Abstract The Internet of Things (IoT) allows communication between devices, things, and
any digital assets that send and receive data over a network without requiring interaction …

The popularity of deep reinforcement learning (DRL) applications in economics has
increased exponentially. DRL, through a wide range of capabilities from reinforcement …

To enable the large scale and efficient deployment of Artificial Intelligence (AI), the
confluence of AI and Edge Computing has given rise to Edge Intelligence, which leverages …

Online algorithms are a hallmark of worst case optimization under uncertainty. On the other
hand, in practice, the input is often far from worst case, and has some predictable …

Blockchain has recently been applied in many applications such as bitcoin, smart grid, and
Internet of Things (IoT) as a public ledger of transactions. However, the use of blockchain in …

Reinforcement learning algorithms describe how an agent can learn an optimal action policy
in a sequential decision process, through repeated experience. In a given environment, the …

State-of-the-art drone technologies have severe flight time limitations due to weight
constraints, which inevitably lead to a relatively small amount of available energy. Therefore …

In classification models, fairness can be ensured by solving a constrained optimization
problem. We focus on fairness constraints like Disparate Impact, Demographic Parity, and …

The design of revenue-maximizing auctions for settings with private budgets is a hard task.
Even the single-item case is not fully understood, and there are no analytical results for …

Abstract Moulin [1980] characterizes the single-facility, deterministic strategy-proof
mechanisms for social choice with single-peaked preferences as the set of generalized …