101 citations · 103 across the 4 of their papers we have counts for
4 papers
Learning the Positions in CountSketch
Yi Li, Honghao Lin, Simin Liu +2
We consider sketching algorithms which first compress data by multiplication with a random sketch matrix, and then apply the sketch to quickly solve an optimization problem, e.g.,…
Overview of FPGA deep learning acceleration based on convolutional neural network
Simin Liu
In recent years, deep learning has become more and more mature, and as a commonly used algorithm in deep learning, convolutional neural networks have been widely used in various vi…
Learning the Positions in CountSketch
Simin Liu, Tianrui Liu, Ali Vakilian +2
We consider sketching algorithms which first quickly compress data by multiplication with a random sketch matrix, and then apply the sketch to quickly solve an optimization problem…
Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning
Anusha Nagabandi, Ignasi Clavera, Simin Liu +4
Although reinforcement learning methods can achieve impressive results in simulation, the real world presents two major challenges: generating samples is exceedingly expensive, and…