Data market design through deep learning
SS Ravindranath, Y Jiang… - Advances in Neural …, 2023 - proceedings.neurips.cc
The data market design problem is a problem in economic theory to find a set of signaling
schemes (statistical experiments) to maximize expected revenue to the information seller …
schemes (statistical experiments) to maximize expected revenue to the information seller …
Optimal auctions through deep learning: Advances in differentiable economics
Designing an incentive compatible auction that maximizes expected revenue is an intricate
task. The single-item case was resolved in a seminal piece of work by Myerson in 1981, but …
task. The single-item case was resolved in a seminal piece of work by Myerson in 1981, but …
On the robustness of mechanism design under total variation distance
A Makur, M Mertzanidis, A Psomas… - Advances in Neural …, 2024 - proceedings.neurips.cc
We study the problem of designing mechanisms when agents' valuation functions are drawn
from unknown and correlated prior distributions. In particular, we are given a prior …
from unknown and correlated prior distributions. In particular, we are given a prior …
Polarization-encoded photonic quantum-to-quantum Bernoulli factory based on a quantum dot source
A Bernoulli factory is a randomness manipulation routine that takes as input a Bernoulli
random variable, outputting another Bernoulli variable whose bias is a function of the input …
random variable, outputting another Bernoulli variable whose bias is a function of the input …
GemNet: Menu-Based, strategy-proof multi-bidder auctions through deep learning
Differentiable economics uses deep learning for automated mechanism design. Despite
strong progress, it has remained an open problem to learn multi-bidder, general, and fully …
strong progress, it has remained an open problem to learn multi-bidder, general, and fully …
Truthful auctions for automated bidding in online advertising
Automated bidding, an emerging intelligent decision making paradigm powered by machine
learning, has become popular in online advertising. Advertisers in automated bidding …
learning, has become popular in online advertising. Advertisers in automated bidding …
Computing simple mechanisms: Lift-and-round over marginal reduced forms
We study revenue maximization in multi-item multi-bidder auctions under the natural item-
independence assumption–a classical problem in Multi-Dimensional Bayesian Mechanism …
independence assumption–a classical problem in Multi-Dimensional Bayesian Mechanism …
Simultaneous Auctions are Approximately Revenue-Optimal for Subadditive Bidders
We study revenue maximization in multi-item auctions, where bidders have subadditive
valuations over independent items 48. Providing a simple mechanism that is approximately …
valuations over independent items 48. Providing a simple mechanism that is approximately …
Mechanism design under approximate incentive compatibility
A fundamental assumption in classical mechanism design is that buyers are perfect
optimizers. However, in practice, buyers may be limited by their computational capabilities or …
optimizers. However, in practice, buyers may be limited by their computational capabilities or …
How to sell information optimally: An algorithmic study
Y Cai, G Velegkas - arXiv preprint arXiv:2011.14570, 2020 - arxiv.org
We investigate the algorithmic problem of selling information to agents who face a decision-
making problem under uncertainty. We adopt the model recently proposed by Bergemann et …
making problem under uncertainty. We adopt the model recently proposed by Bergemann et …