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James L. Patton - Deception, ExoNets, SmushWare, and Organic Data: New Frontiers In Neuro-Rehabilitation

Making use of visual display technology and human-robotic interfaces, many researchers have illustrated various opportunities to distort visual and physical realities. We have had success with…

From  Kathryn Gentilello A week ago 3 views 0  

Sam Kean - The Periodic Table: A Treasure Trove of Passion, Adventure, Betrayal, and Obsession

Why did Gandhi hate iodine? Why did the Japanese kill Godzilla with missiles made of cadmium? How did radium nearly ruin Marie Curie’s reputation? And why did tellurium lead to the most bizarre…

From  Kathryn Gentilello A week ago 7 views 0  

Cody Fleming - Safety of Autonomous Systems: Challenges in Coordination, Consistency, and Integration

Recent issues with the Boeing 737-MAX point to challenges in software engineering and the algorithms that the software must implement. However, the 737-MAX is a microcosm of several other problems…

From  Kathryn Gentilello A month ago 9 views 0  

John Baez - Mathematical Mysteries of the Periodic Table

Why do atoms behave the way they do? Why do electrons form “shells,” as seen in the periodic table? Why does the first shell hold 2 electrons, the second 8, and the third 18: twice the…

From  Kathryn Gentilello A month ago 4 views 0  

Leslie Kaelbling - Doing for Our Robots What Nature Did for Us

We, as robot engineers, have to think hard about our role in the design of robots and how it interacts with learning, both in “the factory” (that is, at engineering time) and in…

From  Kathryn Gentilello A month ago 8 views 0  

Johannes Schmidt-Hieber - Mathematics for Deep Neural Networks: Energy landscape and open problems (Lecture 5/5)

To derive a theory for gradient descent methods, it is important to have some understanding of the energy landscape. In this lecture, an overview of existing results is given. The second part of the…

From  Kathryn Gentilello A month ago 19 views 0  

Johannes Schmidt-Hieber - Mathematics for Deep Neural Networks: Statistical theory for deep ReLU networks (Lecture 4/5)

We outline the theory underlying the recent bounds on the estimation risk of deep ReLU networks. In the lecture, we discuss specific properties of the ReLU activation function that relate to skipping…

From  Kathryn Gentilello A month ago 13 views 0  

Cherie R. Kagan - Designer Colloidal Nanocrystal Materials for Electronic and Optical Applications

Semiconductor and plasmonic nanocrystals are known for their size and shape dependent photo-luminescence and localized surface plasmon resonances, respectively. In this talk, I will describe the use…

From  Kathryn Gentilello 2 Months ago 11 views 0  

Johannes Schmidt-Hieber - Mathematics for Deep Neural Networks: Advantages of Additional Layers (Lecture 3/5)

Why are deep networks better than shallow networks? We provide a survey of the existing ideas in the literature. In particular, we discuss localization of deep networks, functions that can be easily…

From  Kathryn Gentilello 2 Months ago 18 views 0  

Johannes Schmidt-Hieber - Mathematics for Deep Neural Networks : Theory for shallow networks (Lecture 2/5)

We start with the universal approximation theorem and discuss several proof strategies that provide some insights into functions that can be easily approximated by shallow networks. Based on this, a…

From  Kathryn Gentilello 2 Months ago 26 views 0  

Fumin Zhang - Mobile Data Collection in an Aquatic Environment: Cyber Maritime Cycles for Distributed Autonomy

There is a perceivable trend for robots to serve as networked mobile sensing platforms that are able to collect data in aquatic environments in unprecedented ways. We argue that the effective…

From  Kathryn Gentilello 2 Months ago 6 views 0  

Michael A. Filler - Celebrating Silicon: Its Success, Hidden History, and Next Act

The history of silicon is usually told as a history of electronic materials and devices. However, it is better told as a history of manufacturing innovation. This talk will take a journey through the…

From  Kathryn Gentilello 2 Months ago 11 views 0  

Johannes Schmidt-Hieber - Mathematics for Deep Neural Networks (Lecture 1/5)

Lecture 1) Survey on neural network structures and deep learning There are many different types of neural networks that differ in complexity and the data types that can be processed. This lecture…

From  Kathryn Gentilello 2 Months ago 47 views 0  

Matthew T. Mason - Robotic Manipulation: A Broadening View

Mason will discuss a rambling mashup of topics in robotic manipulation, manipulation by apes and humans, early research on manipulation in the blocks world, more recent research motivated by…

From  Kathryn Gentilello 2 Months ago 22 views 0  

Galyna Livshyts - A Tight Net with Respect to a Random Matrix Norm and Applications to Estimating Singular Values

In this talk we construct a net around the unit sphere with good properties. We show that with exponentially high probability, the value of |Ax| on the sphere can be approximated well using this net,…

From  Kathryn Gentilello 3 Months ago 6 views 0  

Tuo Zhao - Towards Understanding First Order Algorithms for Nonconvex Optimization in Machine Learning

Stochastic Gradient Descent-type (SGD) algorithms have been widely applied to many non-convex optimization problems in machine learning, e.g., training deep neural networks, variational Bayesian…

From  Kathryn Gentilello 3 Months ago 13 views 0