3 citations · 6 across the 20 of their papers we have counts for
4 papers · 1 filter
LOFA: Online Influence Maximization under Full-Bandit Feedback using Lazy Forward Selection
Jinyu Xu, Abhishek K. Umrawal
We study the problem of influence maximization (IM) in an online setting, where the goal is to select a subset of nodes$\unicode{x2014}$called the seed set$\unicode{x2014}$at each…
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight Delivery
Jiayu Chen, Abhishek K. Umrawal, Tian Lan +1
With the freight delivery demands and shipping costs increasing rapidly, intelligent control of fleets to enable efficient and cost-conscious solutions becomes an important problem…
DART: aDaptive Accept RejecT for non-linear top-K subset identification
Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn +1
We consider the bandit problem of selecting out of arms at each time step. The reward can be a non-linear function of the rewards of the selected individual arms. The direc…
Stochastic Top- Subset Bandits with Linear Space and Non-Linear Feedback
Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn +1
Many real-world problems like Social Influence Maximization face the dilemma of choosing the best out of options at a given time instant. This setup can be modeled as a com…