
This video is part of the A.C.T. Assessment Course developed by the Center for Educational Effectiveness. A.C.T. is a fully asynchronous, selfpaced course open to all UC Davis faculty, instructors,…


ECS036A Lecture 20230517 at 13:07




CeDAR (Center for Data science and Artificial intelligence Research) and UCD4IDS (UC Davis TETRAPODS Institute for Data Science) held their first joint conference in person on Friday, December 2,…




Distributed deep learning (DL) plays a critical role in many wireless Internet of Things (IoT) applications including remote camera deployment. This work addresses three practical challenges in…


Review of strings and languages. Closing a set of languages using some operators. Regular languages. Examples. BYTE, WORD32, and WORD64 as languages computers "like", and how we…


Familiar sets and operators on them. The boolean domain and basic operators on booleans (AND, OR, NOT). Representing numbers in binary, and in other bases. Can you represent anything you care about…


AMS1C Lecture 20210929 at 16:10


Algorithmic Frameworks for Neuromorphic Computing: Neural Engineering Framework (NEF) Luis El Srouji gives an overview and explanation of the Neural Engineering Framework which can calculate weight…


Abstract: Sparse Manifold clustering and embedding (SMCE) is an algorithm to cluster nonlinear manifolds using selfrepresentation in the dictionary of data points and a proximity regularization. A…


In this talk, we offer an entirely “white box’’ interpretation of deep (convolution) networks from the perspective of data compression (and group invariance). In particular, we show…








WeylMinkowski's theorem proved using Fourier Motzkin elimination and Polarity of cones.
