Kavya Joshi on "Kraken: Leveraging Live Trafﬁc Tests to Identify and Resolve Resource Utilization Bottlenecks in Large Scale Web Services" - https://research.fb.com/publications/kraken-leveraging-live-traf%EF%AC%81c-tests-to-identify-and-resolve-resource-utilization-bottlenecks-in-large-scale-web-services/
Kavya (https://twitter.com/kavya719) writes code for a living at a start-up in San Francisco. She particularly enjoys architecting and building highly concurrent, highly scalable systems. In her free time, she reads non-fiction and climbs rocks. Before moving to San Francisco to be an Adult, Kavya was at MIT where she got a Bachelor's and Master's in Computer Science.
Matt Adereth on Distributed black-box optimization techniques.
Matt tells us:" We often want to find the best settings for our systems, whether it’s configuring the best JVM parameters, optimizing user workflows, or selecting the right configuration for a machine learning algorithm. Black-box optimization techniques that can find good (hopefully optimal!) parameters have been investigated for the last 60 years, but over the last 20 years there’s been significant attention placed on creating versions that can take advantage of parallel compute.
We’ll cover the types of real-world problems that are being solved with these techniques and then walk through a bunch of papers covering the distributed approaches, starting with _Direct Search Methods on Parallel Machines_ (1991) and ending with the very recent _Google Vizier: A Service for Black-Box Optimization_ (August 2017)."
Matt (https://twitter.com/adereth) builds tools and infrastructure for quantitative research at Two Sigma. He previously worked at Microsoft on Visio, focusing on ways to connect data to shapes In his spare time, he builds ergonomic keyboards using Clojure.
Doors open at 6:30 pm; the presentation will begin at 7:00 pm; and, yes, there will be food.
After the paper is presented, we will open up the floor for discussion and questions then we will head over to the bar!
PWL SF strictly adheres to the Code of Conduct (https://github.com/papers-we-love/papers-we-love/blob/master/CODE_OF_CONDUCT.md) set forth by all PWL charters.