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Found 6 papers, 2 papers with code
A Genetic Algorithm-based Framework for Learning Statistical Power Manifold
We also show that the quality of learning the manifold improves as the number of iterations increases for the genetic algorithm.
A Community-Aware Framework for Social Influence Maximization
We propose a community-aware divide-and-conquer framework that involves (i) learning the inherent community structure of the social network, (ii) generating candidate solutions by solving the influence maximization problem for each community, and (iii) selecting the final set of seed nodes using a novel progressive budgeting scheme.
On Parameter Estimation in Unobserved Components Models subject to Linear Inequality Constraints
We propose a new \textit{quadratic programming-based} method of approximating a nonstandard density using a multivariate Gaussian density.
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight Delivery
Then an efficient multi-transfer matching algorithm is executed to assign the delivery requests to the trucks.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Joint Passengers & Goods Transportation
Through simulations on a realistic multi-agent urban mobility platform, we demonstrate that FlexPool outperforms other model-free settings in serving the demands from passengers & goods.
Stochastic Top-$K$ Subset Bandits with Linear Space and Non-Linear Feedback
Many real-world problems like Social Influence Maximization face the dilemma of choosing the best $K$ out of $N$ options at a given time instant.
