ES3-3- "ADC-based Wireline Transceivers" - Yohan Frans
Abstract: The emergence of PAM4 electrical signaling standard at 56Gb/s and 112Gb/s has caused wider adoption of ADC-based transceiver. In this talk, we will ...
IEEE Solid-State Circuits Society
David West - The Past and Future of Domain-Driven Design
Domain-Driven Design Europe 2017 http://dddeurope.com - https://twitter.com/ddd_eu The state-of-the-practice for software development in 1968 was ...
Domain-Driven Design Europe
Data Driven Optimization Models and Algorithms
Yinyu Ye, Stanford University https://simons.berkeley.edu/talks/yinyu-ye-11-28-17 Optimization, Statistics and Uncertainty.
Simons Institute
First-Order Stochastic Optimization
Rachel Ward, University of Texas at Austin https://simons.berkeley.edu/talks/clone-intro-his-foundations-data-science-book-ii-1 Foundations of Data Science ...
Simons Institute
Lecture - 1 Introduction to Adaptive Filters
Lecture Series on Adaptive Signal Processing by Prof.M.Chakraborty, Department of E and ECE, IIT Kharagpur. For more details on NPTEL visit ...
nptelhrd
Natasha 2: Faster Non-convex Optimization Than SGD
Zeyuan Allen-Zhu, Microsoft Research https://simons.berkeley.edu/talks/zeyuan-allen-zhu-10-06-17 Fast Iterative Methods in Optimization.
Simons Institute
Sanjeev Arora: Toward Theoretical Understanding of Deep Learning
This is the second Ahlfors lecture of Sanjeev Arora from Princeton University and the Institute for Advanced Study. The lecture was given on September 12, 2018 ...
Harvard Math
Online Learning and Online Convex Optimization I
Nicolo Cesa-Bianchi, University of Milan https://simons.berkeley.edu/talks/nicolo-cesa-bianchi-08-24-2016-1 Algorithms and Uncertainty Boot Camp.
Simons Institute
PID Velocity Control in Python
A self-driving car company has requested a speed controller for their new model of electric autonomous vehicles. Unlike standard cruise control systems, this ...
APMonitor.com
Adaptive learning - how algorithms are transforming learning - LTSF2016
Adaptive learning - how algorithms are transforming learning Donald Clark, Board Member, Ufi Chair: Niall Gavin, L&D and Learning Technology Consultant ...
LearningTechnologies
NIPS 2015 Workshop (Anandkumar) 15598 Non-convex Optimization for Machine Learning: Theory and ...
Non-convex optimization is ubiquitous in machine learning. In general, reaching the global optima of these problems is NP-hard and in practice, local search ...
NIPS
MIT Bootcamps: Intro to Deep Tech with Dr. Josh Siegel
The webinar will provide a high-level overview of emerging areas in DeepTech including the Internet of Things, Autonomous Vehicles, Deep Learning, and ...
MIT Bootcamps
JuliaCon 2020 | Minisymposium on Partial Differential Equations
Chairs: Jürgen Fuhrmann (Weierstrass Institute Berlin), Petr Krysl (UCSD) The talks at the minisymposium present several packages devoted to the solution of ...
The Julia Programming Language
Richard Liaw: A Guide to Modern Hyperparameters Turning Algorithms | PyData LA 2019
www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the ...
PyData
Possible Paths to Artificial General Intelligence
Yoshua Bengio (MILA), Irina Higgins (DeepMind), Nick Bostrom (FHI), Yi Zeng (Chinese Academy of Sciences), and moderator Joshua Tenenbaum (MIT) ...
Future of Life Institute
Mengdi Wang: "On the statistical complexity of reinforcement learning"
Intersections between Control, Learning and Optimization 2020 "On the statistical complexity of reinforcement learning" Mengdi Wang - Princeton University ...
Institute for Pure & Applied Mathematics (IPAM)
On Expressiveness and Optimization in Deep Learning - Nadav Cohen
Members' Seminar Topic: On Expressiveness and Optimization in Deep Learning Speaker: Nadav Cohen Affiliation: Member, School of Mathematics Date: April ...
Institute for Advanced Study
Module 3 Lecture 1 Neural Control A review
Lectures by Prof. Laxmidhar Behera, Department of Electrical Engineering, Indian Institute of Technology, Kanpur. For more details on NPTEL visit ...
nptelhrd
MIT AGI: Building machines that see, learn, and think like people (Josh Tenenbaum)
This is a talk by Josh Tenenbaum for course 6.S099: Artificial General Intelligence. This class is free and open to everyone. Our goal is to take an engineering ...
Lex Fridman
Mod-01 Lec-33 Introduction to multi-variable optimization
Design and Optimization of Energy Systems by Prof. C. Balaji , Department of Mechanical Engineering, IIT Madras. For more details on NPTEL visit ...
nptelhrd
28. Neural Networks
In the context of this course, we view neural networks as "just" another nonlinear hypothesis space. On the practical side, unlike trees and tree-based ensembles ...
