Kattt Atchley

Blog Posts

Double congratulations to Mike Jordan!

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A couple of announcements regarding Prof. Mike Jordan came in today: 1) Mike joins only a handful of distinguished Berkeley faculty members who have been elected as a Foreign Member of the Royal Society: https://royalsociety.org/news/2021/05/new-fellows-announcement-2021/ 2) He has also been selected to join the 2021 Class of Vannevar Bush Faculty Fellows. The Vannevar Bush Faculty Fellowship (VBFF) is the US Department of Defense’s most prestigious single-investigator award and supports basic research with the potential for transformative impact. Another amazing week for Prof. Jordan!

“Neural-Backed Decision Trees” Accepted to ICLR 2021

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Want to improve accuracy, interpretability, and generalization for your production models? Check out “Neural-Backed Decision Trees” from Professor Joseph E. Gonzalez’s group — including Alvin Wan, Lisa Dunlap, Suzie Petryk, and others — just accepted to ICLR 2021 and just one pip install away. See the brief 3-minute introduction: https://youtu.be/fQ2eNFCSRiA or the updated technical talk with new results and 4 additional human studies: https://youtu.be/bC5n1Yov7D0

Best paper award at NeurIPS 2020

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RISELab faculty Prof. Michael Mahoney and his postdocs Michal Derezinski and Rajiv Khanna are recipients of NeurIPS 2020 Best Paper Award for their paper “Improved Guarantees and a Multiple-Descent Curve for Column Subset Selection and the Nyström Method“. To quote the selection committee: “(…) this paper is expected to have substantial impact and give new insight into (…) kernel methods, feature selection, and the double-descent behavior of neural networks.” Congratulations to Michael, Michal and Rajiv!

Michael Jordan wins 2021 AMS Ulf Grenander Prize

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Prof. Michael I. Jordan, one of RISELab affiliated faculty, has been awarded the 2021 American Mathematical Society (AMS) Ulf Grenander Prize in Stochastic Theory and Modeling. The prize, which was established in 2016, recognizes “exceptional theoretical and applied contributions in stochastic theory and modeling.” It is awarded for “seminal work, theoretical or applied, in the areas of probabilistic modeling, statistical inference, or related computational algorithms, especially for the analysis of complex or high-dimensional systems.” Jordan, who has a split appointment in Statistics, was cited for “foundational contributions to machine learning, especially unsupervised learning, probabilistic computation, and core theory for balancing statistical fidelity with computation.” The prize is awarded every three years, making Jordan the second recipient of the honor.

SEC 2020 Best Paper Award!

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Congratulations to Samvit Jain and Prof. Joey Gonzalez of RISELab for winning the Best Paper award at The Fifth ACM/IEEE Symposium on Edge Computing for the collaborative paper “Spatula: Efficient Cross-Camera Video Analytics on Large Camera Networks”!

Ray Summit happening this Wednesday, September 30th through Thursday, October 1st

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Inaugural Ray Summit is happening this Wednesday, September 30th through Thursday, October 1st. With thousands of the global Ray community from over 100 countries planning to attend, it’s an important milestone for the Ray project that started at U.C. Berkeley’s RISELab nearly four years ago. If you haven’t registered yet, please register here (it’s free!) to get access to the livestream and all session videos. You will hear exciting announcements about the latest features in Ray, new integrations with popular libraries, real-world use cases, and the latest research in AI, scalable systems, and security. Looking forward to seeing you all at the summit! 

Prof. Aditya Parameswaran awarded Sloan Research Fellowship

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Prof. Aditya Parameswaran, RISELab faculty, is one of the nine Sloan Research Fellowship recipients from UC Berkeley, in recognition of his work on building tools to enable people unfamiliar with programming to understand large datasets. You can read related articles here and here. Full list of recipients on Sloan Foundation’s website.

RISE Camp 2019 photos!

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Photos from the awesome RISE Camp 2019 have been posted to our Facebook page. (If you haven’t been aware of its existence, now is your chance to click “Like” and start getting all the latest RISELab news in your feed!)

Prof. Raluca Popa recepient of Bakar Faculty Fellowship Spark Fund Award

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Prof. Popa, one of RISELab’s core faculty members, has been selected for the Bakar Fellows Program, which supports faculty working to apply scientific discoveries to real-world issues in the fields of engineering, computer science, chemistry, and biological and physical sciences. With her Bakar Fellows Spark Award, Prof. Popa will design and build a data encryption platform that will enable collaborative machine learning studies by performing these multi-party computations under encryption. https://vcresearch.berkeley.edu/bakarfellows/about

RadLab students and faculty win “Test of Time” award for the “Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning” paper

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Students and faculty of RadLab, one of the predecessors of the RISElab, just won a “Test of Time” award  for the most influential paper of the 40 presented at the original conference in 2009 . It combined systems and machine learning fields, setting a precedent for a popular combination today. You can read the official announcement here.

