2024
77. Consistency of Neural Causal Partial Identification
Jiyuan Tan, Jose Blanchet, Vasilis Syrgkanis, NeurIPS2024
76. Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity
Vahid Balazadeh, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan, Vasilis Syrgkanis, NeurIPS2024
75. Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Jikai Jin, Vasilis Syrgkanis, NeurIPS2024 (Spotlight)
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