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Author Information
Benjamin Sapp (Stanford University)
Stephen Gould (ANU)
Adrian Kaehler (Giant.AI, Inc.)
Dr. Adrian Kaehler is a recognized expert and inventor in numerous advanced technology domains. Throughout his career, his primary focus has been on intellectual and practical leadership for complex technology innovation efforts for both privately or publicly held companies and enterprises, as well as for the many commercial and government institutions he advises. At this time, Adrian is a start-up founder and entrepreneur in Silicon Valley He holds a Ph.D. degree in theoretical particle physics from Columbia University which, after enrolling in university at the age of 14 and graduating with a bachelor's degree at 18, he received at the age of 25. His fields of expertise include robotics, deep learning, artificial intelligence, machine learning, physics, electrical engineering, computer algorithms, machine vision, biometrics, computer games, system engineering, human machine interface, numerical programming, and design. He is the author of numerous papers and over 30 patents in these and other subjects, as well as two a best-selling books on computer vision.
Gary R Bradski (OpenCV)
Andrew Y Ng (DeepLearning.AI)
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2023 Poster: Revisiting Implicit Differentiation for Learning Problems in Optimal Control »
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2022 Spotlight: Lightning Talks 6B-2 »
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2022 Spotlight: On the Strong Correlation Between Model Invariance and Generalization »
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2022 Poster: On the Strong Correlation Between Model Invariance and Generalization »
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2021 Poster: Rethinking conditional GAN training: An approach using geometrically structured latent manifolds »
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2020 Poster: Language and Visual Entity Relationship Graph for Agent Navigation »
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2018 Poster: Partially-Supervised Image Captioning »
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2015 Symposium: Deep Learning Symposium »
Yoshua Bengio · Marc'Aurelio Ranzato · Honglak Lee · Max Welling · Andrew Y Ng -
2014 Workshop: Deep Learning and Representation Learning »
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2013 Demonstration: Easy Text Classification with Machine Learning »
Richard Socher · Romain Paulus · Bryan McCann · Andrew Y Ng -
2013 Poster: Reasoning With Neural Tensor Networks for Knowledge Base Completion »
Richard Socher · Danqi Chen · Christopher D Manning · Andrew Y Ng -
2013 Poster: Zero-Shot Learning Through Cross-Modal Transfer »
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2012 Poster: Recursive Deep Learning on 3D Point Clouds »
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2012 Poster: Deep Learning of invariant features via tracked video sequences »
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2012 Poster: Large Scale Distributed Deep Networks »
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2012 Poster: Emergence of Object-Selective Features in Unsupervised Feature Learning »
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2011 Workshop: Challenges in Learning Hierarchical Models: Transfer Learning and Optimization »
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2011 Workshop: Deep Learning and Unsupervised Feature Learning »
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2011 Poster: ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning »
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2011 Poster: Unfolding Recursive Autoencoders for Paraphrase Detection »
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2011 Poster: Sparse Filtering »
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2011 Spotlight: Sparse Filtering »
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2011 Demonstration: Haptic Belt with Pedestrian Detection »
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2009 Mini Symposium: Machine Learning for Sustainability »
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2008 Oral: Cascaded Classification Models: Combining Models for Holistic Scene Understanding »
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2008 Poster: Cascaded Classification Models: Combining Models for Holistic Scene Understanding »
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2007 Poster: Efficient multiple hyperparameter learning for log-linear models »
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