activity
20142023
most citedOn Learning Invariant Representation for Domain Adaptation

156 citations · 362 across the 22 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

physics.optics2022★ 1 cited

Electro-optic transduction in silicon via GHz-frequency nanomechanics

Han Zhao, Alkim Bozkurt, Mohammad Mirhosseini

Interfacing electronics with optical fiber networks is key to the long-distance transfer of classical and quantum information. Piezo-optomechanical transducers enable such interfac…

cs.CV2022★ 11 cited

Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery

Ruikang Luo, Yaofeng Song, Han Zhao +5

Accurate vehicle type classification serves a significant role in the intelligent transportation system. It is critical for ruler to understand the road conditions and usually cont…

math.NA2022★ 22 cited

Interpolation-based immersed finite element and isogeometric analysis

Jennifer E. Fromm, Nils Wunsch, Ru Xiang +4

We introduce a new paradigm for immersed finite element and isogeometric methods based on interpolating function spaces from an unfitted background mesh into Lagrange finite elemen…

cs.CR2022

Application of Data Encryption in Chinese Named Entity Recognition

Kaifang Long, Jikun Dong, Shengyu Fan +5

Recently, with the continuous development of deep learning, the performance of named entity recognition tasks has been dramatically improved. However, the privacy and the confident…

quant-ph2022★ 3 cited

A quantum electromechanical interface for long-lived phonons

Alkim Bozkurt, Han Zhao, Chaitali Joshi +3

Controlling long-lived mechanical oscillators in the quantum regime holds promises for quantum information processing. Here, we present an electromechanical system capable of opera…

cs.LG2022★ 1 cited

Algorithms and Theory for Supervised Gradual Domain Adaptation

Jing Dong, Shiji Zhou, Baoxiang Wang +1

The phenomenon of data distribution evolving over time has been observed in a range of applications, calling the needs of adaptive learning algorithms. We thus study the problem of…