We consider the problem of maximizing the gains from trade (GFT) in two-...
Numerous applications in machine learning and data analytics can be
form...
We study the model of metric voting proposed by Feldman et al. [2020]. I...
We revisit the problem of learning in two-player zero-sum Markov games,
...
We propose a new Markov Decision Process (MDP) model for ad auctions to
...
We consider online learning in multi-player smooth monotone games. Exist...
We study the problem of social welfare maximization in bilateral trade, ...
We study first-order methods for constrained min-max optimization. Exist...
We study monotone inclusions and monotone variational inequalities, as w...
Distributed computing (cloud) networks, e.g., mobile edge computing (MEC...
The timely delivery of resource-intensive and latency-sensitive services...
Next-generation distributed computing networks (e.g., edge and fog compu...
We are entering a rapidly unfolding future driven by the delivery of
rea...
Emerging Metaverse applications, designed to deliver highly interactive ...
The monotone variational inequality is a central problem in mathematical...
Emerging distributed cloud architectures, e.g., fog and mobile edge
comp...
The worlds of computing, communication, and storage have for a long time...
We study the problem of selling information to a data-buyer who faces a
...
We study revenue maximization in multi-item multi-bidder auctions under ...
Machine learning has developed a variety of tools for learning and
repre...
We study the problem of selling n heterogeneous items to a single buyer,...
We investigate the algorithmic problem of selling information to agents ...
We study gains from trade in multi-dimensional two-sided markets.
Specif...
As mobile edge computing (MEC) finds widespread use for relieving the
co...
We consider the black-box reduction from multi-dimensional revenue
maxim...
We study the sample complexity of learning revenue-optimal multi-item
au...
We study a new model of complementary valuations, which we call "proport...
We study a classical Bayesian mechanism design problem where a seller is...
We provide a unified view of many recent developments in Bayesian mechan...
We propose a framework for ensuring safe behavior of a reinforcement lea...
The seminal impossibility result of Myerson and Satterthwaite (1983) sta...
This paper studies the revenue of simple mechanisms in settings where a
...
We provide algorithms that learn simple auctions whose revenue is
approx...
We propose an optimum mechanism for providing monetary incentives to the...