Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring.

Research team led by Chuliang Weng introduces D2-GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node representation ...

When the state space becomes large, traditional techniques, such as the backward dynamic programming algorithm (i.e., backward induction or value iteration), may no longer be effective in finding a ...

Jason Southerland, Andrew Loerch, Using Approximate Dynamic Programming to Model Military Force Mix Adaptation, Military Operations Research, Vol. 23, No. 4 (2018), pp. 25-36 ...

Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an integral part of the Robotics, System and ...

It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .

This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for computational geometry. We will discuss how to use these techniques ...

Dynamic Programming and Optimal Control Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an ...