We initiate the study of $\textit {behavioral information design} $ through deep learning. In
information design, a $\textit {sender} $ aims to persuade a $\textit {receiver} $ to take certain …

We consider multiple senders with informational advantage signaling to convince a single
self-interested actor towards certain actions. Generalizing the seminal Bayesian Persuasion …

We consider a novel dynamic pricing and learning setting where in addition to setting prices
of products in sequential rounds, the seller also ex-ante commits to 'advertising schemes' …

We revisit the classic Pandora's Box (PB) problem under correlated distributions on the box
values. Recent work of arXiv: 1911.01632 obtained constant approximate algorithms for a …

Data fuels machine learning (ML)-rich and high-quality training data is essential to the
success of ML. However, to transform ML from the race among a few large corporations to …

The literature on strategic communication originated with the influential cheap talk model,
which precedes the Bayesian persuasion model by three decades. This model describes an …

Prophet inequality concerns a basic optimal stopping problem and states that simple
threshold stopping policies--ie, accepting the first reward larger than a certain threshold--can …

In the area of query complexity of Boolean functions, the most widely studied cost measure
of an algorithm is the worst-case number of queries made by it on an input. Motivated by the …

We study a natural application of contract design to search problems with probabilistic prior
and exploration costs. These problems have a plethora of applications and are expressed …

In this work, we study a scheduling problem with explorable uncertainty. Each job comes
with an upper limit of its processing time, which could be potentially reduced by testing the …