339 citations · 2.5k across the 73 of their papers we have counts for
8 papers · 1 filter
Distributed Stochastic Consensus Optimization with Momentum for Nonconvex Nonsmooth Problems
Zhiguo Wang, Jiawei Zhang, Tsung-Hui Chang +2
While many distributed optimization algorithms have been proposed for solving smooth or convex problems over the networks, few of them can handle non-convex and non-smooth problems…
Transfer Learning and Meta Learning Based Fast Downlink Beamforming Adaptation
Yi Yuan, Gan Zheng, Kai-Kit Wong +2
This paper studies fast adaptive beamforming optimization for the signal-to-interference-plus-noise ratio balancing problem in a multiuser multiple-input single-output downlink sys…
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…
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
Jiawei Zhang, Peijun Xiao, Ruoyu Sun +1
Nonconvex-concave min-max problem arises in many machine learning applications including minimizing a pointwise maximum of a set of nonconvex functions and robust adversarial train…
Improved RIP-Based Bounds for Guaranteed Performance of two Compressed Sensing Algorithms
Yun-Bin Zhao, Zhi-Quan Luo
Iterative hard thresholding (IHT) and compressive sampling matching pursuit (CoSaMP) are two types of mainstream compressed sensing algorithms using hard thresholding operators for…
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…