6 citations · 6 across the 1 of their papers we have counts for
5 papers
On Statistical Efficiency in Learning
Jie Ding, Enmao Diao, Jiawei Zhou +1
A central issue of many statistical learning problems is to select an appropriate model from a set of candidate models. Large models tend to inflate the variance (or overfitting),…
Deep Clustering of Compressed Variational Embeddings
Suya Wu, Enmao Diao, Jie Ding +1
Motivated by the ever-increasing demands for limited communication bandwidth and low-power consumption, we propose a new methodology, named joint Variational Autoencoders with Bern…
Speech Emotion Recognition with Dual-Sequence LSTM Architecture
Jianyou Wang, Michael Xue, Ryan Culhane +3
Speech Emotion Recognition (SER) has emerged as a critical component of the next generation human-machine interfacing technologies. In this work, we propose a new dual-level model…
Restricted Recurrent Neural Networks
Enmao Diao, Jie Ding, Vahid Tarokh
Recurrent Neural Network (RNN) and its variations such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), have become standard building blocks for learning online dat…
DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression
Enmao Diao, Jie Ding, Vahid Tarokh
We propose a new architecture for distributed image compression from a group of distributed data sources. The work is motivated by practical needs of data-driven codec design, low…