2024

74. Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill, ICLR2024

73. Empirical Analysis of Model Selection for Heterogenous Causal Effect Estimation
Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis, ICLR2024

72. Causal Q-Aggregation for CATE Model Selection
Hui Lan, Vasilis Syrgkanis, AISTATS2024

2023

71. Minimax Instrumental Variable Regression and L2 Convergence Guarantees without Identification or Closedness
Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara, COLT2023

70. Inference on Strongly Identified Functionals of Weakly Identified Functions
Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara, COLT2023

2022

69. Debiased Machine Learning without Sample-Splitting for Stable Estimators
Qizhao Chen, Vasilis Syrgkanis, Morgane Austern, NeurIPS2022

68. Robust Generalized Method of Moments: A Finite Sample Viewpoint
Dhruv Rohatgi, Vasilis Syrgkanis, NeurIPS2022

67. Partial Identification of Treatment Effects with Implicit Generative Models
Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G Krishnan, NeurIPS2022
Spotlight Presentation

66. RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis, ICML2022
Long Oral Presentation (2% acceptance rate)

65. Evidence-based Policy Learning
Jann Spiess, Vasilis Syrgkanis, CLear2022

64. Non-Parametric Inference Adaptive to Intrinsic Dimension
Khashayar Khosravi, Gregory Lewis, Vasilis Syrgkanis, CLear2022

63. Towards efficient representation identification in supervised learning
Kartik Ahuja, Divyat Mahajan, Ioannis Mitliagkas, Vasilis Syrgkanis, CLear2022

62. Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models
Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis [Github Code]
The Econometrics Journal, 2022

2021

61. Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection
Morgane Austern, Vasilis Syrgkanis, NeurIPS2021

60. Estimating the Long-Term Effects of Novel Treatments
Keith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu, Vasilis Syrgkanis, NeurIPS2021

59. Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation
Greg Lewis, Vasilis Syrgkanis, NeurIPS2021

58. Incentivizing Compliance with Algorithmic Instruments
Daniel Ngo, Logan Stapleton, Vasilis Syrgkanis, Zhiwei Steven Wu, ICML2021

57. DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
Amit Sharma, Vasilis Syrgkanis, Cheng Zhang, Emre Kiciman, ICML2021 Workshop on the Neglected Assumptions in Causal Inference

56. Dynamically Aggregating Diverse Information
Annie Liang, Xiaosheng Mu, Vasilis Syrgkanis, EC2021
Forthcoming at Econometrica, 2021

55. Knowledge Distillation as Semi-Parametric Inference
Tri Dao, Govinda Kamath, Vasilis Syrgkanis, Lester Mackey, ICLR2021

54. Bid Prediction in Repeated Auctions with Learning
Gali Noti, Vasilis Syrgkanis, WWW2021

53. Genome-scale screens identify factors regulating tumor cell responses to natural killer cells
Sheffer et al., Nature Genetics 2021

2020

52. Minimax Estimation of Conditional Moment Models
Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis, NeurIPS2020 [Github Code] [MSR Blogpost]
Preliminary version appeared as: Adversarial Generalized Method of Moments

51. Estimation and Inference with Trees and Forests in High Dimensions
Vasilis Syrgkanis, Manolis Zampetakis, COLT2020

50. Simple, Credible, and Approximately-Optimal Auctions
Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy, EC2020

2019

49. Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
Vasilis Syrgkanis, Victor Lei, Miruna Oprescu, Maggie Hei, Keith Battocchi, Greg Lewis, NeurIPS 2019
Spotlight Presentation (top 3%)
[Github Code]

48. Semi-Parametric Efficient Policy Learning with Continuous Actions
Mert Demirer, Vasilis Syrgkanis, Greg Lewis, Victor Chernozhukov, NeurIPS 2019

47. Low-rank Bandit Methods for High-dimensional Dynamic Pricing
Jonas Mueller, Vasilis Syrgkanis, Matt Taddy, NeurIPS 2019

46. Orthogonal Random Forest for Causal Inference
Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu, ICML 2019
[Github Code]

45. Statisical Learning with a Nuisance Component
Dylan Foster, Vasilis Syrgkanis, COLT 2019
Best Paper Award
Full version: Orthogonal Statistical Learning
Revise and Resubmit at the Annals of Statistics

2018

44. A Multifactorial Model of T Cell Expansion and Durable Clinical Benefit in Response to a PD-L1 Inhibitor
Mark DM Leiserson, Vasilis Syrgkanis, Amy Gilson, Miroslav Dudik, Samuel Funt, Alexandra Snyder, Lester Mackey, PLOS ONE