“A Swiss Army Infinitesimal Jackknife” paper wins “Notable Paper Award” at the 2019 Artificial Intelligence and Statistics (AISTATS) conference

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The following paper from the RISELab has won the “Notable Paper Award” at the 2019 Artificial Intelligence and Statistics (AISTATS) conference: A Swiss Army Infinitesimal Jackknife; Giordano, R., Stephenson, W., Liu, R., Jordan, M. I. & Broderick, T.  (2019); In K. Chaudhuri and M. Sugiyama (Eds.), Proceedings of the Twenty-Second Conference on Artificial Intelligence and Statistics (AISTATS), Okinawa, Japan.

RISE Camp 2018 Photos!

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Lost of great photos from last week’s RISE Camp can be found here! And if you haven’t already, please make sure you “like” our Facebook page, for all the latest RISELab  news.

Notes from the first Ray meetup

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The Ray team is starting a series of meetups, the first of which was held at OpenAI (in San Francisco) on August 2, 2018, with over 50 people in attendance! Here is a great summary of what was presented, written by Ben Lorica of O’Reilly Media: https://www.oreilly.com/ideas/notes-from-the-first-ray-meetup

Michael I. Jordan: Artificial Intelligence — The Revolution Hasn’t Happened Yet

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(This article has originally been published on Medium.com.) Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying the use of the phrase. But this is not the classical case of the public not understanding the scientists — here the scientists are often as befuddled as the public. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us — enthralling us and frightening us in equal measure. And, unfortunately, it distracts us. There is a different narrative that one can…

Online Foundations of Data Science Course Launches on edX!

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UC Berkeley’s pathbreaking entry-level course on the Foundations of Data Science (Data 8) is launching on edX on April 2. This makes the fastest-growing class in UC Berkeley history available to everyone. Foundations of Data Science teaches computational and inferential thinking from the ground up. It covers everything from testing hypotheses, applying statistical inferences, visualizing distributions and drawing conclusions—all while coding in Python and using real world data sets. The course is taught by award-winning Berkeley professors and designed by a team of faculty working together across Berkeley’s Computer Science and Statistics Departments, led by RISE faculty Michael Jordan. The three 5-week online courses cover: Foundations of Data Science: Computational Thinking with Python, starting on April 2, teaches the basics…

Pictures from RISE Winter 2018 retreat!

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Our biggest retreat so far (182 registered attendees!) happened January 10 – 12, 2018, at Monterey Tides hotel. We had lots of productive interactions (presentations, meeting, poster sessions), but also managed to have some fun kayaking at the Elkhorn Slough! You can see the photos on our Facebook page.

Incubator launches AI-focused accelerator to help startups out of UC Berkeley, RISELab faculty involved

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Berkeley-based startup incubator and venture capital fund The House is launching an AI-specific initiative backed by Google that is meant to take advantage of the technical and academic expertise in the field coming out of UC Berkeley. The faculty involved in the program include Databricks co-founder and UC Berkeley professor Ion Stoica, Berkeley Artificial Intelligence Research lab co-director Trevor Darrell and UC Berkeley professor Michael Jordan, one of the most influential computer scientists working in AI. You can read the whole article here.

RISELab to cooperate with Alibaba DAMO Academy

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Alibaba Group launched a massive global research program, “Alibaba DAMO Academy”, by committing $15B in funding. The Academy aims to increase technological collaboration worldwide, advance the development of cutting-edge technology, and strive to make the world more inclusive by narrowing the technology gap. The Academy will cooperate with the University of California, Berkeley through its RISE Lab on areas such as secured real-time computing. For more information, please read this article.

Prof. Popa gave a keynote talk at the GE Industrial Machine Learning Workshop 2017

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RISELab’s Raluca Ada Popa gave a keynote talk on security for machine learning systems at the GE Industrial Machine Learning Workshop 2017. https://wise.io/imlw17/ Her talk discussed security threats in deploying machine learning systems as well as three promising approaches to address some of these: secure multi-party computation, differential privacy and hardware enclaves.

RISELab faculty publishes paper on how to build more secure, faster AI systems

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The RISELab faculty—who cover the fields of machine learning, systems, security, and hardware—have just published a vision paper on systems challenges for AI. They argue that future AI systems must make timely and safe decisions in unpredictable environments, be robust against sophisticated adversaries, and process ever increasing amounts of data across organizations and individuals without compromising confidentiality. These challenges will be exacerbated by the end of the Moore’s Law, which will constrain the amount of data these technologies can store and process. They propose several open research directions in systems, computer architecture, and security that can address these challenges and help unlock AI’s potential to improve lives and society. Link to the press release: https://news.berkeley.edu/2017/10/16/berkeley-experts-on-how-to-build-faster-safer-and-more-secure-ai-systems/

Second RISELab Newsletter!

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In case you missed it (it went out on August 1, 2017), you can still read a web copy here. If you’d like to be added to our mailing list, please fill out this form.

Join RISELab at NSDI’17

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Join RISELab at NSDI’17 on March 27th through the 29th in Boston.  There we will be presenting the Opaque and Clipper systems. Please see the below links to read the final versions of the papers and try pre-release versions of the software and check out slides and videos from their previous talks. Opaque system: The paper is already available here Software is available here Slides and video from a previous talk here Clipper system: The paper is available here Software is available here Slides and video from a previous talk here