51 citations · 77 across the 20 of their papers we have counts for
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eess.SP2020
Pushing The Limit of Type I Codebook For FDD Massive MIMO Beamforming: A Channel Covariance Reconstruction Approach
Kai Li, Ying Li, Lei Cheng +2
There is a fundamental trade-off between the channel representation resolution of codebooks and the overheads of feedback communications in the fifth generation new radio (5G NR) f…
cs.LG2020
Towards Flexible Sparsity-Aware Modeling: Automatic Tensor Rank Learning Using The Generalized Hyperbolic Prior
Lei Cheng, Zhongtao Chen, Qingjiang Shi +2
Tensor rank learning for canonical polyadic decomposition (CPD) has long been deemed as an essential yet challenging problem. In particular, since the tensor rank controls the comp…
cs.LG2020★ 2 cited
Optimally Combining Classifiers for Semi-Supervised Learning
Zhiguo Wang, Liusha Yang, Feng Yin +3
This paper considers semi-supervised learning for tabular data. It is widely known that Xgboost based on tree model works well on the heterogeneous features while transductive supp…