activity
20182021
most citedMemory-efficient training with streaming dimensionality reduction

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2021

Computing and Memory Technologies based on Magnetic Skyrmions

Hamed Vakili, Wei Zhou, Chung T Ma +13

Solitonic magnetic excitations such as domain walls and, specifically, skyrmionics enable the possibility of compact, high density, ultrafast,all-electronic, low-energy devices, wh…

cs.LG20202 cited

Memory-efficient training with streaming dimensionality reduction

Siyuan Huang, Brian D. Hoskins, Matthew W. Daniels +2

The movement of large quantities of data during the training of a Deep Neural Network presents immense challenges for machine learning workloads. To minimize this overhead, especia…

cs.LG2019

Streaming Batch Eigenupdates for Hardware Neuromorphic Networks

Brian D. Hoskins, Matthew W. Daniels, Siyuan Huang +5

Neuromorphic networks based on nanodevices, such as metal oxide memristors, phase change memories, and flash memory cells, have generated considerable interest for their increased…

cs.ET2018

A scalable method to find the shortest path in a graph with circuits of memristors

Alice Mizrahi, Thomas Marsh, Brian Hoskins +1

Finding the shortest path in a graph has applications to a wide range of optimization problems. However, algorithmic methods scale with the size of the graph in terms of time and e…

cond-mat.mtrl-sci2018

In aqua electrochemistry probed by XPEEM: experimental setup, examples, and challenges

Slavomír Nemšák, Evgheni Strelcov, Hongxuan Guo +8

Recent developments in environmental and liquid cells equipped with electron transparent graphene windows have enabled traditional surface science spectromicroscopy tools, such as…