Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Lukasz Kaiser is active.

Publication


Featured researches published by Lukasz Kaiser.


empirical methods in natural language processing | 2015

Sentence Compression by Deletion with LSTMs

Katja Filippova; Enrique Alfonseca; Carlos A. Colmenares; Lukasz Kaiser; Oriol Vinyals

We present an LSTM approach to deletion-based sentence compression where the task is to translate a sentence into a sequence of zeros and ones, corresponding to token deletion decisions. We demonstrate that even the most basic version of the system, which is given no syntactic information (no PoS or NE tags, or dependencies) or desired compression length, performs surprisingly well: around 30% of the compressions from a large test set could be regenerated. We compare the LSTM system with a competitive baseline which is trained on the same amount of data but is additionally provided with all kinds of linguistic features. In an experiment with human raters the LSTMbased model outperforms the baseline achieving 4.5 in readability and 3.8 in informativeness.


arXiv: Distributed, Parallel, and Cluster Computing | 2015

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi; Ashish Agarwal; Paul Barham; Eugene Brevdo; Zhifeng Chen; Craig Citro; Gregory S. Corrado; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Ian J. Goodfellow; Andrew Harp; Geoffrey Irving; Michael Isard; Yangqing Jia; Rafal Jozefowicz; Lukasz Kaiser; Manjunath Kudlur; Josh Levenberg; Dan Mané; Rajat Monga; Sherry Moore; Derek Gordon Murray; Chris Olah; Mike Schuster; Jonathon Shlens; Benoit Steiner; Ilya Sutskever; Kunal Talwar


neural information processing systems | 2015

Grammar as a foreign language

Oriol Vinyals; Lukasz Kaiser; Terry Koo; Slav Petrov; Ilya Sutskever; Geoffrey E. Hinton


international conference on learning representations | 2016

Multi-task Sequence to Sequence Learning

Minh-Thang Luong; Quoc V. Le; Ilya Sutskever; Oriol Vinyals; Lukasz Kaiser


arXiv: Machine Learning | 2017

Adding Gradient Noise Improves Learning for Very Deep Networks

Arvind Neelakantan; Luke Vilnis; Quoc V. Le; Lukasz Kaiser; Karol Kurach; Ilya Sutskever; James Martens


international conference on learning representations | 2017

Learning to Remember Rare Events

Lukasz Kaiser; Ofir Nachum; Aurko Roy; Samy Bengio


arXiv: Neural and Evolutionary Computing | 2017

Regularizing Neural Networks by Penalizing Confident Output Distributions

Gabriel Pereyra; George Tucker; Jan Chorowski; Lukasz Kaiser; Geoffrey E. Hinton


neural information processing systems | 2016

Can Active Memory Replace Attention

Lukasz Kaiser; Samy Bengio


international conference on learning representations | 2018

Depthwise Separable Convolutions for Neural Machine Translation

Lukasz Kaiser; Aidan N. Gomez; François Chollet


Archive | 2016

GENERATING PARSE TREES OF TEXT SEGMENTS USING NEURAL NETWORKS

Oriol Vinyals; Lukasz Kaiser

Collaboration


Dive into the Lukasz Kaiser's collaboration.

Researchain Logo
Decentralizing Knowledge