Name
Title | ||
|---|---|---|
Robust Dynamic Trajectory Regression on Road Networks: A Multi-task Learning Framework |
Abstract | ||
|---|---|---|
Trajectory regression, which aims to predict the travel time of arbitrary trajectories on road networks, attracts significant attention in various applications of traffic systems these years. In this paper, we tackle this problem with a multitask learning (MTL) framework. To take the temporal nature of the problem into consideration, we divide the regression problem into a set of sub-tasks of distinct time periods, then the problem can be treated in a multi-task learning framework. Further, we propose a novel regularization term in which we exploit the block sparse structure to augment the robustness of the model. In addition, we incorporate the spatial smoothness over road links and thus achieve a spatial-temporal framework. An accelerated proximal algorithm is adopted to solve the convex but non-smooth problem, which will converge to the global optimum. Experiments on both synthetic and real data sets demonstrate the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICDM.2014.132 | ICDM |
Keywords | Field | DocType |
multitask learning framework,regression problem,traffic systems,travel time prediction,accelerated proximal algorithm,learning (artificial intelligence),traffic engineering computing,regression analysis,robust dynamic trajectory regression,trajectory regression,arbitrary trajectories,convex nonsmooth problem,road networks,spatial-temporal framework,multi-task learning,block sparse structure,trajectory control,mtl framework,structured sparsity,dynamic,optimization,data models,trajectory,acceleration,robustness | Data modeling,Data mining,Data set,Computer science,Robustness (computer science),Regularization (mathematics),Artificial intelligence,Smoothness,Trajectory,Mathematical optimization,Multi-task learning,Exploit,Machine learning | Conference |
ISSN | Citations | PageRank |
1550-4786 | 4 | 0.41 |
References | Authors | |
13 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aiqing Huang | 1 | 4 | 0.41 |
| Linli Xu | 2 | 790 | 42.51 |
| Yitan Li | 3 | 32 | 3.11 |
| Enhong Chen | 4 | 1235 | 86.93 |