We are interested in developing new algorithms for large-scale machine learning problems. Currently, we are particularly interested in the following topics:

Adversarial deep learning

Model compression and fast prediction

Fast (parallel) training

Large-scale recommender systems, ranking, active learning

Besides, we are also interested in general machine learning problems such as GAN, reinforcement learning, learning to learn, and learning word/graph embeddings.