122 citations · 253 across the 11 of their papers we have counts for
5 papers · 1 filter
Earliness-Aware Deep Convolutional Networks for Early Time Series Classification
Wenlin Wang, Changyou Chen, Wenqi Wang +2
We present Earliness-Aware Deep Convolutional Networks (EA-ConvNets), an end-to-end deep learning framework, for early classification of time series data. Unlike most existing meth…
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Changyou Chen, Nan Ding, Lawrence Carin
Recent advances in Bayesian learning with large-scale data have witnessed emergence of stochastic gradient MCMC algorithms (SG-MCMC), such as stochastic gradient Langevin dynamics…
Stochastic Gradient MCMC with Stale Gradients
Changyou Chen, Nan Ding, Chunyuan Li +2
Stochastic gradient MCMC (SG-MCMC) has played an important role in large-scale Bayesian learning, with well-developed theoretical convergence properties. In such applications of SG…
Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling
Kar Wai Lim, Changyou Chen, Wray Buntine
Twitter data is extremely noisy -- each tweet is short, unstructured and with informal language, a challenge for current topic modeling. On the other hand, tweets are accompanied b…
Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes
Kar Wai Lim, Wray Buntine, Changyou Chen +1
The Dirichlet process and its extension, the Pitman-Yor process, are stochastic processes that take probability distributions as a parameter. These processes can be stacked up to f…