The increasingly tight coupling between humans and system operations in domains ranging
from intelligent infrastructure to e-commerce has led to a challenging new class of problems …

Workers recruitment remains a significant issue in Mobile Crowdsourcing (MCS), where the
aim is to recruit a group of workers that maximizes the expected Quality of Service (QoS) …

In this paper, we introduce a multi-objective selection hyper-heuristic approach combining
Reinforcement Learning,(meta) heuristic selection, and group decision-making as …

We consider a budgeted combinatorial multi-armed bandit setting where, in every round, the
algorithm selects a super-arm consisting of one or more arms. The goal is to minimize the …

Demand response is a crucial tool to maintain the stability of the smart grids. With the
upcoming research trends in the area of electricity markets, it has become a possibility to …

There are numerous situations when a service requester wishes to expertsource a series of
identical but non-trivial tasks from a pool of experts so as to achieve an assured accuracy …

How should a firm allocate its limited interviewing resources to select the optimal cohort of
new employees from a large set of job applicants? How should that firm allocate cheap but …

There is a rapid increase in the cooperative learning paradigm in online learning settings, ie,
federated learning (FL). Unlike most FL settings, there are many situations where the agents …

We develop and extend a line of recent works on the design of mechanisms for
heterogeneous tasks assignment problem in'crowdsourcing'. The budgeted market we …

Strategic behavior against sequential learning methods, such as" click framing''in real
recommendation systems, have been widely observed. Motivated by such behavior we …