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20162026
most citedHardware for Machine Learning: Challenges and Opportunities

192 citations · 638 across the 26 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV2019★ 3 cited

Design Considerations for Efficient Deep Neural Networks on Processing-in-Memory Accelerators

Tien-Ju Yang, Vivienne Sze

This paper describes various design considerations for deep neural networks that enable them to operate efficiently and accurately on processing-in-memory accelerators. We highligh…

cs.RO2019★ 4 cited

FSMI: Fast computation of Shannon Mutual Information for information-theoretic mapping

Zhengdong Zhang, Trevor Henderson, Sertac Karaman +1

Exploration tasks are embedded in many robotics applications, such as search and rescue and space exploration. Information-based exploration algorithms aim to find the most informa…

cs.LG2019★ 20 cited

MLSys: The New Frontier of Machine Learning Systems

Alexander Ratner, Dan Alistarh, Gustavo Alonso +66

Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…

cs.CV2019★ 163 cited

DeeperLab: Single-Shot Image Parser

Tien-Ju Yang, Maxwell D. Collins, Yukun Zhu +6

We present a single-shot, bottom-up approach for whole image parsing. Whole image parsing, also known as Panoptic Segmentation, generalizes the tasks of semantic segmentation for '…

cs.CV2019

FastDepth: Fast Monocular Depth Estimation on Embedded Systems

Diana Wofk, Fangchang Ma, Tien-Ju Yang +2

Depth sensing is a critical function for robotic tasks such as localization, mapping and obstacle detection. There has been a significant and growing interest in depth estimation f…