14.1k citations · 89.2k across the 108 of their papers we have counts for
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Towards Principled Unsupervised Learning
Ilya Sutskever, Rafal Jozefowicz, Karol Gregor +3
General unsupervised learning is a long-standing conceptual problem in machine learning. Supervised learning is successful because it can be solved by the minimization of the train…
Multilingual Language Processing From Bytes
Dan Gillick, Cliff Brunk, Oriol Vinyals +1
We describe an LSTM-based model which we call Byte-to-Span (BTS) that reads text as bytes and outputs span annotations of the form [start, length, label] where start positions, len…
Order Matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, Manjunath Kudlur
Sequences have become first class citizens in supervised learning thanks to the resurgence of recurrent neural networks. Many complex tasks that require mapping from or to a sequen…
Generating Sentences from a Continuous Space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals +3
The standard recurrent neural network language model (RNNLM) generates sentences one word at a time and does not work from an explicit global sentence representation. In this work,…
Multi-task Sequence to Sequence Learning
Minh-Thang Luong, Quoc V. Le, Ilya Sutskever +2
Sequence to sequence learning has recently emerged as a new paradigm in supervised learning. To date, most of its applications focused on only one task and not much work explored t…
A Neural Transducer
Navdeep Jaitly, David Sussillo, Quoc V. Le +3
Sequence-to-sequence models have achieved impressive results on various tasks. However, they are unsuitable for tasks that require incremental predictions to be made as more data a…