43. Combinatorial Assortment Optimization
Nicole Immorlica, Brendan Lucier, Jieming Mao, Vasilis Syrgkanis, Christos Tzamos, WINE 2018

42. Semiparametric Contextual Bandits
Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis, ICML 2018

41. Accurate Inference for Adaptive Linear Models
Yash Deshpande, Lester Mackey, Vasilis Syrgkanis, Matt Taddy, ICML 2018

40. Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik, ICML 2018

39. Optimal Data Acquisition for Statistical Estimation
Yiling Chen, Nicole Immorlica, Brendan Lucier, Vasilis Syrgkanis, Juba Ziani, EC 2018

38. Learning to Bid Without Knowing your Value
Zhe Feng, Chara Podimata, Vasilis Syrgkanis, EC 2018
[Github Code]

37. Optimal and Myopic Information Acquisition
Annie Liang, Xiaoseng Mu, Vasilis Syrgkanis, EC 2018

36. Training GANs with Optimism
Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng, ICLR 2018
[Github Code]

35. Simple vs Optimal Contests with Convex Costs
Amy Greenwald, Takehiro Oyakawa, Vasilis Syrgkanis, WWW 2018

35. Truthful Multi-parameter Auctions with Online Supply: an Impossible Combination
Nikhil Devanur, Balasubramanian Sivan, Vasilis Syrgkanis, SODA 2018

2017

34. Robust Optimization for Non-Convex Objectives
Robert Chen, Brendan Lucier, Yaron Singer, Vasilis Syrgkanis, NeurIPS 2017
Oral Presentation (top 1%)
[Github Code]

33. A Sample Complexity Measure with Applications to Learning Optimal Auctions
Vasilis Syrgkanis, NeurIPS 2017

32. Efficiency Guarantees from Data
Darrell Hoy, Denis Nekipelov, Vasilis Syrgkanis, NeurIPS 2017

31. Oracle Efficient Learning and Auction Design
Miroslav Dudik, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan, FOCS 2017

2016

30. Improved Regret Bounds for Adversarial Contextual Bandits
Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire, NeurIPS 2016

29. Learning in Auctions: Regret is Hard, Envy is Easy
Constantinos Daskalakis, Vasilis Syrgkanis, FOCS 2016

28. Bayesian Exploration: Incentivizing Exploration in Bayesian Games
Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu, EC 2016
Full version: Operations Research, 2021

27. Bounded Rationality in Wagering Mechanisms
David M. Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan, UAI 2016

26. Efficient Algorithms for Adversarial Contextual Learning
Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire, ICML 2016

25. The Price of Anarchy in Large Games
Michal Feldman, Nicole Immorlica, Brendan Lucier, Tim Roughgarden, Vasilis Syrgkanis, STOC 2016

24. Learning and Efficiency in Games with Dynamic Population
Thodoris Lykouris, Vasilis Syrgkanis, Eva Tardos, SODA 2016

2015

23. Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire, NeurIPS 2015
Best Paper Award

22. No-Regret Learning in Repeated Bayesian Games
Jason Hartline, Vasilis Syrgkanis, Eva Tardos, NeurIPS 2015

21. Econometrics for Learning Agents
Denis Nekipelov, Vasilis Syrgkanis, Eva Tardos, EC 2015
Best paper award

20. Bayesian Incentive-Compatible Bandit Exploration
Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, EC 2015
Full version: Operations Research, 2020

19. Greedy Algorithms make Efficient Mechanisms
Brendan Lucier, Vasilis Syrgkanis, EC 2015

18. Simple Auctions with Simple Strategies
Nikhil Devanur, Jamie Morgenstern, Vasilis Syrgkanis, S. Matthew Weinberg, EC 2015

17. Information Asymmetries in Common-Value Auctions with Discrete Signals
Vasilis Syrgkanis, David Kempe, Eva Tardos, EC 2015
Full version: Mathematics of Operations Research, 2019
MATLAB Code for computing equilibrium for asymmetric common value first price auction
Mathematica notebook for binary value and binary signals for asymmetric common value first price auction. Includes equilibrium computation and examples.

