, Christos Tzamos
2018	—	`conf`	Expert identification of visual primitives used by CNNs during mammogram classification. Computer-Aided Diagnosis Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester W. Mackey, Genevieve Patterson
2018	J	`jnl`	Expert identification of visual primitives used by CNNs during mammogram classification. CoRR Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester W. Mackey, Genevieve Patterson
2018	A*	`conf`	Learning to Bid Without Knowing your Value. EC Zhe Feng, Chara Podimata, Vasilis Syrgkanis
2018	J	`jnl`	Low-rank Bandit Methods for High-dimensional Dynamic Pricing. CoRR Jonas Mueller, Vasilis Syrgkanis, Matt Taddy
2018	B	`conf`	On Revenue-Maximizing Mechanisms Assuming Convex Costs. SAGT Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
2018	A*	`conf`	Optimal Data Acquisition for Statistical Estimation. EC Yiling Chen, Nicole Immorlica, Brendan Lucier, Vasilis Syrgkanis, Juba Ziani
2018	A*	`conf`	Optimal and Myopic Information Acquisition. EC Annie Liang, Xiaosheng Mu, Vasilis Syrgkanis
2018	A*	`conf`	Orthogonal Machine Learning: Power and Limitations. ICML Ilias Zadik, Lester W. Mackey, Vasilis Syrgkanis
2018	J	`jnl`	Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation. CoRR Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu
2018	J	`jnl`	Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models. CoRR Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis
2018	A*	`conf`	Semiparametric Contextual Bandits. ICML Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis
2018	J	`jnl`	Semiparametric Contextual Bandits. CoRR Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis
2018	A*	`conf`	Simple vs Optimal Contests with Convex Costs. WWW Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
2018	—	`conf`	Training GANs with Optimism. ICLR (Poster) Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng
2018	A*	`conf`	Truthful Multi-Parameter Auctions with Online Supply: an Impossible Combination. SODA Nikhil R. Devanur, Balasubramanian Sivan, Vasilis Syrgkanis
2017	J	`jnl`	A Proof of Orthogonal Double Machine Learning with Z-Estimators. CoRR Vasilis Syrgkanis
2017	—	`conf`	A Sample Complexity Measure with Applications to Learning Optimal Auctions. NIPS Vasilis Syrgkanis
2017	J	`jnl`	A Sample Complexity Measure with Applications to Learning Optimal Auctions. CoRR Vasilis Syrgkanis
2017	J	`jnl`	Accurate Inference for Adaptive Linear Models. CoRR Yash Deshpande, Lester W. Mackey, Vasilis Syrgkanis, Matt Taddy
2017	J	`jnl`	Combinatorial Assortment Optimization. CoRR Nicole Immorlica, Brendan Lucier, Jieming Mao, Vasilis Syrgkanis, Christos Tzamos
2017	A*	`conf`	Fast convergence of learning in games (invited talk). STOC Vasilis Syrgkanis
2017	J	`jnl`	Inference on Auctions with Weak Assumptions on Information. CoRR Vasilis Syrgkanis, Elie Tamer, Juba Ziani
2017	J	`jnl`	Learning to Bid Without Knowing your Value. CoRR Zhe Feng, Chara Podimata, Vasilis Syrgkanis
2017	J	`jnl`	Optimal Data Acquisition for Statistical Estimation. CoRR Yiling Chen, Nicole Immorlica, Brendan Lucier, Vasilis Syrgkanis, Juba Ziani
2017	J	`jnl`	Optimal Learning from Multiple Information Sources. CoRR Annie Liang, Xiaosheng Mu, Vasilis Syrgkanis
2017	A*	`conf`	Oracle-Efficient Online Learning and Auction Design. FOCS Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2017	J	`jnl`	Orthogonal Machine Learning: Power and Limitations. CoRR Lester W. Mackey, Vasilis Syrgkanis, Ilias Zadik
2017	—	`conf`	Robust Optimization for Non-Convex Objectives. NIPS Robert S. Chen, Brendan Lucier, Yaron Singer, Vasilis Syrgkanis
2017	J	`jnl`	Robust Optimization for Non-Convex Objectives. CoRR Robert S. Chen, Brendan Lucier, Yaron Singer, Vasilis Syrgkanis
2017	J	`jnl`	Simple vs Optimal Mechanisms in Auctions with Convex Payments. CoRR Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
