In this paper, we study the setting in which data owners train machine
l...
We study autobidding ad auctions with user costs, where each bidder is
v...
The streaming model of computation is a popular approach for working wit...
We study the price of anarchy of the first-price auction in the autobidd...
In a typical optimization problem, the task is to pick one of a number o...
We study bilateral trade between two strategic agents. The celebrated re...
In classic auction theory, reserve prices are known to be effective for
...
In shuffle privacy, each user sends a collection of randomized messages ...
We define a model of interactive communication where two agents with pri...
A patient seller aims to sell a good to an impatient buyer (i.e., one wh...
Auto-bidding has become one of the main options for bidding in online
ad...
In the shuffle model of differential privacy, data-holding users send
ra...
A centrally differentially private algorithm maps raw data to differenti...
We prove a general connection between the communication complexity of
tw...
We consider the sorted top-k problem whose goal is to recover the top-k
...
In consumer search, there is a set of items. An agent has a prior over h...
We study the power of interactivity in local differential privacy. First...
It is common in recommendation systems that users both consume and produ...
We design two learning algorithms that simultaneously promise differenti...
We study a basic private estimation problem: each of n users draws a sin...
In a social learning setting, there is a set of actions, each of which h...
We consider the problem of a single seller repeatedly selling a single i...
Assortment optimization refers to the problem of designing a slate of
pr...
We study the active learning problem of top-k ranking from multi-wise
co...
We study a strategic version of the multi-armed bandit problem, where ea...
Motivated by applications in recommender systems, web search, social cho...