activity
20182021
most citedToward Trainability of Quantum Neural Networks

44 citations · 44 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation

Ye Huang, Di Kang, Wenjing Jia +2

Spatial and channel attentions, modelling the semantic interdependencies in spatial and channel dimensions respectively, have recently been widely used for semantic segmentation. H…

quant-ph202044 cited

Toward Trainability of Quantum Neural Networks

Kaining Zhang, Min-Hsiu Hsieh, Liu Liu +1

Quantum Neural Networks (QNNs) have been recently proposed as generalizations of classical neural networks to achieve the quantum speed-up. Despite the potential to outperform clas…

cs.RO2020

On the Guaranteed Almost Equivalence between Imitation Learning from Observation and Demonstration

Zhihao Cheng, Liu Liu, Aishan Liu +3

Imitation learning from observation (LfO) is more preferable than imitation learning from demonstration (LfD) due to the nonnecessity of expert actions when reconstructing the expe…

quant-ph2019

Quantum algorithm for finding the negative curvature direction in non-convex optimization

Kaining Zhang, Min-Hsiu Hsieh, Liu Liu +1

We present an efficient quantum algorithm aiming to find the negative curvature direction for escaping the saddle point, which is the critical subroutine for many second-order non-…

math.OC2018

Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient

Liu Liu, Xuanqing Liu, Cho-Jui Hsieh +1

Trust region and cubic regularization methods have demonstrated good performance in small scale non-convex optimization, showing the ability to escape from saddle points. Each iter…