Vasilis Syrgkanis

Orcid: 0000-0001-5047-8772

Affiliations:
  • Cornell University, Ithaca, USA


According to our database1, Vasilis Syrgkanis authored at least 120 papers between 2009 and 2024.

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Bibliography

2024
Consistency of Neural Causal Partial Identification.
CoRR, 2024

Direct Preference Optimization With Unobserved Preference Heterogeneity.
CoRR, 2024

Taking a Moment for Distributional Robustness.
CoRR, 2024

Dynamic Local Average Treatment Effects.
CoRR, 2024

Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity.
CoRR, 2024

Regularized DeepIV with Model Selection.
CoRR, 2024

Applied Causal Inference Powered by ML and AI.
CoRR, 2024

Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation.
CoRR, 2024

Causal Q-Aggregation for CATE Model Selection.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration.
CoRR, 2023

Adaptive Instrument Design for Indirect Experiments.
CoRR, 2023

Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity.
CoRR, 2023

Source Condition Double Robust Inference on Functionals of Inverse Problems.
CoRR, 2023

Inference on Optimal Dynamic Policies via Softmax Approximation.
CoRR, 2023

Post-Episodic Reinforcement Learning Inference.
CoRR, 2023

Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness.
CoRR, 2023

Minimax Instrumental Variable Regression and L<sub>2</sub> Convergence Guarantees without Identification or Closedness.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Inference on Strongly Identified Functionals of Weakly Identified Functions.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Multi-Item Nontruthful Auctions Achieve Good Revenue.
SIAM J. Comput., 2022

Bayesian Exploration: Incentivizing Exploration in Bayesian Games.
Oper. Res., 2022

Learning in auctions: Regret is hard, envy is easy.
Games Econ. Behav., 2022

Empirical Analysis of Model Selection for Heterogenous Causal Effect Estimation.
CoRR, 2022

Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime.
CoRR, 2022

Automatic Debiased Machine Learning for Dynamic Treatment Effects.
CoRR, 2022

Robust Generalized Method of Moments: A Finite Sample Viewpoint.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Partial Identification of Treatment Effects with Implicit Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Debiased Machine Learning without Sample-Splitting for Stable Estimators.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests.
Proceedings of the International Conference on Machine Learning, 2022

Non-parametric Inference Adaptive to Intrinsic Dimension.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Towards efficient representation identification in supervised learning.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021
Combinatorial Assortment Optimization.
ACM Trans. Economics and Comput., 2021

Omitted Variable Bias in Machine Learned Causal Models.
CoRR, 2021

DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions.
CoRR, 2021

Evidence-Based Policy Learning.
CoRR, 2021

Adversarial Estimation of Riesz Representers.
CoRR, 2021

Bid Prediction in Repeated Auctions with Learning.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Dynamically Aggregating Diverse Information.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Double/Debiased Machine Learning for Dynamic Treatment Effects.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Estimating the Long-Term Effects of Novel Treatments.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Incentivizing Compliance with Algorithmic Instruments.
Proceedings of the 38th International Conference on Machine Learning, 2021

Knowledge Distillation as Semiparametric Inference.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Oracle-efficient Online Learning and Auction Design.
J. ACM, 2020

Bayesian Incentive-Compatible Bandit Exploration.
Oper. Res., 2020

Asymptotics of the Empirical Bootstrap Method Beyond Asymptotic Normality.
CoRR, 2020

Simple, Credible, and Approximately-Optimal Auctions.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Minimax Estimation of Conditional Moment Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Statistical Learning with a Nuisance Component (Extended Abstract).
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Estimation and Inference with Trees and Forests in High Dimensions.
Proceedings of the Conference on Learning Theory, 2020

2019
Information Asymmetries in Common-Value Auctions with Discrete Signals.
Math. Oper. Res., 2019

Orthogonal Statistical Learning.
CoRR, 2019

Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Semi-Parametric Efficient Policy Learning with Continuous Actions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Orthogonal Random Forest for Causal Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

Statistical Learning with a Nuisance Component.
Proceedings of the Conference on Learning Theory, 2019

2018
Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models.
CoRR, 2018

Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation.
CoRR, 2018

Adversarial Generalized Method of Moments.
CoRR, 2018

Simple vs Optimal Contests with Convex Costs.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Truthful Multi-Parameter Auctions with Online Supply: an Impossible Combination.
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

Optimal and Myopic Information Acquisition.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

Optimal Data Acquisition for Statistical Estimation.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

Learning to Bid Without Knowing your Value.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

