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X-WR-CALDESC:Events for Halıcıoğlu Data Science Institute - UC San Diego
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DTSTART;TZID=America/Los_Angeles:20201201T130000
DTEND;TZID=America/Los_Angeles:20201201T140000
DTSTAMP:20260723T020952
CREATED:20201124T214441Z
LAST-MODIFIED:20201124T214441Z
UID:10000140-1606827600-1606831200@datascience.ucsd.edu
SUMMARY:Data Systems for Machine Learning Lecture
DESCRIPTION:We have 3 exciting invited talks from industry in my graduate CSE course titled “Data Systems for Machine Learning” (coursewebpage). The topics span ML deployment platforms\, deep learning training platforms\, and GPU acceleration for data science workloads. I’d like to open up these talks to the wider CSE and HDSI talks audiences. \n  \nThe full 3-talk schedule is attached for your convenience. Each talk’s details will be emailed a few days ahead of time. All talks will be recorded. The speakers have consented to the recordings being posted publicly on Youtube. \n  \nJoin Zoom Meeting \nhttps://ucsd.zoom.us/j/92636219457?pwd=bWpLTFJackdzUXVlenVXcTJHU0Q3dz09 \n  \nMeeting ID: 926 3621 9457\nPassword: 579720 \n  \nOnetap mobile\n+12133388477\,\,92636219457# US (Los Angeles)\n+16692192599\,\,92636219457# US (San Jose) \n  \nDialby your location\n+1 213 338 8477 US (Los Angeles)\n+1 669 219 2599 US (San Jose)\n+1 669 900 6833 US (San Jose)\nMeeting ID: 926 3621 9457\nFind your local number: https://ucsd.zoom.us/u/aeuwWB6NW7
URL:https://datascience.ucsd.edu/event/data-systems-for-machine-learning-lecture/
CATEGORIES:Guest Lecture
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201201T143000
DTEND;TZID=America/Los_Angeles:20201201T160000
DTSTAMP:20260723T020952
CREATED:20201117T181952Z
LAST-MODIFIED:20230929T215007Z
UID:10000136-1606833000-1606838400@datascience.ucsd.edu
SUMMARY:Addressing Anti-Blackness: How to Sustain a Culture of Inclusion\, Equity\, and Anti-Racism at UC San Diego
DESCRIPTION:Please join the UC San Diego Staff Association and Black Staff Association as we welcome Shola Richards to facilitate the discussion Addressing Anti-Blackness: How to Sustain a Culture of Inclusion\, Equity\, and Anti-Racism at UC San Diego. The highly engaging Addressing Anti-Blackness webinar will provide the audience with the information\, strategies\, and critical actions necessary to engage in this work and sustain it. \nThis webinar is ideal for individual contributors\, leaders\, and teams who are: \n\nLooking for the strategies and actions necessary to create and sustain an anti-racist culture at UC San Diego.\nConcerned about the current civil unrest and its impact on your BIPoC (Black\, Indigenous\, and People of Color) colleagues’ mental health and well-being.\nReady to effectively engage in difficult conversations with colleagues and others about race\, inequity\, and anti-blackness.\n\nThe audience will leave with: \n\nThe discovery of the history of systemic racism and its impact on the modern-day workplace.\nStrategies to recognize bias\, prejudice\, and microaggressions in the workplace and how to address it immediately.\nThe education\, inspiration\, and the key actions necessary to stay committed to the ongoing work of anti-racism.\n\nRegistration \nFor ALL STAFF \n\nTuesday\, December 8\, 2:30 p.m. – 4 p.m.\n\nFor HEALTH SCIENCES \n\nTuesday\, November 17\, 2:30 p.m. – 4 p.m.\n\nFor BLACK STAFF \n\nTuesday\, December 1\, 2:30 p.m. – 4 p.m.\n\n* All sessions will be recorded and live captioned. \nContact Bryce Besser with questions\, bbesser@ucsd.ed \n 
URL:https://datascience.ucsd.edu/event/addressing-anti-blackness-how-to-sustain-a-culture-of-inclusion-equity-and-anti-racism-at-uc-san-diego/2020-12-01/
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201203T160000
