14. Caching and Cache-Efficient Algorithms
MIT 6.172 Performance Engineering of Software Systems, Fall 2018 Instructor: Julian Shun View the complete course: https://ocw.mit.edu/6-172F18 YouTube ...
MIT OpenCourseWare
Pushing C# to the limit - Joe Albahari
C# is a language of breadth. At one end it allows low-level programming with pointers and lock-free synchronization; at the other end, it sports high-level ...
NDC Conferences
Presto: Optimizing Performance of SQL-on-Anything | Starburst
Download Slides: https://www.datacouncil.ai/talks/presto-optimizing-performance-of-sql-on-anything?hsLang=en WANT TO EXPERIENCE A TALK LIKE THIS ...
Data Council
An introduction to high performance custom arrays | Matt Bauman
Have you ever wondered how or why you might create a custom array? Have you never written struct ___ : AbstractArray{T,N}? It's easier than you might expect!
The Julia Programming Language
Decoupling Algorithms from the Organization of Computation for High-Performance Graphics & Imaging
Future graphics and imaging applications�from photorealistic real-time rendering, to 4D light field cameras and pervasive sensing, to multi-material 3D ...
Microsoft Research
Domain-Driven Design: Hidden Lessons from the Big Blue Book - Nick Tune
We are entering an incredible new era of digital product development where users expect a seamless experience across all of their touchable, wearable, and ...
NDC Conferences
Sanjeev Arora | Provable Bounds for Machine Learning
Many tasks in machine learning (especially unsupervised learning) are provably intractable: NP-complete or worse. Can we change this state of affairs? This talk ...
University of Michigan Engineering
Unity ECS for mobile: Metropolis Traffic Simulation - Unite Copenhagen
For most Unity developers, the cutting-edge data-oriented approach introduced with the Entity Component System (ECS) is unfamiliar. While ECS clearly ...
Unity
Deep Dive on Amazon Athena - AWS Online Tech Talks
Amazon Athena is an interactive query service that enables you to process data directly from Amazon S3 without the need for infrastructure. Since its launch at ...
AWS Online Tech Talks
AI Meets Security - Prof. Zico Kolter, CMU
Description: Prof. Kolter presents a talk on Securing AI in a talk entitled Provably Robust Deep Learning: Methods and Challenges.
IBM Research
MIA: Eric Kelsic, Machine-guided capsid engineering for gene therapy; Sam Sinai, Sequence design
October 7, 2020 Models, Inference and Algorithms Broad Institute Meeting: ...
Broad Institute
"GC Tuning Confessions Of A Performance Engineer" by Monica Beckwith
Performance tuning is a methodical and an iterative process. It is imperative to have a performance plan coexist with a product development plan. A performance ...
Strange Loop
Amazon DynamoDB Accelerator (DAX): DynamoDB Just Got Faster - 2017 AWS Online Tech Talks
Learning Objectives: - Learn about the benefits and features to help you get the most out of your DynamoDB database - Learn how customers have successfully ...
AWS Online Tech Talks
BEREC Public virtual workshop on traffic identification
During the workshop, the co-Chairs of BEREC's Open Internet Working Group Michiel Van Dijk (ACM, The Netherlands) and Klaus Nieminen (Traficom, Finland) ...
berec.europa.eu
TechBytes: Teradata 101 | Part 4. Optimizer
Learn what makes Teradata Database unique and powerful though a series of videos - Teradata Database 101 series. In this 4th module, you will learn about ...
Teradata
YOW! CTO 2019 - Rebecca Wirfs Brock - Decision Making and Heuristics
CTOs often make high-stakes architecture decisions under conditions of uncertainty, with insufficient information, and too little time. At other times it is prudent to ...
YOW! Conferences
Cloud OnAir: Stream Processing with Cloud Dataflow: SDKs & Architectures
Stream processing can seem challenging. However, Google Cloud Dataflow simplifies and abstracts away a lot of the complexities so that you can implement ...
Google Cloud Platform
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization (Paper Explained)
machinelearning #ai #google The high-level architecture of CNNs has not really changed over the years. We tend to build high-resolution low-dimensional ...
Yannic Kilcher
Leland Mcinnes: Topological Techniques for Unsupervised Learning | 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
Closing Keynote: Quantum Computing: Reality vs. Hype - John Preskill - 6/27/2019
AstroInformatics 2019 Conference: Methodology Transfer, Quantum Computing, and Looking Ahead http://astroinformatics2019.org/
caltech
Keynote: Inside Microsoft Azure Datacenter Architecture
Mark Russinovich is Chief Technology Officer for Microsoft Azure, Microsoft's global enterprise-grade cloud platform. A widely recognized expert in distributed ...
