output
20182020
most citedHow Bad Can a Bug Get? An Empirical Analysis of Software Failures in the OpenStack Cloud Computing Platform

80 citations

12 papers

cs.AR2020

Combinatorics and Geometry for the Many-ported, Distributed and Shared Memory Architecture

Hao Luan, Alan Gatherer

Manycore SoC architectures based on on-chip shared memory are preferred for flexible and programmable solutions in many application domains. However, the development of many ported…

eess.SP2020★ 7 cited

Reconfigurable Intelligent Surface: Design the Channel -- a New Opportunity for Future Wireless Networks

Miguel Dajer, Zhengxiang Ma, Leonard Piazzi +5

In this paper, we survey state-of-the-art research outcomes in the burgeoning field of reconfigurable intelligent surface (RIS) in view of its potential for significant performance…

eess.AS2020★ 18 cited

improving partition-block-based acoustic echo canceler in under-modeling scenarios

Wenzhi Fan, Jing Lu

Recently, a partitioned-block-based frequency-domain Kalman filter (PFKF) has been proposed for acoustic echo cancellation. Compared with the normal frequency-domain Kalman filter,…

cs.CV2020★ 1 cited

K-Shot Contrastive Learning of Visual Features with Multiple Instance Augmentations

Haohang Xu, Hongkai Xiong, Guo-Jun Qi

In this paper, we propose the -Shot Contrastive Learning (KSCL) of visual features by applying multiple augmentations to investigate the sample variations within individual inst…

cs.LG2019★ 7 cited

TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning

Zhongjie Yu, Lin Chen, Zhongwei Cheng +1

The successful application of deep learning to many visual recognition tasks relies heavily on the availability of a large amount of labeled data which is usually expensive to obta…

cs.CV2019★ 15 cited

EnAET: A Self-Trained framework for Semi-Supervised and Supervised Learning with Ensemble Transformations

Xiao Wang, Daisuke Kihara, Jiebo Luo +1

Deep neural networks have been successfully applied to many real-world applications. However, such successes rely heavily on large amounts of labeled data that is expensive to obta…