DTEND;TZID=America/Los_Angeles:20201203T173000
DTSTAMP:20260723T020952
CREATED:20201106T175928Z
LAST-MODIFIED:20201106T175928Z
UID:10000284-1607011200-1607016600@datascience.ucsd.edu
SUMMARY:Institute for Practical Ethics Keynote Series: How Not to Destroy the World with AI
DESCRIPTION:How Not to Destroy the World with AI\nThe Institute for Practical Ethics speaker series featuring Stuart Russell of UC Berkeley has been rescheduled\, and will take place Dec. 3 at 4 p.m.\nRegistration is open >>\nIn this third annual lecture of the Institute for Practical Ethics\, Stuart Russell will briefly survey recent and expected developments in artificial intelligence and their implications. Some are enormously positive\, while others\, such as the development of autonomous weapons and the replacement of humans in economic roles\, may be negative. \nBeyond these\, one must expect that AI capabilities will eventually exceed those of humans across a range of real-world-decision making scenarios. Should this be a cause for concern\, as Elon Musk\, Stephen Hawking\, and others have suggested? And\, if so\, what can we do about it? \nWhile some in the mainstream AI community dismiss the issue\, I will argue that the problem is real and that the technical aspects of it are solvable if we replace current definitions of AI with a version based on provable benefit to humans. \nRegister for the webinar here: https://bit.ly/2GkXqUs \n\nStuart Russell received his bachelor’s degree with first-class honours in physics from Oxford University in 1982 and his Ph.D. in computer science from Stanford University in 1986. He then joined the faculty of the University of California at Berkeley\, where he is professor (and formerly chair) of Electrical Engineering and Computer Sciences and holder of the Smith-Zadeh Chair in Engineering. He is also an adjunct professor of neurological surgery at UC San Francisco and vice-chair of the World Economic Forum’s Council on AI and Robotics. \nRussell is a recipient of the Presidential Young Investigator Award of the National Science Foundation\, the IJCAI Computers and Thought Award\, the World Technology Award (Policy category)\, the Mitchell Prize of the American Statistical Association and the International Society for Bayesian Analysis\, the ACM Karlstrom Outstanding Educator Award\, and the AAAI/EAAI Outstanding Educator Award. In 1998\, he gave the Forsythe Memorial Lectures at Stanford University\, and from 2012 to 2014 he held the Chaire Blaise Pascal in Paris. He is a Fellow of the American Association for Artificial Intelligence\, the Association for Computing Machinery and the American Association for the Advancement of Science. \nHis research covers a wide range of topics in artificial intelligence including machine learning\, probabilistic reasoning\, knowledge representation\, planning\, real-time decision making\, multitarget tracking\, computer vision\, computational physiology\, global seismic monitoring and philosophical foundations. His books include “The Use of Knowledge in Analogy and Induction\,” “Do the Right Thing: Studies in Limited Rationality” (with Eric Wefald) and “Artificial Intelligence: A Modern Approach” (with Peter Norvig). His current concerns include the threat of autonomous weapons and the long-term future of artificial intelligence and its relation to humanity. \n 
URL:https://datascience.ucsd.edu/event/institute-for-practical-ethics-keynote-series-how-not-to-destroy-the-world-with-ai/
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201204T130000
DTEND;TZID=America/Los_Angeles:20201204T140000
DTSTAMP:20260723T020952
CREATED:20201130T215335Z
LAST-MODIFIED:20201130T215335Z
UID:10000142-1607086800-1607090400@datascience.ucsd.edu
SUMMARY:Meet the DSC Reps!
