Các bài viết có thể truy cập công khai - Vasilis SyrgkanisTìm hiểu thêm
Không có ở bất kỳ nơi nào: 1
On Revenue-Maximizing Mechanisms Assuming Convex Costs
A Greenwald, T Oyakawa, V Syrgkanis
Algorithmic Game Theory: 11th International Symposium, SAGT 2018, Beijing …, 2018
Các cơ quan ủy nhiệm: US National Science Foundation
Có tại một số nơi: 19
Orthogonal statistical learning
DJ Foster, V Syrgkanis
The Annals of Statistics 51 (3), 879-908, 2023
Các cơ quan ủy nhiệm: US National Science Foundation
Minimax estimation of conditional moment models
N Dikkala, G Lewis, L Mackey, V Syrgkanis
Advances in Neural Information Processing Systems 33, 12248-12262, 2020
Các cơ quan ủy nhiệm: US National Science Foundation
Learning and efficiency in games with dynamic population
T Lykouris, V Syrgkanis, É Tardos
Proceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete …, 2016
Các cơ quan ủy nhiệm: US National Science Foundation
Oracle-efficient online learning and auction design
M Dudík, N Haghtalab, H Luo, RE Schapire, V Syrgkanis, JW Vaughan
Journal of the ACM (JACM) 67 (5), 1-57, 2020
Các cơ quan ủy nhiệm: US National Science Foundation
Learning in auctions: Regret is hard, envy is easy
C Daskalakis, V Syrgkanis
2016 ieee 57th annual symposium on foundations of computer science (focs …, 2016
Các cơ quan ủy nhiệm: US National Science Foundation
Genome-scale screens identify factors regulating tumor cell responses to natural killer cells
M Sheffer, E Lowry, N Beelen, M Borah, SNA Amara, CC Mader, JA Roth, ...
Nature Genetics 53 (8), 1196-1206, 2021
Các cơ quan ủy nhiệm: US Department of Defense, US National Institutes of Health, Academy of …
The price of anarchy in large games
M Feldman, N Immorlica, B Lucier, T Roughgarden, V Syrgkanis
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
Các cơ quan ủy nhiệm: European Commission
Optimal data acquisition for statistical estimation
Y Chen, N Immorlica, B Lucier, V Syrgkanis, J Ziani
Proceedings of the 2018 ACM Conference on Economics and Computation, 27-44, 2018
Các cơ quan ủy nhiệm: US National Science Foundation
Riesznet and forestriesz: Automatic debiased machine learning with neural nets and random forests
V Chernozhukov, W Newey, VM Quintas-Martınez, V Syrgkanis
International Conference on Machine Learning, 3901-3914, 2022
Các cơ quan ủy nhiệm: US National Science Foundation
A unifying hierarchy of valuations with complements and substitutes
U Feige, M Feldman, N Immorlica, R Izsak, B Lucier, V Syrgkanis
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
Các cơ quan ủy nhiệm: European Commission
Dynamically aggregating diverse information
A Liang, X Mu, V Syrgkanis
Proceedings of the 22nd ACM Conference on Economics and Computation, 687-688, 2021
Các cơ quan ủy nhiệm: US National Science Foundation
Bid prediction in repeated auctions with learning
G Noti, V Syrgkanis
Proceedings of the Web Conference 2021, 3953-3964, 2021
Các cơ quan ủy nhiệm: European Commission
Minimax Instrumental Variable Regression and Convergence Guarantees without Identification or Closedness
A Bennett, N Kallus, X Mao, W Newey, V Syrgkanis, M Uehara
The Thirty Sixth Annual Conference on Learning Theory, 2291-2318, 2023
Các cơ quan ủy nhiệm: US National Science Foundation, National Natural Science Foundation of China
Partial identification of treatment effects with implicit generative models
V Balazadeh Meresht, V Syrgkanis, RG Krishnan
Advances in Neural Information Processing Systems 35, 22816-22829, 2022
Các cơ quan ủy nhiệm: Natural Sciences and Engineering Research Council of Canada
A multifactorial model of T cell expansion and durable clinical benefit in response to a PD-L1 inhibitor
MDM Leiserson, V Syrgkanis, A Gilson, M Dudik, S Gillett, J Chayes, ...
PLoS One 13 (12), e0208422, 2018
Các cơ quan ủy nhiệm: US National Institutes of Health
Multi-item nontruthful auctions achieve good revenue
C Daskalakis, M Fishelson, B Lucier, V Syrgkanis, S Velusamy
SIAM Journal on Computing 51 (6), 1796-1838, 2022
Các cơ quan ủy nhiệm: US National Science Foundation, US Department of Energy, US Department of …
Towards efficient representation identification in supervised learning
K Ahuja, D Mahajan, V Syrgkanis, I Mitliagkas
Conference on Causal Learning and Reasoning, 19-43, 2022
Các cơ quan ủy nhiệm: Natural Sciences and Engineering Research Council of Canada
Incentivizing compliance with algorithmic instruments
DDT Ngo, L Stapleton, V Syrgkanis, S Wu
International Conference on Machine Learning, 8045-8055, 2021
Các cơ quan ủy nhiệm: US National Science Foundation
Simple vs optimal contests with convex costs
A Greenwald, T Oyakawa, V Syrgkanis
Proceedings of the 2018 World Wide Web Conference, 1429-1438, 2018
Các cơ quan ủy nhiệm: US National Science Foundation
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