Geoffrey E. Hinton

Research topics

• Domain Adaptation and Few-Shot Learning · 2 papers
• Neural Networks and Applications · 2 papers
• Advanced Neural Network Applications · 1 paper
• Advanced Image Processing Techniques · 1 paper
• Model Reduction and Neural Networks · 1 paper
• Image and Signal Denoising Methods · 1 paper

Frequent co-authors

• Alex Krizhevsky · 1 paper
• Ilya Sutskever · 1 paper
• Ruslan Salakhutdinov · 1 paper
• Simon Osindero · 1 paper
• Yee‐Whye Teh · 1 paper

Papers

1. ImageNet classification with deep convolutional neural networksCommunications of the ACM · 2017 · 109,548 citations

   We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0%,…

2. Reducing the Dimensionality of Data with Neural NetworksScience · 2006 · 21,380 citations

   High-dimensional data can be converted to low-dimensional codes by training a multilayer neural network with a small central layer to reconstruct high-dimensional input vectors. Gradient descent can be used for fine-tuning the weights in such "autoencoder" networks, but this works…

3. A Fast Learning Algorithm for Deep Belief NetsNeural Computation · 2006 · 16,600 citations

   We show how to use "complementary priors" to eliminate the explaining-away effects that make inference difficult in densely connected belief nets that have many hidden layers. Using complementary priors, we derive a fast, greedy algorithm that can learn deep, directed…