DESCRIPTION:Take a break from midterms and come meet your Data Science Student Representatives this Friday! Chat with the Reps and play some games to win awesome HDSI swag. Learn how to balance classes\, get peer insight on finding research and internships\, and talk about any other questions you’d like answered. Please RSVP through the link below to receive the Zoom link.   \n			\n						RSVP Here for Zoom Link
URL:https://datascience.ucsd.edu/event/meet-the-dsc-reps/
CATEGORIES:HDSI Event
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DTSTART;TZID=America/Los_Angeles:20201204T150000
DTEND;TZID=America/Los_Angeles:20201204T160000
DTSTAMP:20260723T020952
CREATED:20201203T183014Z
LAST-MODIFIED:20201203T183014Z
UID:10000150-1607094000-1607097600@datascience.ucsd.edu
SUMMARY:Seminar: Programmatically Building & Managing Training Data with Snorkel by Alex Ratner
DESCRIPTION:For the final Database Seminar of this quarter on Friday (Dec 4) at 3pm PT\, we have another exciting external speaker\, Alex Ratner. He is going to tell us about programmatic approaches to label data for modern ML/AI applications that reduce the burden of manual hand labeling. \nPlease find the talk details and Zoom details below. \nIf you’d like to get DB-related talk notices in future quarters\, please subscribe to the db-talks mailing list as described here: https://dbucsd.github.io/seminar \n— \nTitle:\nProgrammatically Building & Managing Training Data with Snorkel \nAbstract: \nOne of the key bottlenecks in building machine learning systems is creating and managing the massive training datasets that today’s models require. In this talk\, I will describe our work on Snorkel (snorkel.org)\, an open-source framework for building and managing training datasets\, and describe three key operators for letting users build and manipulate training datasets: labeling functions\, for labeling unlabeled data; transformation functions\, for expressing data augmentation strategies; and slicing functions\, for partitioning and structuring training datasets. These operators allow domain expert users to specify machine learning (ML) models entirely via noisy operators over training data\, expressed as simple Python functions—or even via higher level NL or point-and-click interfaces—leading to applications that can be built in hours or days\, rather than months or years\, and that can be iteratively developed\, modified\, versioned\, and audited. I will describe recent work on modeling the noise and imprecision inherent in these operators\, and using these approaches to train ML models that solve real-world problems\, including recent state-of-the-art results on benchmark tasks and real-world industry\, government\, and medical deployments. \nSpeaker bio: \nAlex Ratner is the co-founder and CEO of Snorkel AI\, Inc.\, which supports the open source Snorkel library and develops Snorkel Flow\, an end-to-end system for building machine learning applications\, and an Assistant Professor of Computer Science at the University of Washington. Prior to Snorkel AI and UW\, he completed his PhD in CS advised by Christopher Ré at Stanford\, where his research focused on applying data management and statistical learning techniques to emerging machine learning workflows\, such as creating and managing training data\, and applying this to real-world problems in medicine\, knowledge base construction\, and more. \n— \nArun Kumar is inviting you to a scheduled Zoom meeting. \nPlease download and import the following iCalendar (.ics) files to your calendar system.\nWeekly: https://ucsd.zoom.us/meeting/tJwqceGpqjMvGNy7Td1vjiCqmP4Rb3_iCDIG/ics?icsToken=98tyKuCgqT0iG9CdtRuPRow-B4_oWevwiFxYjY1EyyvhUjZZayDnO9IWALAsL9Hz \nJoin Zoom Meeting\nhttps://ucsd.zoom.us/j/98768148528?pwd=NFFrSVpySWlEOU9WT3FhWVlkTmZFUT09 \nMeeting ID: 987 6814 8528\nPassword: 827714 \nOne tap mobile\n+12133388477\,\,98768148528# US (Los Angeles)\n+16692192599\,\,98768148528# US (San Jose) \nDial by your location\n+1 213 338 8477 US (Los Angeles)\n+1 669 219 2599 US (San Jose)\n+1 669 900 6833 US (San Jose)\n833 548 0276 US Toll-free\n833 548 0282 US Toll-free\n877 853 5257 US Toll-free\n888 475 4499 US Toll-free\nMeeting ID: 987 6814 8528\nFind your local number: https://ucsd.zoom.us/u/ajIyGW1ve
URL:https://datascience.ucsd.edu/event/seminar-programmatically-building-managing-training-data-with-snorkel-by-alex-ratner/
CATEGORIES:Guest Lecture,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201207T120000
DTEND;TZID=America/Los_Angeles:20201207T130000
DTSTAMP:20260723T020952
CREATED:20201203T004927Z
LAST-MODIFIED:20201203T004927Z
UID:10000148-1607342400-1607346000@datascience.ucsd.edu
SUMMARY:Causal Inference for Responsible Data Science
