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CoRL 2020, Spotlight Talk 440: Reactive motion planning with probabilisticsafety guarantees

“**Reactive motion planning with probabilisticsafety guarantees** Yuxiao Chen (California Institute of Technology)*; Ugo Rosolia (California Institute of Technology); Chuchu Fan (MIT); Aaron Ames (Caltech); Richard Murray (California Institute of Technology) Publication: http://corlconf.github.io/paper_440/ **Abstract** Motion planning in environments with multiple agents is critical to many important autonomous applications such as autonomous vehicles and assistive robots. This […]
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CoRL 2020, Spotlight Talk 140: Guaranteeing Safety of Learned Perception Modules via Measurement-…

“**Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions** Sarah Dean (UC Berkeley)*; Andrew Taylor (Caltech); Ryan Cosner (Caltech); Benjamin Recht (UC Berkeley); Aaron Ames (Caltech) Publication: http://corlconf.github.io/paper_140/ **Abstract** Modern nonlinear control theory seeks to develop feedback controllers that endow systems with properties such as safety and stability. The guarantees ensured by these […]
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Neural Networks Demystified [Part 7: Overfitting, Testing, and Regularization]

We’ve built and trained our neural network, but before we celebrate, we must be sure that our model is representative of the real world. Supporting Code: https://github.com/stephencwelch/Neural-Networks-Demystified Nate Silver’s Book: http://www.amazon.com/Signal-Noise-Many-Predictions-Fail/dp/159420411X/ref=sr_1_1?ie=UTF8&qid=1421442340&sr=8-1&keywords=signal+and+the+noise Caltech Machine Learning Course: https://work.caltech.edu/telecourse.html And the lecture shown: http://youtu.be/Dc0sr0kdBVI?t=56m52s In this series, we will build and train a complete Artificial Neural Network in […]
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15:43

Quantum Singular Value Transformation (Quantum Summer Symposium 2020)

András Gilyén of Caltech talks about Quantum Singular Value Transformation, a unified framework of quantum algorithms. This presentation was recorded on Day 2 of Google’s Quantum Summer Symposium 2020 (July 23, 2020). Google’s Quantum Summer Symposium 2020 playlist → https://goo.gle/2Z149sN Subscribe to TensorFlow → https://goo.gle/TensorFlow Source of this TensorFlow AI Video
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42:21

DeepLearning.AI Learner Community Event ft. Jan Jitse Venselaar

deeplearning.ai presents virtual mini-event series for our Learner Community of those taking the AI for Medicine specialization! #MeetYourMentor: Mentors sharing their personal experiences of breaking into AI #DeepDive: A deep dive into a specific area that the guest speaker is working on and more! This event will be from 10am to 10:30 am on May […]
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52:00

Trends in Machine Learning with Anima Anandkumar – TWiML Talk #215

In this episode of our AI Rewind series, we’re back with Anima Anandkumar, Bren Professor at Caltech and now Director of Machine Learning Research at NVIDIA. Anima joins us to discuss her take on trends in the broader Machine Learning field in 2018 and beyond. In our conversation, we cover not only technical breakthroughs in […]
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01:30:05

PyTorch Developer Conference 2018: Cloud & Academia Sessions

Watch sessions from our PyTorch Developer Conference featuring the PyTorch community, including cloud partners, Amazon, Microsoft, and Google, along with applied research in academia with Caltech, Cornell University, UC Berkeley, and more. Learn more at pytorch.org. Source of this PyTorch AI Video
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36:04

Anima Anandkumar Interview – Tensor Operations for Machine Learning

In this episode of our TrainAI series, I sit down with Anima Anandkumar, Bren Professor at Caltech and Principal Scientist with Amazon Web Services. Anima joined me to discuss the research coming out of her “Tensorlab” at CalTech. In our conversation, we review the application of tensor operations to machine learning and discuss how an […]
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38:39

