I am now a postdoctoral research associate in Stats-Lab, Department of Pure Math and Mathematical Statistics, University of Cambridge. I am co-supervised by Prof. John Aston and Dr. Carola-Bibiane Schönlieb. I achieved my PhD degree in Computer Science from University of Cambridge, UK in 2016, supervised by Dr. Ian Wassell.
My research mainly focuses on machine learning topics. Specifically, I actively research with variational Bayesian inference, deep learning, generative models, and sparsity learning.
During my PhD, I was extremingly keen in investigating the mysterious Bayesian algorithms by bridging them with the underlying closed form optimization formulations. I believe by understanding these hidden connections, boosting the model towards more successful inference and regression is possible. My research also pays much emphasis on sparsity and low rank driven machine learning phenomenon. Based on my research, I developed novel efficient statistical Bayesian models for clustering, recognition, classification and generative tasks.
One of my favorite work was to successfully derive the closed form sparsity driven cost function hidden behind the hierarchical statistical clustering techniques (published in ICML 2015). My latest (UAI 2017) work introduces deep recurrent network into the Variational auto encoder (VAE), which enables to recycle the dirty data (See the paper for what I mean)!
Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders
Yu Wang, Bin Dai, Gang Hua, John Aston, David Wipf
Uncertainty of Artifical Intellegnece (UAI), August, 2017
Sparse Bayesian Multitask Learning for Subspace Segmentation
Yu Wang, David Wipf, Jonh Aston
CVPR 2017 WiCV (Workshop short paper). July 2017
Structured sparsity learning -- Taming the sparsity under structure
University of Cambridge Technical Report, August, 2016
Simultaneous Bayesian Sparse Approximation With Structured Sparse Models
Wei Chen, David Wipf, Yu Wang, Yang Liu, Ian Wassell
IEEE Transactions on Signal Processing (TSP), Dec 2016
Clustered Sparse Bayesian Learning
Yu Wang, David Wipf, Jeong Min Yun, Wei Chen, Ian J. Wassell
The Conference on Uncertainty in Artificial Intelligence (UAI), Jul 2015
Multi-Task Learning for Subspace Segmentation
Yu Wang, David Wipf, Qing Ling, Wei Chen, Ian Wassell
International Conference on Machine Learning (ICML), Jul 2015
Exploiting the Convex-Concave Penalty for Tracking: A Novel Dynamic Reweighted Sparse Bayesian Learning Algorithm
Yu Wang, David Wipf, Wei Chen, Ian Wassell
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2014
Exploiting Hidden Block Sparsity: Interdependent Matching Pursuit for Cyclic Feature Detection
Yu Wang, Wei Chen, Ian Wassell
IEEE Global Communications Conference (GLOBECOM), Dec 2013