Inside Bloomberg
Quantum-probabilistic Generative Models and Variational Quantum Thermalization - Guillaume Verdon
Speaker: Guillaume Verdon Host: Zlatko Minev, Ph.D. Title: Quantum-probabilistic Generative Models and Variational Quantum Thermalization Algorithms ...
Qiskit
Michael I. Jordan: Machine Learning: Dynamical, Stochastic & Economic Perspectives
2019 Purdue Engineering Distinguished Lecture Series presenter Dr. Michael I. Jordan While there has been significant progress at the interface of statistics and ...
Purdue Engineering
Online Optimization, Smoothing, and Competitive Ratio
Maryam Fazel, University of Washington https://simons.berkeley.edu/talks/maryam-fazel-09-13-17 Discrete Optimization via Continuous Relaxation.
Simons Institute
John Tsitsiklis (MIT): "The Shades of Reinforcement Learning"
John Tsitsiklis (MIT): "The Shades of Reinforcement Learning" May 31, 2019 Learning for Dynamics and Control (L4DC) 2019.
MIT Institute for Data, Systems, and Society
High-Accuracy Neural-Network Models for Speech Enhancement
In this talk we will discuss our recent work on AI techniques that improve the quality of audio signals for both machine understanding and sensory perception.
Microsoft Research
What is Cognitive AI? Cognitive Computing vs Artificial Intelligence | AI Tutorial | Edureka
PGP in AI and Machine Learning (9 Months Online Program) : https://www.edureka.co/post-graduate/machine-learning-and-ai This Edureka video on "Cognitive ...
edureka!
Digital Design & Computer Arch. - Lecture 18b: Systolic Arrays and Beyond (ETH Zürich, Spring 2020)
Digital Design and Computer Architecture, ETH Zürich, Spring 2020 (https://safari.ethz.ch/digitaltechnik/spring2020/doku.php?id=start) Lecture 18b: Systolic ...
Onur Mutlu Lectures
noc18-ee31-Lec 52 -Applied Optimization | Co-operative Communication -I
Want to learn about PYTHON and 5G Technology? Check out our 5G Python Program below! https://www.iitk.ac.in/mwn/python5G/ Welcome to the IIT Kanpur ...
IIT Kanpur July 2018
Lecture 3 | Loss Functions and Optimization
Lecture 3 continues our discussion of linear classifiers. We introduce the idea of a loss function to quantify our unhappiness with a model's predictions, and ...
Stanford University School of Engineering
Mod-14 Lec-37 Neuro-Adaptive Design -- II
Advanced Control System Design by Radhakant Padhi, Department of Aerospace Engineering, IISC Bangalore For more details on NPTEL visit ...
nptelhrd
tinyML Talks - Pete Warden: Getting started with TinyML
tinyML Talks webcast - recorded March 31, 2020 Pete Warden - Google Daniel Situnayake (moderator) - Edge Impulse If you're interested in running machine ...
tinyML
Lecture - 29 Equalization and Diversity Techniques
Lecture Series on Wireless Communications by Dr.Ranjan Bose, Department of Electrical Engineering, IIT Delhi. For more details on NPTEL, visit ...
nptelhrd
Deep Learning Crash Course for Beginners
Learn the fundamental concepts and terminology of Deep Learning, a sub-branch of Machine Learning. This course is designed for absolute beginners with no ...
freeCodeCamp.org
Accelerating Vaccine Development: Applications to COVID-19 and Future Pandemics
The COVID-19 pandemic has created an urgent need to develop a safe and effective vaccine. Currently, research groups around the world are working to ...
Certara
Adaptive Sampling via Sequential Decision Making - András György
The workshop aims at bringing together researchers working on the theoretical foundations of learning, with an emphasis on methods at the intersection of ...
The Alan Turing Institute
Steven Low - CS+Energy - Alumni College 2016
"Greening the Grid through Optimization and Control" Steven Low, Professor of Computer Science and Electrical Engineering, is deeply involved in research ...
caltech
Design in Tech Report 2019 at SXSW
I delivered the 5th Design in Tech Report at SXSW in Austin, Texas on March 9, 2019. This report covers the latest trends in the technology sphere with respect ...
John Maeda
Computer Science and World Building in Homestuck
This is part one of a video analysis on the webcomic Homestuck. It attempts to lay out Homestuck's world building and frame it in the context of computer science ...
Tex Talks
Project Bonsai End-to-End Workflow
Project Bonsai enables subject matter experts, even those with no AI background, to incorporate their expertise directly into an AI model and teach it how to ...
AnyLogic
Stanford Seminar - Safe and Robust Perception-Based Control
Sarah Dean UC Berkeley February 21, 2020 Machine learning provides a promising path to distill information from high dimensional sensors like cameras -- a ...
stanfordonline
CppCon 2017: Hartmut Kaiser “The Asynchronous C++ Parallel Programming Model”
http://CppCon.org — Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/CppCon/CppCon2017 — With ...
CppCon