2017	J	`jnl`	The Price of Anarchy in Auctions. J. Artif. Intell. Res. Tim Roughgarden, Vasilis Syrgkanis, Éva Tardos
2017	J	`jnl`	Training GANs with Optimism. CoRR Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng
2017	—	`conf`	Welfare Guarantees from Data. NIPS Darrell Hoy, Denis Nekipelov, Vasilis Syrgkanis
2016	A*	`conf`	Bayesian Exploration: Incentivizing Exploration in Bayesian Games. EC Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu
2016	J	`jnl`	Bayesian Exploration: Incentivizing Exploration in Bayesian Games. CoRR Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu
2016	A	`conf`	Bounded Rationality in Wagering Mechanisms. UAI David M. Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2016	A*	`conf`	Efficient Algorithms for Adversarial Contextual Learning. ICML Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire
2016	J	`jnl`	Efficient Algorithms for Adversarial Contextual Learning. CoRR Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire
2016	—	`conf`	Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. NIPS Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire
2016	J	`jnl`	Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. CoRR Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire
2016	A*	`conf`	Learning and Efficiency in Games with Dynamic Population. SODA Thodoris Lykouris, Vasilis Syrgkanis, Éva Tardos
2016	A*	`conf`	Learning in Auctions: Regret is Hard, Envy is Easy. FOCS Constantinos Daskalakis, Vasilis Syrgkanis
2016	J	`jnl`	Optimal Auctions with Convex Perceived Payments. CoRR Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis
2016	J	`jnl`	Oracle-Efficient Learning and Auction Design. CoRR Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2016	J	`jnl`	The Price of Anarchy in Auctions. CoRR Tim Roughgarden, Vasilis Syrgkanis, Éva Tardos
2016	A*	`conf`	The price of anarchy in large games. STOC Michal Feldman, Nicole Immorlica, Brendan Lucier, Tim Roughgarden, Vasilis Syrgkanis
2015	A*	`conf`	A Unifying Hierarchy of Valuations with Complements and Substitutes. AAAI Uriel Feige, Michal Feldman, Nicole Immorlica, Rani Izsak, Brendan Lucier, Vasilis Syrgkanis
2015	J	`jnl`	Algorithmic game theory and econometrics. SIGecom Exch. Vasilis Syrgkanis
2015	A*	`conf`	Bayesian Incentive-Compatible Bandit Exploration. EC Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis
2015	J	`jnl`	Bayesian Incentive-Compatible Bandit Exploration. CoRR Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis
2015	A*	`conf`	Econometrics for Learning Agents. EC Denis Nekipelov, Vasilis Syrgkanis, Éva Tardos
2015	J	`jnl`	Econometrics for Learning Agents. CoRR Denis Nekipelov, Vasilis Syrgkanis, Éva Tardos
2015	—	`conf`	Fast Convergence of Regularized Learning in Games. NIPS Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire
2015	J	`jnl`	Fast Convergence of Regularized Learning in Games. CoRR Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire
2015	A*	`conf`	Greedy Algorithms Make Efficient Mechanisms. EC Brendan Lucier, Vasilis Syrgkanis
2015	J	`jnl`	Greedy Algorithms make Efficient Mechanisms. CoRR Brendan Lucier, Vasilis Syrgkanis
2015	A*	`conf`	Information Asymmetries in Common-Value Auctions with Discrete Signals. EC Vasilis Syrgkanis, David Kempe, Éva Tardos
2015	J	`jnl`	Learning and Efficiency in Games with Dynamic Population. CoRR Thodoris Lykouris, Vasilis Syrgkanis, Éva Tardos
2015	J	`jnl`	Learning in Auctions: Regret is Hard, Envy is Easy. CoRR Constantinos Daskalakis, Vasilis Syrgkanis
2015	J	`jnl`	Multi-parameter Auctions with Online Supply. CoRR Nikhil R. Devanur, Balasubramanian Sivan, Vasilis Syrgkanis
2015	—	`conf`	No-Regret Learning in Bayesian Games. NIPS Jason D. Hartline, Vasilis Syrgkanis, Éva Tardos
2015	J	`jnl`	No-Regret Learning in Repeated Bayesian Games. CoRR Jason D. Hartline, Vasilis Syrgkanis, Éva Tardos
2015	J	`jnl`	Price of Stability in Games of Incomplete Information. CoRR Vasilis Syrgkanis