DESCRIPTION:The last AI seminar of the Fall quarter will take place next Monday\, Monday (Dec 7) from 12pm-12:50pm over Zoom (https://ucsd.zoom.us/j/99067937524). Our speaker is Babak Salimi. Looking forward! FYI: The recording and slides of the previous talks can be found here: https://shangjingbo1226.github.io/teaching/2020-fall-CSE259-AI-seminarTitle: Causal Inference for Responsible Data ScienceAbstract: Scaling and democratizing access to big data promises to provide meaningful\, actionable information that supports decision-making. Today\, data-driven decisions profoundly affect the course of our lives\, such as whether to admit applicants to a particular school\, offer them a job\, or grant them a mortgage. Unfair\, inconsistent\, or faulty decision-making raises serious concerns about ethics and responsibility. For example\, we may know that our training data is biased\, but how do we avoid propagating discrimination when we use this data?  How do we avoid incorrect\, spurious and non-reproducible findings?  How can we curate and expose existing data to make it “safe” for informed decision-making?In this talk\, I describe how we can combine techniques from causal inference and data management to develop systems and algorithms that help answer some of these questions.  Many existing popular notions of fairness in ML fail to distinguish between discriminatory\, non-discriminatory and spurious correlations between sensitive attributes and outcomes of learning algorithms. I present a new notion of fairness that subsumes and improves upon previous definitions and correctly distinguishes between fairness violations and non-violations. Further\, I describe an approach to removing discrimination by repairing training data in order to remove the effects of any inappropriate and/or discriminatory causal relationships between a protected attribute and classifier predictions.  Finally\, I present my most recent work that use counterfactual reasoning and provenance for explaining black-box decision-making algorithms. Speaker Bio: Babak Salimi is an assistant professor in HDSI at UC San Diego. Before joining UC San Diego\, he was a postdoctoral research associate in the Department of Computer Science and Engineering\, University of Washington where he worked with Prof. Dan Suciu and the database group. He received his Ph.D. from the School of Computer Science at Carleton University\, advised by Prof. Leopoldo Bertossi. His research seeks to unify techniques from theoretical data management\, causal inference and machine learning to develop a new generation of decision-support systems that help people with heterogeneous background to interpret data. His ongoing work in causal relational learning aims to develop the necessary conceptual foundations to make causal inference from complex relational data. Further\, his research in the area of responsible data science develops needed foundations for ensuring fairness and accountability in the era of data-driven decisions. His research contributions have been recognized with a Postdoc Research Award at University of Washington\, a Best Demonstration Paper Award at VLDB 2018\, a Best Paper Award at SIGMOD 2019 and a Research Highlight Award at SIGMOD 2020.
URL:https://datascience.ucsd.edu/event/causal-inference-for-responsible-data-science/
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201208T143000
DTEND;TZID=America/Los_Angeles:20201208T160000
DTSTAMP:20260723T020952
CREATED:20201117T181952Z
LAST-MODIFIED:20230929T215007Z
UID:10000137-1607437800-1607443200@datascience.ucsd.edu
SUMMARY:Addressing Anti-Blackness: How to Sustain a Culture of Inclusion\, Equity\, and Anti-Racism at UC San Diego
DESCRIPTION:Please join the UC San Diego Staff Association and Black Staff Association as we welcome Shola Richards to facilitate the discussion Addressing Anti-Blackness: How to Sustain a Culture of Inclusion\, Equity\, and Anti-Racism at UC San Diego. The highly engaging Addressing Anti-Blackness webinar will provide the audience with the information\, strategies\, and critical actions necessary to engage in this work and sustain it. \nThis webinar is ideal for individual contributors\, leaders\, and teams who are: \n\nLooking for the strategies and actions necessary to create and sustain an anti-racist culture at UC San Diego.\nConcerned about the current civil unrest and its impact on your BIPoC (Black\, Indigenous\, and People of Color) colleagues’ mental health and well-being.\nReady to effectively engage in difficult conversations with colleagues and others about race\, inequity\, and anti-blackness.\n\nThe audience will leave with: \n\nThe discovery of the history of systemic racism and its impact on the modern-day workplace.\nStrategies to recognize bias\, prejudice\, and microaggressions in the workplace and how to address it immediately.\nThe education\, inspiration\, and the key actions necessary to stay committed to the ongoing work of anti-racism.\n\nRegistration \nFor ALL STAFF \n\nTuesday\, December 8\, 2:30 p.m. – 4 p.m.\n\nFor HEALTH SCIENCES \n\nTuesday\, November 17\, 2:30 p.m. – 4 p.m.\n\nFor BLACK STAFF \n\nTuesday\, December 1\, 2:30 p.m. – 4 p.m.\n\n* All sessions will be recorded and live captioned. \nContact Bryce Besser with questions\, bbesser@ucsd.ed \n 
URL:https://datascience.ucsd.edu/event/addressing-anti-blackness-how-to-sustain-a-culture-of-inclusion-equity-and-anti-racism-at-uc-san-diego/2020-12-08/