David Van Valen Interview – Deep Learning for Live-Cell Imaging

In today’s show, I sit down with David Van Valen, assistant professor of Bioengineering & Biology at Caltech. David joined me after his talk at the Figure Eight TrainAI conference to chat about his research using image recognition and segmentation techniques in biological settings. In particular, we discuss his use of deep learning to automate […]
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09:38

PyTorch in Robotics – Yisong Yue, Caltech

Learn about the research work at Caltech focused on risk aware machine learning for dynamic robotics control, and how PyTorch is being used to build deep learning systems for projects like the neural lander. Source of this PyTorch AI Video
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03:45

Using deep learning and PyTorch to power next gen aircraft at Caltech

Learn how Caltech’s Center for Autonomous Systems and Technologies (CAST) uses PyTorch to build deep learning systems that can understand the aerodynamics of how aircrafts interact with the ground to enable much smoother and safer landings. Read more about the neural lander project here: http://bit.ly/2NHEL6c Source of this PyTorch AI Video
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04:52:07

PyTorch Developer Conference 2019 | Full Livestream

Watch the full set of talks from the 2019 PyTorch Developer Conference. Deep dive on PyTorch 1.3 and new tools and libraries including PyTorch Mobile, CrypTen, Captum, Detectron2 and more. Hear from AI researchers and engineers from leading organizations in academia and industry on how they’re using PyTorch for both cutting edge research and production. […]
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01:09:28

Lecture 18 – Epilogue

Epilogue – The map of machine learning. Brief views of Bayesian learning and aggregation methods. Lecture 18 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App – https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website – http://work.caltech.edu/telecourse.html Produced in association with Caltech Academic Media […]
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01:16:18

Lecture 17 – Three Learning Principles

Three Learning Principles – Major pitfalls for machine learning practitioners; Occam’s razor, sampling bias, and data snooping. Lecture 17 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App – https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website – http://work.caltech.edu/telecourse.html Produced in association with Caltech […]
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01:22:08

Lecture 16 – Radial Basis Functions

Radial Basis Functions – An important learning model that connects several machine learning models and techniques. Lecture 16 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App – https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website – http://work.caltech.edu/telecourse.html Produced in association with Caltech Academic […]
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01:13:23

Lecture 16: A Framework for Consciousness

Lecture 16 corresponds to Chapter 19 of “The Quest for Consciousness – A Neurobiological Approach,” by Christof Koch. Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/ YouTube Source for this AI Video
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01:18:19

Lecture 15 – Kernel Methods

Kernel Methods – Extending SVM to infinite-dimensional spaces using the kernel trick, and to non-separable data using soft margins. Lecture 15 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App – https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website – http://work.caltech.edu/telecourse.html Produced in association […]
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39:02

Lecture 15: Splitting the Brain

Lecture 15 corresponds to Chapter 17 of “The Quest for Consciousness – A Neurobiological Approach,” by Christof Koch. Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/ YouTube Source for this AI Video
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01:14:16

Lecture 14 – Support Vector Machines

Support Vector Machines – One of the most successful learning algorithms; getting a complex model at the price of a simple one. Lecture 14 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App – https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website – http://work.caltech.edu/telecourse.html […]
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01:02:41

Lecture 14: When the Mind Flips

Lecture 14 corresponds to Chapter 16 of “The Quest for Consciousness – A Neurobiological Approach,” by Christof Koch. Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/ YouTube Source for this AI Video
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01:26:12

Lecture 13 – Validation

Validation – Taking a peek out of sample. Model selection and data contamination. Cross validation. Lecture 13 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App – https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website – http://work.caltech.edu/telecourse.html Produced in association with Caltech Academic Media […]
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01:05:42

Lecture 13: On Time and Consciousness

Lecture 13 corresponds to Chapter 15 of “The Quest for Consciousness – A Neurobiological Approach,” by Christof Koch. Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/ YouTube Source for this AI Video