449 citations · 996 across the 58 of their papers we have counts for
8 papers · 1 filter
Embedding Bilateral Filter in Least Squares for Efficient Edge-preserving Image Smoothing
Wei Liu, Pingping Zhang, Xiaogang Chen +3
Edge-preserving smoothing is a fundamental procedure for many computer vision and graphic applications. This can be achieved with either local methods or global methods. In most ca…
Hardware-Constrained Millimeter Wave Systems for 5G: Challenges, Opportunities, and Solutions
Xi Yang, Michail Matthaiou, Jie Yang +3
Although millimeter wave (mmWave) systems promise to offer larger bandwidth and unprecedented peak data rates, their practical implementation faces several hardware challenges comp…
Learning Data-adaptive Nonparametric Kernels
Fanghui Liu, Xiaolin Huang, Chen Gong +2
In this paper, we propose a data-adaptive non-parametric kernel learning framework in margin based kernel methods. In model formulation, given an initial kernel matrix, a data-adap…
Adaptive guaranteed-performance consensus design for high-order multiagent systems
Jianxiang Xi, Jie Yang, Hao Liu +1
The current paper addresses the distributed guaranteed-performance consensus design problems for general high-order linear multiagent systems with leaderless and leader-follower st…
Bayesian active learning for choice models with deep Gaussian processes
Jie Yang, Diego Klabjan
In this paper, we propose an active learning algorithm and models which can gradually learn individual's preference through pairwise comparisons. The active learning scheme aims at…
A Low-Resolution ADC Module Assisted Hybrid Beamforming Architecture for mmWave Communications
Jie Yang, Xi Yang, Shi Jin +2
We propose a low-resolution analog-to-digital converter (ADC) module assisted hybrid beamforming architecture for millimeter-wave (mmWave) communications. We prove that the propose…
Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa
Jie Yang, Thomas Drake, Andreas Damianou +1
This paper presents a generic Bayesian framework that enables any deep learning model to actively learn from targeted crowds. Our framework inherits from recent advances in Bayesia…
Edge-Preserving Piecewise Linear Image Smoothing Using Piecewise Constant Filters
Wei Liu, Wei Xu, Xiaogang Chen +3
Most image smoothing filters in the literature assume a piecewise constant model of smoothed output images. However, the piecewise constant model assumption can cause artifacts suc…