Microsoft Research
A Blueprint of Standardized and Composable Machine Learning - Eric Xing
Seminar on Theoretical Machine Learning Topic: A Blueprint of Standardized and Composable Machine Learning Speaker: Eric Xing Affiliation: Carnegie ...
Institute for Advanced Study
Efficient and Scalable Deep Learning
In deep learning, researchers keep gaining higher performance by using larger models. However, there are two obstacles blocking the community to build larger ...
Microsoft Research
Stanford Seminar: HPC Opportunities in Deep Learning
EE380: Computer Systems Colloquium HPC Opportunities in Deep Learning Speaker: Greg Diamos, Baidu Just this year, deep learning has fueled significant ...
stanfordonline
CppCon 2018: Nir Friedman “Understanding Optimizers: Helping the Compiler Help You”
http://CppCon.org — Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/CppCon/CppCon2018 ...
CppCon
How to Train Neural Networks Fast and Efficiently | Tutorial
0:00 Multi-GPU Training 2:15 Cyclic Learning Rate Schedules 3:07 Mixup: Beyond Empirical Risk Minimization 3:44 Label Smoothing 4:28 Deep Double ...
Leo Isikdogan
State of the .NET Performance - Adam Sitnik
There are major performance changes in .NET Core and C# 7. This talk will be a guided tour of most important of them. We'll see how the new tools: ref returns ...
NDC Conferences
Ses 20: Efficient Markets III & Course Summary
MIT 15.401 Finance Theory I, Fall 2008 View the complete course: http://ocw.mit.edu/15-401F08 Instructor: Andrew Lo License: Creative Commons BY-NC-SA ...
MIT OpenCourseWare
Lecture - 5 Heuristic Search: A* and Beyond
Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, I.I.T,kharagpur. For More details on NPTEL visit ...
nptelhrd
Webinar: Building a real-time analytics pipeline with BigQuery and Cloud Dataflow (EMEA)
Join the live chat Q&A at: https://cloudwebinars.withgoogle.com/live/real-time-analytics-emea/watch/webcast Real-time ingestion and analysis of data streams is ...
Google Cloud Platform
Approximate cross validation for large data and high dimensions - Tamara Broderick, MIT
The error or variability of statistical and machine learning algorithms is often assessed by repeatedly re-fitting a model with different weighted versions of the ...
The Alan Turing Institute
Technology and the future of medicine | Dr Cosima Gretton | TEDxRoyalHolloway
In the last 5 years there has been a surge in new technologies for healthcare, predicted to transform the field. The effect on the medical profession is profound.
TEDx Talks
Non-Convex Quadratic Optimization Webinar
One major new feature in Gurobi 9.0 is a new bilinear solver, which allows users to solve problems with non-convex quadratic objectives and constraints (i.e., ...
Gurobi Optimization
STOC 2020 - Workshop 5: Algorithms with Predictions
Association for Computing Machinery (ACM)
Phebe Vayanos, Robust Optimization & Sequential Decision-Making
CompSustNet
How to get the most out of ray tracing | Inside Unreal
We have a special guest in the studio this week! Sjoerd De Jong will walk us through an updated version of the ray tracing example he demonstrated at GDC.
Unreal Engine
XLA: TensorFlow, Compiled! (TensorFlow Dev Summit 2017)
Speed is everything for effective machine learning, and XLA was developed to reduce training and inference time. In this talk, Chris Leary and Todd Wang ...
Google Developers
"Why Auto-routers Suck, And How To Use Them Anyway" - Craig Bishop (KiCon 2019)
Note: This is a re-upload with fixed audio) Auto-routers have a widespread reputation for sucking, hard. Have you ever wondered why that is? What math and ...
Contextual Electronics
CppCon 2017: P. McKenney, M. Michael & M. Wong “Is Parallel Programming still hard? PART 1 of 2”
http://CppCon.org — Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/CppCon/CppCon2017 — Most ...
CppCon
Physical Internet: Concept, Research, Innovation
An overview of the research of Dr. Benoit Montreuil, who leads the International Physical Internet Initiative, engaging academic, industry and government leaders ...
GTSCL
Strategic Autonomous Design: Patterns and Heuristics - Nick Tune - KanDDDinsky 2018
Model the wrong boundaries in your systems and disaster is just around the corner waiting to tease your sanity. An excess of dependencies between modules ...
KanDDDinsky
Adversarial Machine Learning
The reliability of machine learning systems in the presence of adversarial noise has become a major field of study in recent years. As ML is being used for ...
Microsoft Research
