23 citations · 29 across the 3 of their papers we have counts for
3 papers
cs.CV2020★ 23 cited
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation
Sicheng Zhao, Xiangyu Yue, Shanghang Zhang +8
Large-scale labeled training datasets have enabled deep neural networks to excel across a wide range of benchmark vision tasks. However, in many applications, it is prohibitively e…
cs.AR2020★ 2 cited
Accelerating Recommender Systems via Hardware "scale-in"
Suresh Krishna, Ravi Krishna
In today's era of "scale-out", this paper makes the case that a specialized hardware architecture based on "scale-in"--placing as many specialized processors as possible along with…
cs.CL2020★ 4 cited
SqueezeBERT: What can computer vision teach NLP about efficient neural networks?
Forrest N. Iandola, Albert E. Shaw, Ravi Krishna +1
Humans read and write hundreds of billions of messages every day. Further, due to the availability of large datasets, large computing systems, and better neural network models, nat…