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DTSTART;TZID=America/Los_Angeles:20201208T170000
DTEND;TZID=America/Los_Angeles:20201208T180000
DTSTAMP:20260723T020952
CREATED:20201202T175418Z
LAST-MODIFIED:20201202T175418Z
UID:10000146-1607446800-1607450400@datascience.ucsd.edu
SUMMARY:Neuroscience in the Data Science Age
DESCRIPTION:Abstract:The brain is often likened to a symphony\, where 86 billion neurons are coordinating in an unfathomably complex electrochemical orchestra. However\, our brains are more like a symphony without a conductor: there is no leader orchestrating those 86 billion neurons! Despite this apparent chaos\, our brains usually just work (if we’re lucky!). My research lab leverages a data science approach to neuroscience in order to understand how these 86 billion neurons communicate with one another\, and to figure out when\, why\, and how that process breaks down. To do this\, we turn many massive\, disconnected neuroscience databases into coherent models for examining relationships across scales\, and to generate new research directions. Our approach is to combine brain imaging data with genetics\, electrical recordings from neurons\, and textual data from millions of peer-reviewed neuroscience publications. By putting those data into a common reference frame\, we can mine across datasets to find missing links and gaps in our knowledge. This approach allows us to algorithmically generate plausible hypotheses to better understanding human brain function\, development\, aging\, and disease. \nBio:Bradley Voytek is an Associate Professor in the Department of Cognitive Science\, the Halıcıoğlu Data Science Institute\, and the Neurosciences Graduate Program at UC San Diego. He is both an Alfred P. Sloan Neuroscience Research Fellow and a Kavli Fellow of the National Academies of Sciences\, as well as a founding faculty member of the UC San Diego Halıcıoğlu Data Science Institute and the Undergraduate Data Science program\, where he serves as Vice-Chair. After his PhD at UC Berkeley he joined Uber as their first data scientist\, when it was a 10-person startup\, where he helped build their data science strategy and team. His neuroscience research lab combines large-scale data science and machine learning to study how brain regions communicate with one another\, and how that communication changes with development\, aging\, and disease. He is an advocate for promoting science to the public\, and speaks extensively with students at all grade levels about the joys of scientific research and discovery. In addition to his academic publications\, his outreach work has appeared in outlets ranging from Scientific American and NPR to the San Diego Comic-Con. His most important contribution to science though is his book with fellow neuroscientist Tim Verstynen\, “Do Zombies Dream of Undead Sheep?”\, by Princeton University Press.Agenda=================– 4:45 – 5:00 pm — Arrival and socializing– 5:00 – 6:00 pm — TalkLinks to slides and videos of meetup presentations are available on the SDML GitHub repo https://github.com/SanDiegoMachineLearning/talks=================Questions?=================Join our slack channel or leave a comment below if you have any questions about the group or need clarification on anything.https://join.slack.com/t/sdmachinelearning/shared_invite/zt-6b0ojqdz-9bG7tyJMddVHZ3Zm9IajJA\n 
URL:https://datascience.ucsd.edu/event/neuroscience-in-the-data-science-age/
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201209T160000
DTEND;TZID=America/Los_Angeles:20201209T170000
DTSTAMP:20260723T020952
CREATED:20201208T221628Z
LAST-MODIFIED:20201208T221628Z
UID:10000288-1607529600-1607533200@datascience.ucsd.edu
SUMMARY:Design@Large Speaker Series: Data Stories\, the Information Reformation\, and COVID-19 by Benjamin Smarr
DESCRIPTION:Benjamin Smarr (UC San Diego)\nWednesday\, December 09\, 2020 at 4:00 P.M. \nAbstract: \nData Stories\, the Information Reformation\, and COVID-19 \nPersonal\, physiological data are becoming common. How do we pick information from this deluge of data? A deeper appreciation of the way biology makes use of time combine with the timeless human urge to share with stories\, not just numbers. Together\, these two lenses let us surf the deluge to make rapid progress in previously impossible-to-reach biomedical applications. In this talk\, we will see how classical circadian biology has sewn the seeds for a major upheaval in biomedical research\, in which COVID-19 seems likely to become a historic pivot. \nBiography: \nProf. Smarr got his PhD in Neurobiology and Behavior at the University of Washington before serving as an NIH postdoctoral fellow at Berkeley. Dr. Smarr’s work focuses on biological rhythms and neuroendocrinology\, which he approaches through collaboration with wearable device companies and communities wishing to collaborate to explore the data they generate about themselves. Dr. Smarr joined UCSD’s Dept. of Bioengineering early in 2020\,  has a joint appointment to the Halicioglu Data Science Institute\, and is the UCSD PI and technical lead on the largest public wearable-driven COVID-19 study: TemPredict.
