1.1k citations · 3k across the 8 of their papers we have counts for
8 papers
Semantic Redundancies in Image-Classification Datasets: The 10% You Don't Need
Vighnesh Birodkar, Hossein Mobahi, Samy Bengio
Large datasets have been crucial to the success of deep learning models in the recent years, which keep performing better as they are trained with more labelled data. While there h…
Neural Combinatorial Optimization with Reinforcement Learning
Irwan Bello, Hieu Pham, Quoc V. Le +2
This paper presents a framework to tackle combinatorial optimization problems using neural networks and reinforcement learning. We focus on the traveling salesman problem (TSP) and…
Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt +2
Despite their massive size, successful deep artificial neural networks can exhibit a remarkably small difference between training and test performance. Conventional wisdom attribut…
Adversarial Machine Learning at Scale
Alexey Kurakin, Ian Goodfellow, Samy Bengio
Adversarial examples are malicious inputs designed to fool machine learning models. They often transfer from one model to another, allowing attackers to mount black box attacks wit…
Can Active Memory Replace Attention?
Łukasz Kaiser, Samy Bengio
Several mechanisms to focus attention of a neural network on selected parts of its input or memory have been used successfully in deep learning models in recent years. Attention ha…
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
Oriol Vinyals, Alexander Toshev, Samy Bengio +1
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In this paper, w…