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!
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.
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”!
Video recordings of all the presentations can be viewed on our YouTube channel. Slides and tutorials can be found on the event website. Thanks to all the participants who made RISE Camp 2020 a success!
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, 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.
Join us for Ray (http://ray.io/) meetup on January 30th at 6:00pm, hosted at Galvanize SF! Please RSVP here: https://www.meetup.com/Bay-Area-Ray-Meetup/events/267883815/
Anyscale was founded by our grad students Robert Nishihara and Philipp Moritz, as well as our lab director, professor Ion Stoica. The company is an extension of the research they were doing on Ray, an open source project developed in RISELab. You can read the Busineess Insider article here.
Videos of all talks from RISE Camp 2019 are now available for viewing on RISELab YouTube channel.
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!)
Quick update: There are two separate links for live streaming (one for each day). Please use the following: YouTube RISE Camp 2019 Live Stream – Day 1 YouTube RISE Camp 2019 Live Stream – Day 2 If you have any questions or need assistance registering please feel free to contact us at email@example.com Best regards, The RISE Camp Team
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
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.
Congratulations to Raluca Popa, core RISELab faculty member, and EECS faculty Moritz Hardt, who just won 2019 Okawa Research Foundation Grants! The award will be celebrated at a presentation in San Francisco in the fall.
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 videos have been posted to our YouTube channel! Please enjoy and share!
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.
Prof. Raluca Popa, one our core faculty, has received an award from The Hellman Fellows Fund, which supports junior faculty research on the ten campuses of the UC system and at four private institutions. Congratulations to Prof. Popa!
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
Please go to our Facebook page to see photos from our best retreat yet!
(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…
The online version of our April 2018 Newsletter can be found here.
Prof. Ion Stoica and Xin Jin, a former postdoc in RISELab (now a faculty at John Hopkins University), have received the best paper award for their paper on NetChain which shows that it is possible to do coordination in distributed systems at line speed. You can read more about it at the official NSDI link.
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…
You can read the full article here. For more info on Prof. Popa, please go to her page.
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.
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.
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.
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.
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/
Link: https://www.youtube.com/playlist?list=PLTPaZLQlNIHqJf8GYCly6m2Pl8pBqPLpR. Please subscribe to our channel!
This is the YouTube Live Stream link for Friday, 9/8/17: https://www.youtube.com/watch?v=JKwCXafHmgg
PLEASE NOTE: tutorials are not Live Streamed – they will be made available on the event page at a later date
Apologies for the earlier problems; the live stream link is working now: https://www.youtube.com/watch?v=lmQOEjymzUk
For the latest agenda updates and link to the Live Stream (starting at 9 AM), please go to the event website: https://risecamp.berkeley.edu/.
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.
Meet Ray, the Real-Time Machine-Learning Replacement for Spark
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