1.6k citations · 11.3k across the 73 of their papers we have counts for
12 papers · 1 filter
Content preserving text generation with attribute controls
Lajanugen Logeswaran, Honglak Lee, Samy Bengio
In this work, we address the problem of modifying textual attributes of sentences. Given an input sentence and a set of attribute labels, we attempt to generate sentences that are…
You Look Twice: GaterNet for Dynamic Filter Selection in CNNs
Zhourong Chen, Yang Li, Samy Bengio +1
The concept of conditional computation for deep nets has been proposed previously to improve model performance by selectively using only parts of the model conditioned on the sampl…
Area Attention
Yang Li, Lukasz Kaiser, Samy Bengio +1
Existing attention mechanisms are trained to attend to individual items in a collection (the memory) with a predefined, fixed granularity, e.g., a word token or an image grid. We p…
Predicting the Generalization Gap in Deep Networks with Margin Distributions
Yiding Jiang, Dilip Krishnan, Hossein Mobahi +1
As shown in recent research, deep neural networks can perfectly fit randomly labeled data, but with very poor accuracy on held out data. This phenomenon indicates that loss functio…
Insights on representational similarity in neural networks with canonical correlation
Ari S. Morcos, Maithra Raghu, Samy Bengio
Comparing different neural network representations and determining how representations evolve over time remain challenging open questions in our understanding of the function of ne…
A Study on Overfitting in Deep Reinforcement Learning
Chiyuan Zhang, Oriol Vinyals, Remi Munos +1
Recent years have witnessed significant progresses in deep Reinforcement Learning (RL). Empowered with large scale neural networks, carefully designed architectures, novel training…
Adversarial Attacks and Defences Competition
Alexey Kurakin, Ian Goodfellow, Samy Bengio +20
To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop…
Tensor2Tensor for Neural Machine Translation
Ashish Vaswani, Samy Bengio, Eugene Brevdo +10
Tensor2Tensor is a library for deep learning models that is well-suited for neural machine translation and includes the reference implementation of the state-of-the-art Transformer…
Predicting Human Performance in Vertical Menu Selection Using Deep Learning
Yang Li, Samy Bengio, Gilles Bailly
Predicting human performance in interaction tasks allows designers or developers to understand the expected performance of a target interface without actually testing it with real…
Large Margin Deep Networks for Classification
Gamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi +2
We present a formulation of deep learning that aims at producing a large margin classifier. The notion of margin, minimum distance to a decision boundary, has served as the foundat…
Fast Decoding in Sequence Models using Discrete Latent Variables
Łukasz Kaiser, Aurko Roy, Ashish Vaswani +4
Autoregressive sequence models based on deep neural networks, such as RNNs, Wavenet and the Transformer attain state-of-the-art results on many tasks. However, they are difficult t…
Discrete Autoencoders for Sequence Models
Łukasz Kaiser, Samy Bengio
Recurrent models for sequences have been recently successful at many tasks, especially for language modeling and machine translation. Nevertheless, it remains challenging to extrac…