On Revenue-Maximizing Mechanisms Assuming Convex Costs.
Proceedings of the Algorithmic Game Theory - 11th International Symposium, 2018

Expert identification of visual primitives used by CNNs during mammogram classification.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Orthogonal Machine Learning: Power and Limitations.
Proceedings of the 35th International Conference on Machine Learning, 2018

Semiparametric Contextual Bandits.
Proceedings of the 35th International Conference on Machine Learning, 2018

Accurate Inference for Adaptive Linear Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

Training GANs with Optimism.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
The Price of Anarchy in Auctions.
J. Artif. Intell. Res., 2017

Inference on Auctions with Weak Assumptions on Information.
CoRR, 2017

A Proof of Orthogonal Double Machine Learning with Z-Estimators.
CoRR, 2017

Optimal Learning from Multiple Information Sources.
CoRR, 2017

Simple vs Optimal Mechanisms in Auctions with Convex Payments.
CoRR, 2017

Fast convergence of learning in games (invited talk).
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

A Sample Complexity Measure with Applications to Learning Optimal Auctions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Welfare Guarantees from Data.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Robust Optimization for Non-Convex Objectives.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Optimal Auctions with Convex Perceived Payments.
CoRR, 2016

Oracle-Efficient Learning and Auction Design.
CoRR, 2016

Bounded Rationality in Wagering Mechanisms.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

The price of anarchy in large games.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Learning and Efficiency in Games with Dynamic Population.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Efficient Algorithms for Adversarial Contextual Learning.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Algorithmic game theory and econometrics.
SIGecom Exch., 2015

Pricing Queries Approximately Optimally.
CoRR, 2015

Price of Stability in Games of Incomplete Information.
CoRR, 2015

Robust Data-Driven Efficiency Guarantees in Auctions.
CoRR, 2015

No-Regret Learning in Repeated Bayesian Games.
CoRR, 2015

Multi-parameter Auctions with Online Supply.
CoRR, 2015

Social Status and Badge Design.
Proceedings of the 24th International Conference on World Wide Web, 2015

Econometrics for Learning Agents.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Greedy Algorithms Make Efficient Mechanisms.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Simple Auctions with Simple Strategies.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Fast Convergence of Regularized Learning in Games.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

No-Regret Learning in Bayesian Games.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Efficiency of Mechanisms in Complex Markets.
PhD thesis, 2014

A Unifying Hierarchy of Valuations with Complements and Substitutes.
Electron. Colloquium Comput. Complex., 2014

Strong Price of Anarchy, Utility Games and Coalitional Dynamics.
Proceedings of the Algorithmic Game Theory - 7th International Symposium, 2014

2013
Auctions vs Negotiations in Irregular Markets.
CoRR, 2013

Draft Auctions.
CoRR, 2013

Strong Price of Anarchy and Coalitional Dynamics.
CoRR, 2013

Vickrey Auctions for Irregular Distributions.
Proceedings of the Web and Internet Economics - 9th International Conference, 2013

Equilibrium in Combinatorial Public Projects.
Proceedings of the Web and Internet Economics - 9th International Conference, 2013

Limits of Efficiency in Sequential Auctions.
Proceedings of the Web and Internet Economics - 9th International Conference, 2013

Incentives and Efficiency in Uncertain Collaborative Environments.
Proceedings of the Web and Internet Economics - 9th International Conference, 2013

Composable and efficient mechanisms.
Proceedings of the Symposium on Theory of Computing Conference, 2013

Cost-recovering bayesian algorithmic mechanism design.
Proceedings of the fourteenth ACM Conference on Electronic Commerce, 2013

Selfish Resource Allocation in Optical Networks.
Proceedings of the Algorithms and Complexity, 8th International Conference, 2013

2012
The dining bidder problem: à la russe et à la française.
SIGecom Exch., 2012

Bayesian Games and the Smoothness Framework
CoRR, 2012

Lower Bounds on Revenue of Approximately Optimal Auctions.
Proceedings of the Internet and Network Economics - 8th International Workshop, 2012

Sequential auctions and externalities.
Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, 2012

Bayesian sequential auctions.
Proceedings of the 13th ACM Conference on Electronic Commerce, 2012

The curse of simultaneity.
Proceedings of the Innovations in Theoretical Computer Science 2012, 2012

2010
The Complexity of Equilibria in Cost Sharing Games.
Proceedings of the Internet and Network Economics - 6th International Workshop, 2010

2009
Colored Resource Allocation Games.
Proceedings of the 8th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, 2009


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