URL:https://datascience.ucsd.edu/event/data-stories-the-information-reformation-and-covid-19/
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201209T190000
DTEND;TZID=America/Los_Angeles:20201209T210000
DTSTAMP:20260723T020952
CREATED:20201204T190221Z
LAST-MODIFIED:20201204T190221Z
UID:10000154-1607540400-1607547600@datascience.ucsd.edu
SUMMARY:DS3 Projects Committee Fall Showcase
DESCRIPTION:Hello all\, \nWe hope you have had a safe and relaxing Thanksgiving break. I am reaching out on behalf of the Data Science Student Society’s Projects Committee. This quarter\, we had a mix of in-house data science projects as well as industry collaborated projects. We would like to invite you to our project’s presentations on Wednesday\, December 9 from 7 PM – 9 PM PST. Students from a variety of majors and classes will be presenting data science projects they have been working on throughout the quarter\, and we’ve found that in the past\, having faculty there to give feedback was extremely helpful to our committee members. \nThis quarter’s project lineup includes (but is not limited to): \n\nApplying Neural Networks to Classify and Predict Biomolecules (partnership with RepurposeAI)\nInvestigating the Relationship between Twitter sentiment and Stock Price\nObject motion prediction from self-driving car data\nGoFundMe Donations NLP and Prediction Analysis\n\nLink to Zoom meeting: https://ucsd.zoom.us/j/92113763293 \nIf you’d like\, feel free to share this invitation with your colleagues\, postdocs\, grad students\, lab members\, etc. – all faculty at UC San Diego are invited! We hope to see you there! \nBest\, \nPeter Larcheveque – Projects Director \nArunav Gupta – Assistant Projects Director \nLulu Ricketts – Assistant Projects Director
URL:https://datascience.ucsd.edu/event/ds3-projects-committee-fall-showcase/
CATEGORIES:Showcase
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201211T160000
DTEND;TZID=America/Los_Angeles:20201211T170000
DTSTAMP:20260723T020952
CREATED:20201204T185420Z
LAST-MODIFIED:20201204T185420Z
UID:10000152-1607702400-1607706000@datascience.ucsd.edu
SUMMARY:2020 American Statistical Association Women in Statistics Social Hour
DESCRIPTION:A social event sponsored by the Caucus for Women in Statistics and the ASA Committee on Women in Statistics. Please join us on Friday\, December 11 at 4 p.m. ET to reconnect with folx you met at WSDS and make new friends! There will be trivia games\, games of chance\, great conversation and more. Please use this link to register.
URL:https://datascience.ucsd.edu/event/2020-american-statistical-association-women-in-statistics-social-hour/
CATEGORIES:Social Event
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201217T100000
DTEND;TZID=America/Los_Angeles:20201217T110000
DTSTAMP:20260723T020952
CREATED:20201215T185934Z
LAST-MODIFIED:20201215T185934Z
UID:10000289-1608199200-1608202800@datascience.ucsd.edu
SUMMARY:Thesis Proposal: Multi-Query Optimizations for Deep Learning Systems by Supun Nakandala
DESCRIPTION:Abstract: \nDeep learning (DL) is revolutionizing many fields. Major web companies are heavily relying on DL-based analytics\, and there is excitement among the wider industries and the sciences for adopting DL. However\, adopting DL in real-world applications is a non-trivial task. DL practitioners often have to iterate through complex stages of 1) data sourcing\, 2) model building\, and 3) model deploying. To overcome these bottlenecks\, a new breed of specialized software systems\, broadly referred to as Deep Learning Systems (e.g.\, TensorFlow\, PyTorch\, TVM)\, have emerged. The goal of these systems is to make DL adoption easier and efficient. \nHowever\, there is a significant limitation with the current generation DL systems: they don’t take into account the patterns and characteristics of end-to-end workloads. For example\, exploratory nature is a common characteristic of many end-to-end DL workloads. In practice\, this ends up generating workloads that launch several independent sub-tasks. However\, these sub-tasks often overlap substantially on data and computations. A prime example is model selection\, where one has to explore several different model configurations before picking the best one. As DL systems do not