P. Simard

Learning long-term dependencies with gradient descent is difficult

Yoshua Bengio, P. Simard, Paolo Frasconi · IEEE Transactions on Neural Networks · 1994 · 8.3K citations

Structured Prediction, Gradient Descent, Engineering +11

Best practices for convolutional neural networks applied to visual document analysis

P. Simard, Don Steinkraus, John Platt · 2005 · 2.8K citations

Convolutional Neural Network, Engineering, Machine Learning +18

Comparison of classifier methods: a case study in handwritten digit recognition

Léon Bottou, Corinna Cortes, J. S. Denker et al. · 2002 · 620 citations

Engineering, Machine Learning, Standard Database +21

The problem of learning long-term dependencies in recurrent networks

Yoshua Bengio, Paolo Frasconi, P. Simard · IEEE International Conference on Neural Networks · 2002 · 235 citations

Natural Language Processing, Deep Neural Networks, Gradient Descent +15

Using GPUs for machine learning algorithms

Don Steinkraus, Ian Buck, P. Simard · 2005 · 233 citations

Engineering, Machine Learning, Machine Learning Algorithms +17