activity
20182020
most citedComputation Reallocation for Object Detection

30 citations · 46 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV20207 cited

Powering One-shot Topological NAS with Stabilized Share-parameter Proxy

Ronghao Guo, Chen Lin, Chuming Li +4

One-shot NAS method has attracted much interest from the research community due to its remarkable training efficiency and capacity to discover high performance models. However, the…

cs.CV201930 cited

Computation Reallocation for Object Detection

Feng Liang, Chen Lin, Ronghao Guo +4

The allocation of computation resources in the backbone is a crucial issue in object detection. However, classification allocation pattern is usually adopted directly to object det…

cs.IR2019

FLEN: Leveraging Field for Scalable CTR Prediction

Wenqiang Chen, Lizhang Zhan, Yuanlong Ci +3

Click-Through Rate (CTR) prediction has been an indispensable component for many industrial applications, such as recommendation systems and online advertising. CTR prediction syst…

cs.CV20199 cited

Improving One-shot NAS by Suppressing the Posterior Fading

Xiang Li, Chen Lin, Chuming Li +4

There is a growing interest in automated neural architecture search (NAS). To improve the efficiency of NAS, previous approaches adopt weight sharing method to force all models sha…

cs.CV2019

AM-LFS: AutoML for Loss Function Search

Chuming Li, Yuan Xin, Chen Lin +4

Designing an effective loss function plays an important role in visual analysis. Most existing loss function designs rely on hand-crafted heuristics that require domain experts to…

cs.CV2019

Online Hyper-parameter Learning for Auto-Augmentation Strategy

Chen Lin, Minghao Guo, Chuming Li +5

Data augmentation is critical to the success of modern deep learning techniques. In this paper, we propose Online Hyper-parameter Learning for Auto-Augmentation (OHL-Auto-Aug), an…