Deep neural networks (DNN) are the de-facto solution behind many intelligent applications
of today, ranging from machine translation to autonomous driving. DNNs are accurate but …

We present a fascinating model that has lately caught attention among physicists working in
complexity related fields. Though it originated from mathematics and later from economics …

This paper develops a price-theoretic framework for matching markets with heterogeneous
preferences. The model departs from the Gale and Shapley model by assuming that a finite …

The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a
profound influence on market design, both directly, by being adapted into practical matching …

Many real matching markets are subject to distributional constraints. These constraints often
take the form of restrictions on the numbers of agents on one side of the market matched to …

Fog computing has risen as a promising architecture for future Internet of Things, 5G and
embedded artificial intelligence applications with stringent service delay requirements along …

This paper studies matching in vertical networks, generalizing the theory of matching in two-
sided markets. It gives sufficient conditions for the existence of stable networks and presents …

We introduce a two‐sided, many‐to‐one matching with contracts model in which agents with
unit demand match to branches that may have multiple slots available to accept contracts …

We introduce a model in which agents in a network can trade via bilateral contracts. We find
that when continuous transfers are allowed and utilities are quasi-linear, the full …

Accommodating couples has been a long-standing issue in the design of centralized labor
market clearinghouses for doctors and psychologists, because couples view pairs of jobs as …