31 citations · 75 across the 6 of their papers we have counts for
6 papers
An Ensemble Learning Approach for In-situ Monitoring of FPGA Dynamic Power
Zhe Lin, Sharad Sinha, Wei Zhang
As field-programmable gate arrays become prevalent in critical application domains, their power consumption is of high concern. In this paper, we present and evaluate a power monit…
HL-Pow: A Learning-Based Power Modeling Framework for High-Level Synthesis
Zhe Lin, Jieru Zhao, Sharad Sinha +1
High-level synthesis (HLS) enables designers to customize hardware designs efficiently. However, it is still challenging to foresee the correlation between power consumption and HL…
FP-Stereo: Hardware-Efficient Stereo Vision for Embedded Applications
Jieru Zhao, Tingyuan Liang, Liang Feng +4
Fast and accurate depth estimation, or stereo matching, is essential in embedded stereo vision systems, requiring substantial design effort to achieve an appropriate balance among…
Learning from a Lightweight Teacher for Efficient Knowledge Distillation
Yuang Liu, Wei Zhang, Jun Wang
Knowledge Distillation (KD) is an effective framework for compressing deep learning models, realized by a student-teacher paradigm requiring small student networks to mimic the sof…
Momentum-based Accelerated Q-learning
Bowen Weng, Lin Zhao, Huaqing Xiong +1
This paper studies accelerated algorithms for Q-learning. We propose an acceleration scheme by incorporating the historical iterates of the Q-function. The idea is conceptually ins…
SEE: Syntax-aware Entity Embedding for Neural Relation Extraction
Zhengqiu He, Wenliang Chen, Zhenghua Li +3
Distant supervised relation extraction is an efficient approach to scale relation extraction to very large corpora, and has been widely used to find novel relational facts from pla…