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Recent advances in Fourier analysis have brought new tools to efficiently represent and learn set functions.
On the Fourier analysis of Boolean functions
A. Bernasconi, B. Codenotti, and J. Simon · 1996
Earlier work this paper cites.
Using value queries in combinatorial auctions
B. Hudson and T. Sandholm · 2003
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Preference elicitation and query learning
A. Blum, J. Jackson, T. Sandholm, and M. Zinkevich · 2004
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Least angle regression
B. Efron, T. Hastie, I. Johnstone, R. Tibshirani, et al · 2004
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Applying learning algorithms to preference elicitation
S. Lahaie and C. Parkes · 2004
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The clock-proxy auction: A practical combinatorial auction design
L. Ausubel, P. Cramton, and P. Milgrom · 2006
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The communication requirements of efficient allocations and supporting prices
N. Nisan and I. Segal · 2006
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Package auctions and exchanges
P. Milgrom · 2007
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Hierarchical package bidding: A paper & pencil combinatorial auction
J. K. Goeree and C. A. Holt · 2010
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Kernel methods for revealed preference analysis
S. Lahaie · 2010
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Auction design for wind rights
L. Ausubel and P. Cramton · 2011
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Combinatorial auctions with restricted complements
I. Abraham, M. Babaioff, S. Dughmi, and T. Roughgarden · 2012
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On the impact of package selection in combinatorial auctions: an experimental study in the context of spectrum auction design
T. Scheffel, G. Ziegler, and M. Bichler · 2012
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Learning Fourier sparse set functions
P. Stobbe and A. Krause · 2012
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Spectrum auction design
P. Cramton · 2013
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Analysis of boolean functions
R. O’Donnell · 2014
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A practical guide to the combinatorial clock auction
L. M. Ausubel and O. Baranov · 2017
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Sats: A universal spectrum auction test suite
M. Weiss, B. Lubin, and S. Seuken · 2017
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Automated mechanism design via neural networks
W. Shen, P. Tang, and S. Zuo · 2019
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Discrete signal processing with set functions
M. Püschel and C. Wendler · 2020
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Reinforcement mechanism design: With applications to dynamic pricing in sponsored search auctions
W. Shen, B. Peng, H. Liu, M. Zhang, R. Qian, Y. Hong, Z. Guo, Z. Ding, P. Lu, and P. Tang · 2020
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Deep learning—powered iterative combinatorial auctions
Jakob Weissteiner and Sven Seuken · 2020
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Machine learning-powered iterative combinatorial auctions
G. Brero, B. Lubin, and S. Seuken · 2021
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A permutation-equivariant neural network architecture for auction design
J. Rahme, S. Jelassi, J. Bruna, and M. Weinberg · 2021
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