16. Social Status and Badge Design
Nicole Immorlica, Greg Stoddard, Vasilis Syrgkanis, WWW 2015
Preliminary version at 2013 NBER Market Design Working Group Meeting

15. A Unifying Hierarchy of Valuations with Complements and Substitutes
Uriel Feige, Michal Feldman, Nicole Immorlica, Rani Izsak, Brendan Lucier, Vasilis Syrgkanis, AAAI 2015

2014

14. Strong Price of Anarchy, Utility Games and Coalitional Dynamics
Yoram Bachrach, Vasilis Syrgkanis, Eva Tardos, Milan Vojnovic, SAGT 2014

2013

13. Composable and Efficient Mechanisms
Vasilis Syrgkanis, Eva Tardos, STOC 2013

12. Cost-Recovering Bayesian Algorithmic Mechanism Design
Hu Fu, Brendan Lucier, Balasubramanian Sivan, Vasilis Syrgkanis, EC 2013

11. Vickrey Auctions for Irregular Distributions
Balasubramanian Sivan, Vasilis Syrgkanis, WINE 2013

10. Incentives and Efficiency in Uncertain Collaborative Environments
Yoram Bachrach, Vasilis Syrgkanis, Milan Vojnovic, WINE 2013

9. Limits of Efficiency in Sequential Auctions
Michal Feldman, Brendan Lucier, Vasilis Syrgkanis, WINE 2013

8. Equilibrium in Combinatorial Public Projects
Brendan Lucier, Yaron Singer, Vasilis Syrgkanis, Eva Tardos, WINE 2013

2012

7. Bayesian Games and the Smoothness Framework
Vasilis Syrgkanis, March 2012

6. Bayesian Sequential Auctions
Vasilis Syrgkanis, Eva Tardos, EC 2012

5. Sequential Auctions and Externalities
Renato Paes Leme, Vasilis Syrgkanis, Eva Tardos, SODA 2012

4. The Curse of Simultaneity
Renato Paes Leme, Vasilis Syrgkanis, Eva Tardos, ITCS 2012

3. Lower Bounds on Revenue of Approximately Optimal Auctions
Balasubramanian Sivan, Vasilis Syrgkanis, Omer Tamuz, WINE 2012

2010

2. The Complexity of Equilibria in Cost Sharing Games
Vasilis Syrgkanis, WINE 2010 [Slides]

2009

1. Colored Resource Allocation Games
E. Bampas, A. Pagourtzis, G. Pierrakos, V. Syrgkanis, CTW 2009

Working Papers


Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity
Vahid Balazadeh, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan, Vasilis Syrgkanis

Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Jikai Jin, Vasilis Syrgkanis

Regularized DeepIV with Model Selection
Zihao Li, Hui Lan, Vasilis Syrgkanis, Mengdi Wang, Masatoshi Uehara

Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration
Daniel Ngo, Keegan Harris, Anish Agarwal, Vasilis Syrgkanis, Zhiwei Steven Wu

Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Jikai Jin, Vasilis Syrgkanis

Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Jikai Jin, Vasilis Syrgkanis

Source Condition Double Robust Inference on Functionals of Inverse Problems
Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara

Inference on Optimal Dynamic Policies via Softmax Approximation
Qizhao Chen, Morgane Austern, Vasilis Syrgkanis

Post-Episodic Reinforcement Learning Inference
Vasilis Syrgkanis, Ruohan Zhan

Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime
Anish Agarwal, Vasilis Syrgkanis

Long Story Short: Omitted Variable Bias in Causal Machine Learning
Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis

Automatic Debiased Machine Learning for Dynamic Treatment Effects
Victor Chernozhukov, Whitney Newey, Rahul Singh, Vasilis Syrgkanis

Automatic Debiased Machine Learning via Neural Nets for Generalized Linear Regression
Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis

Evidence-Based Policy Learning
Jann Spiess, Vasilis Syrgkanis

Adversarial Estimation of Reisz Representers
Victor Chernozhukov, Whitney Newey, Rahul Singh, Vasilis Syrgkanis

Inference on Auctions with Weak Assumptions on Information
Vasilis Syrgkanis, Elie Tamer, Juba Ziani [Github Code]

A Proof of Orthogonal Double Machine Learning with Z-Estimators
Vasilis Syrgkanis

Pricing Queries Approximately Optimally
Vasilis Syrgkanis, Johannes Gehrke

Price of Stability in Games of Incomplete Information
Vasilis Syrgkanis, under submission

Surveys

Price of Anarchy in Auctions
Tim Roughgarden, Vasilis Syrgkanis, Eva Tardos
Journal of Artificial Intelligence Research, May 2017

Algorithmic Game Theory and Econometrics
Vasilis Syrgkanis, SIGecom Exchanges, June 2015

The Dining Bidder Problem: a la russe et a la francaise
Renato Paes Leme, Vasilis Syrgkanis, Eva Tardos, SIGecom Exchanges, December 2012
A review of recent results in simultaneous and sequential item auctions.

Theses

Efficiency of Mechanisms in Complex Markets
PhD Thesis, Cornell University, Computer Science Department, August 2014

Equilibria in Congestion Game Models: Existence, Complexity and Efficiency
Vasilis Syrgkanis
Undergraduate Diploma Thesis, National Technical University of Athens, July 2009 (title is in Greek but main content, p. 6 and on, is in English)