This paper considers a multi-depot heterogeneous vehicle routing problem (MDHVRP) with
time windows, which is very crucial for hazardous materials transportation. For this reason …

Federated learning (FL) has gained much attention in recent years for building privacy-
preserving collaborative learning systems. However, FL algorithms for constrained machine …

In multiagent reinforcement learning, policy evaluation is a central problem. To solve this
problem, decentralized temporal-difference (TD) learning is one of the most popular …

Computing offloading based on mobile edge computing (MEC) for mobile devices (MDs)
has received great attentions in recent years. Strategy selection is an extremely important …

Submodular functions, as well as the sub-class of decomposable submodular functions, and
their optimization appear in a wide range of applications in machine learning …

The computational bottleneck in distributed optimization methods, which is based on
projected gradient descent, is due to the computation of a full gradient vector and projection …

In order to rapidly train deep learning models, many adaptive gradient methods have been
proposed in recent years, such as Adam and AMSGrad. However, the computation of the full …

We consider a two-network saddle-point problem with constraints, whose projections are
expensive. We propose a projection-free algorithm, which is referred to as Distributed Frank …