2015	J	`jnl`	Pricing Queries Approximately Optimally. CoRR Vasilis Syrgkanis, Johannes Gehrke
2015	J	`jnl`	Robust Data-Driven Efficiency Guarantees in Auctions. CoRR Darrell Hoy, Denis Nekipelov, Vasilis Syrgkanis
2015	A*	`conf`	Simple Auctions with Simple Strategies. EC Nikhil R. Devanur, Jamie Morgenstern, Vasilis Syrgkanis, S. Matthew Weinberg
2015	A*	`conf`	Social Status and Badge Design. WWW Nicole Immorlica, Gregory Stoddard, Vasilis Syrgkanis
2015	J	`jnl`	The Price of Anarchy in Large Games. CoRR Michal Feldman, Nicole Immorlica, Brendan Lucier, Tim Roughgarden, Vasilis Syrgkanis
2014	J	`jnl`	A Unifying Hierarchy of Valuations with Complements and Substitutes. CoRR Uriel Feige, Michal Feldman, Nicole Immorlica, Rani Izsak, Brendan Lucier, Vasilis Syrgkanis
2014	J	`jnl`	A Unifying Hierarchy of Valuations with Complements and Substitutes. Electron. Colloquium Comput. Complex. Uriel Feige, Michal Feldman, Nicole Immorlica, Rani Izsak, Brendan Lucier, Vasilis Syrgkanis
2014	B	`conf`	Strong Price of Anarchy, Utility Games and Coalitional Dynamics. SAGT Yoram Bachrach, Vasilis Syrgkanis, Éva Tardos, Milan Vojnovic
2013	J	`jnl`	Auctions vs Negotiations in Irregular Markets. CoRR Balasubramanian Sivan, Vasilis Syrgkanis
2013	A*	`conf`	Composable and efficient mechanisms. STOC Vasilis Syrgkanis, Éva Tardos
2013	J	`jnl`	Cost-Recovering Bayesian Algorithmic Mechanism Design CoRR Hu Fu, Brendan Lucier, Balasubramanian Sivan, Vasilis Syrgkanis
2013	A*	`conf`	Cost-recovering bayesian algorithmic mechanism design. EC Hu Fu, Brendan Lucier, Balasubramanian Sivan, Vasilis Syrgkanis
2013	J	`jnl`	Draft Auctions. CoRR Nikhil R. Devanur, Jamie Morgenstern, Vasilis Syrgkanis
2013	—	`conf`	Equilibrium in Combinatorial Public Projects. WINE Brendan Lucier, Yaron Singer, Vasilis Syrgkanis, Éva Tardos
2013	—	`conf`	Incentives and Efficiency in Uncertain Collaborative Environments. WINE Yoram Bachrach, Vasilis Syrgkanis, Milan Vojnovic
2013	J	`jnl`	Incentives and Efficiency in Uncertain Collaborative Environments. CoRR Yoram Bachrach, Vasilis Syrgkanis, Milan Vojnovic
2013	—	`conf`	Limits of Efficiency in Sequential Auctions. WINE Michal Feldman, Brendan Lucier, Vasilis Syrgkanis
2013	J	`jnl`	Limits of Efficiency in Sequential Auctions. CoRR Michal Feldman, Brendan Lucier, Vasilis Syrgkanis
2013	C	`conf`	Selfish Resource Allocation in Optical Networks. CIAC Evangelos Bampas, Aris Pagourtzis, George Pierrakos, Vasilis Syrgkanis
2013	J	`jnl`	Social Status and Badge Design. CoRR Nicole Immorlica, Gregory Stoddard, Vasilis Syrgkanis
2013	J	`jnl`	Strong Price of Anarchy and Coalitional Dynamics. CoRR Yoram Bachrach, Vasilis Syrgkanis, Éva Tardos, Milan Vojnovic
2013	—	`conf`	Vickrey Auctions for Irregular Distributions. WINE Balasubramanian Sivan, Vasilis Syrgkanis
2012	J	`jnl`	Bayesian Games and the Smoothness Framework CoRR Vasilis Syrgkanis
2012	J	`jnl`	Bayesian Sequential Auctions CoRR Vasilis Syrgkanis, Éva Tardos
2012	A*	`conf`	Bayesian sequential auctions. EC Vasilis Syrgkanis, Éva Tardos
2012	J	`jnl`	Composable and Efficient Mechanisms CoRR Vasilis Syrgkanis, Éva Tardos
2012	J	`jnl`	Lower Bounds on Revenue of Approximately Optimal Auctions CoRR Balasubramanian Sivan, Vasilis Syrgkanis, Omer Tamuz
2012	—	`conf`	Lower Bounds on Revenue of Approximately Optimal Auctions. WINE Balasubramanian Sivan, Vasilis Syrgkanis, Omer Tamuz
2012	A*	`conf`	Sequential auctions and externalities. SODA Renato Paes Leme, Vasilis Syrgkanis, Éva Tardos
2012	A	`conf`	The curse of simultaneity. ITCS Renato Paes Leme, Vasilis Syrgkanis, Éva Tardos
2012	J	`jnl`	The dining bidder problem: à la russe et à la française. SIGecom Exch. Renato Paes Leme, Vasilis Syrgkanis, Éva Tardos
2011	J	`jnl`	Sequential Auctions and Externalities CoRR Renato Paes Leme, Vasilis Syrgkanis, Éva Tardos
2010	—	`conf`	The Complexity of Equilibria in Cost Sharing Games. WINE Vasilis Syrgkanis