Multi-task Learning

MM-DAG: Multi-task DAG Learning for Multi-modal Data--with Application for Traffic Congestion Analysis

This paper proposes to learn Multi-task, Multi-modal Direct Acyclic Graphs (MM-DAGs), which are commonly observed in complex systems, e.g., traffic, manufacturing, and weather systems, whose variables are multi-modal with scalars, vectors, and …

A General Scenario-agnostic Reinforcement Learning for Traffic Signal Control

Reinforcement learning has been recently adopted to revolutionize and optimize traditional traffic signal control systems. Existing methods are either based on a single scenario or multiple independent scenarios, where each scenario has a separate …