Improving medical predictions by caring about uncertainty: Combining Deep Neural Networks with Bayesian methodology
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Improving medical predictions by caring about uncertainty: Combining Deep Neural Networks with Bayesian methodology

Room 116

Details of Improving medical predictions by caring about uncertainty: Combining Deep Neural Networks with Bayesian methodology
How To Beat Empirical Risk Minimization
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How To Beat Empirical Risk Minimization

Room 116

Details of How To Beat Empirical Risk Minimization
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences
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Robust Bi-Tempered Logistic Loss Based on Bregman Divergences

Room 116

Details of Robust Bi-Tempered Logistic Loss Based on Bregman Divergences
Private Deep Learning
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Private Deep Learning

Room 116

Details of Private Deep Learning
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
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Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks

Room 116

Details of Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
Reducing AI Bias using Truncated Statistics
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Reducing AI Bias using Truncated Statistics

Room 116

Details of Reducing AI Bias using Truncated Statistics
Memory, Modularity, and the Theory of Deep Learnability
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Memory, Modularity, and the Theory of Deep Learnability

Room 116

Details of Memory, Modularity, and the Theory of Deep Learnability
Frontiers of Efficient Neural-Network Learnability
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Frontiers of Efficient Neural-Network Learnability

Room 116

Details of Frontiers of Efficient Neural-Network Learnability
The singular values of convolutional layers
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The singular values of convolutional layers

Room 116

Details of The singular values of convolutional layers
A New Perspective on Adversarial Perturbations
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A New Perspective on Adversarial Perturbations

116 Calvin Lab

Details of A New Perspective on Adversarial Perturbations