Yishu Miao

Neural Variational Inference for Text Processing

2015 · arXiv (Cornell University)

Recent advances in neural variational inference have spawned a renaissance in deep latent variable models. In this paper we introduce a generic variational inference framework for generative and conditional models of text. While traditional variational …

Hybrid Deep-Semantic Matrix Factorization for Tag-Aware Personalized Recommendation

2017 · arXiv (Cornell University)

Matrix factorization has now become a dominant solution for personalized recommendation on the Social Web. To alleviate the cold start problem, previous approaches have incorporated various additional sources of information into traditional matrix factorization models. …

Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling

2016

With the rapid growth of social tagging systems, many efforts have been put on tag-aware personalized recommendation. However, due to uncontrolled vocabularies, social tags are usually redundant, sparse, and ambiguous. In this paper, we propose …

Discovering Discrete Latent Topics with Neural Variational Inference

2017 · arXiv (Cornell University)

Topic models have been widely explored as probabilistic generative models of documents. Traditional inference methods have sought closed-form derivations for updating the models, however as the expressiveness of these models grows, so does the difficulty …