take into account such patterns\, they often miss significant opportunities for optimization. On the contrary\, relational database management systems\, a much older subfield\, has extensively explored how to optimize such workloads under the umbrella of multi-query optimization techniques. \nTo mitigate the above drawbacks of DL systems\, we propose developing novel multi-query optimization-inspired techniques for optimizing end-to-end workloads in DL systems. In this presentation\, I will present several examples of such optimization techniques that can accelerate and improve the resource efficiency of popular end-to-end DL workloads\, spanning data sourcing\, model building\, and model deployment stages. \nSupun Chathuranga Nakandala is inviting you to a scheduled Zoom meeting. \nTopic: Supun Chathuranga Nakandala’s Personal Meeting Room \nJoin Zoom Meeting https://ucsd.zoom.us/j/7296707725?pwd=WXcwM0UvNFBoUkZIRVNJNVd6YnUydz09 \nMeeting ID: 729 670 7725 \nPassword: qo4mlsys \nOne tap mobile +16699006833\,\,7296707725# US (San Jose) \n+12133388477\,\,7296707725# US (Los Angeles) \nDial by your location +1 669 900 6833 US (San Jose) \n+1 213 338 8477 US (Los Angeles) \n+1 669 219 2599 US (San Jose) \n888 475 4499 US Toll-free \n833 548 0276 US Toll-free \n833 548 0282 US Toll-free \n877 853 5257 US Toll-free \nMeeting ID: 729 670 7725 \nFind your local number: https://ucsd.zoom.us/u/a1EzQv2RK
URL:https://datascience.ucsd.edu/event/thesis-proposal-multi-query-optimizations-for-deep-learning-systems-by-supun-nakandala/
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DTSTART;TZID=America/Los_Angeles:20201217T130000
DTEND;TZID=America/Los_Angeles:20201217T140000
DTSTAMP:20260723T020952
CREATED:20201216T193508Z
LAST-MODIFIED:20201216T193508Z
UID:10000290-1608210000-1608213600@datascience.ucsd.edu
SUMMARY:Thesis Proposal: Simplifying Data Preparation for Machine Learning on Tabular Data by Vraj Shah
DESCRIPTION:Abstract: \nMachine learning (ML) over tabular data has become ubiquitous with applications in many domains. This success has led to the rise of ML platforms\, including automated ML (AutoML) platforms to manage the end-to-end ML workflow. The tedious grunt work involved in data preparation (prep) reduces data scientist productivity and slows down the ML development lifecycle\, which makes the automation of data prep even more critical. While many works have looked into automating feature engineering and model selection in the end-to-end ML workflows\, little attention has been paid to understanding the automated data prep for ML. Automating data prep remains challenging due to several reasons such as semantic gaps and lack of ways to objectively measure accuracy. \nIn this work\, we aim to address these challenges by abstracting data prep in terms of ML-readiness properties of the data to help simplify and automate them. In the first part of the talk\, we present how we leverage database schema information to reduce the burden in procuring datasets for ML. In the remaining part\, we first discuss our vision of systematic benchmarking and automating ML data prep by formalizing them as applied ML tasks. We then present a case study of our approach on a key data prep task: ML feature type inference. Our approach not only outperforms state-of-the-art AutoML tools but also improves the performance of the downstream model. We conclude by discussing our research plans to tackle another major ML data prep task. \nVraj Shah is inviting you to a scheduled Zoom meeting. \n  \nTopic: Vraj Shah Thesis Proposal \nTime: Dec 17\, 2020 01:00 PM Pacific Time (US and Canada) \nJoin Zoom Meeting \nhttps://ucsd.zoom.us/j/6922746284?pwd=SEtoYi9TQndtQVFuU0JubVpSSHB6dz09 \nMeeting ID: 692 274 6284 \nPassword: proposal \nOne tap mobile \n+16692192599\,\,6922746284# US (San Jose) \n+16699006833\,\,6922746284# US (San Jose) \nDial by your location \n+1 669 219 2599 US (San Jose) \n+1 669 900 6833 US (San Jose) \n+1 213 338 8477 US (Los Angeles) \nMeeting ID: 692 274 6284 \nFind your local number: https://ucsd.zoom.us/u/apq1x0zGX
URL:https://datascience.ucsd.edu/event/thesis-proposal-simplifying-data-preparation-for-machine-learning-on-tabular-data-by-vraj-shah/
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