215 citations · 531 across the 19 of their papers we have counts for
6 papers · 1 filter
Exploiting Multimodal Reinforcement Learning for Simultaneous Machine Translation
Julia Ive, Andy Mingren Li, Yishu Miao +3
This paper addresses the problem of simultaneous machine translation (SiMT) by exploring two main concepts: (a) adaptive policies to learn a good trade-off between high translation…
Discovering Discrete Latent Topics with Neural Variational Inference
Yishu Miao, Edward Grefenstette, Phil Blunsom
Topic models have been widely explored as probabilistic generative models of documents. Traditional inference methods have sought closed-form derivations for updating the models, h…
Latent Intention Dialogue Models
Tsung-Hsien Wen, Yishu Miao, Phil Blunsom +1
Developing a dialogue agent that is capable of making autonomous decisions and communicating by natural language is one of the long-term goals of machine learning research. Traditi…
Language as a Latent Variable: Discrete Generative Models for Sentence Compression
Yishu Miao, Phil Blunsom
In this work we explore deep generative models of text in which the latent representation of a document is itself drawn from a discrete language model distribution. We formulate a…
Neural Variational Inference for Text Processing
Yishu Miao, Lei Yu, Phil Blunsom
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…
Bayesian Optimisation for Machine Translation
Yishu Miao, Ziyu Wang, Phil Blunsom
This paper presents novel Bayesian optimisation algorithms for minimum error rate training of statistical machine translation systems. We explore two classes of algorithms for effi…