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DTSTART;TZID=America/New_York:20170214T160000
DTEND;TZID=America/New_York:20170214T160000
DTSTAMP:20260407T092422
CREATED:20190627T212136Z
LAST-MODIFIED:20190627T212136Z
UID:10112-1487088000-1487088000@idss-stage.mit.edu
SUMMARY:An Information Theoretic Perspective on the ExplorationExploitation Tradeoff
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/an-information-theoretic-perspective-on-the-explorationexploitation-tradeoff-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170213T160000
DTEND;TZID=America/New_York:20170213T160000
DTSTAMP:20260407T092422
CREATED:20190627T212137Z
LAST-MODIFIED:20190904T175906Z
UID:10113-1487001600-1487001600@idss-stage.mit.edu
SUMMARY:Towards a Theory of Fairness in Machine Learning
DESCRIPTION:Abstract:  Algorithm design has moved from being a tool used exclusively for designing systems to one used to present people with personalized content\, advertisements\, and other economic opportunities. Massive amounts of information is recorded about people’s online behavior including the websites they visit\, the advertisements they click on\, their search history\, and their IP address. Algorithms then use this information for many purposes: to choose which prices to quote individuals for airline tickets\, which advertisements to show them\, and even which news stories to promote. These systems create new challenges for algorithm design. When a person’s behavior influences the prices they may face in the future\, they may have a strong incentive to modify their behavior to improve their long-term utility; therefore\, these algorithms’ performance should be resilient to strategic manipulation. Furthermore\, when an algorithm makes choices that affect people’s everyday lives\, the effects of these choices raise ethical concerns such as whether the algorithm’s behavior violates individuals’ privacy or whether the algorithm treats people fairly. \nMachine learning algorithms in particular have received much attention for exhibiting bias\, or unfairness\, in a large number of contexts. In this talk\, I will describe my recent work on developing a definition of fairness for machine learning. One definition of fairness\, encoding the notion of ‘fair equality of opportunity’\, informally\, states that if one person has higher expected quality than another person\, the higher quality person should be given at least as much opportunity as the lower quality person. I will present a result characterizing the performance degradation of algorithms\, which satisfy this condition in the contextual bandits setting. To complement these theoretical results\, I then present the results of several empirical evaluations of fair algorithms. \nI will also briefly describe my work on designing algorithms whose performance guarantees are resilient to strategic manipulation of their inputs\, and machine learning for optimal auction design. \nBio: Jamie Morgenstern is a Warren Center postdoctoral fellow in Computer Science and Economics at the University of Pennsylvania. She received her Ph.D. in Computer Science from Carnegie Mellon University in 2015\, and her B.S. in Computer Science and B.A. in Mathematics from the University of Chicago in 2010. Her research focuses on machine learning for mechanism design\, fairness in machine learning\, and algorithmic game theory. She received a Microsoft Women’s Research Scholarship\, an NSF Graduate Research Fellowship\, and a Simons Award for Graduate Students in Theoretical Computer Science.
URL:https://idss-stage.mit.edu/calendar/towards-a-theory-of-fairness-in-machine-learning-2/
LOCATION:32-G449 (Kiva)\, United States
CATEGORIES:IDSS Special Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170210T110000
DTEND;TZID=America/New_York:20170210T110000
DTSTAMP:20260407T092422
CREATED:20190627T212137Z
LAST-MODIFIED:20190627T212137Z
UID:10114-1486724400-1486724400@idss-stage.mit.edu
SUMMARY:Slope meets Lasso in sparse linear regression
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/slope-meets-lasso-in-sparse-linear-regression-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170203T110000
DTEND;TZID=America/New_York:20170203T110000
DTSTAMP:20260407T092422
CREATED:20190627T212137Z
LAST-MODIFIED:20190627T212137Z
UID:10115-1486119600-1486119600@idss-stage.mit.edu
SUMMARY:Non-classical Berry-Esseen inequality and accuracy of the weighted bootstrap
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/non-classical-berry-esseen-inequality-and-accuracy-of-the-weighted-bootstrap-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20170203
DTEND;VALUE=DATE:20170204
DTSTAMP:20260407T092422
CREATED:20190627T212137Z
LAST-MODIFIED:20190627T212137Z
UID:10116-1486080000-1486166399@idss-stage.mit.edu
SUMMARY:Women in Data Science (WiDS) Conference
DESCRIPTION:This conference will bring together local academic leaders\, industrial professionals\, and students to hear about the latest data science-related research in a number of domains; to learn how companies are leveraging data science for success; and to connect with potential mentors\, collaborators\, and others in the field.
URL:https://idss-stage.mit.edu/calendar/women-in-data-science-wids-conference-2/
LOCATION:Microsoft NERD Center\, Cambridge\, United States
CATEGORIES:Conferences and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20170202
DTEND;VALUE=DATE:20170204
DTSTAMP:20260407T092422
CREATED:20190627T212138Z
LAST-MODIFIED:20190627T212138Z
UID:10117-1485993600-1486166399@idss-stage.mit.edu
SUMMARY:LIDS Student Conference
DESCRIPTION:This a student-organized\, student-run conference provides an opportunity for graduate students to present their research to peers\, as well as to the community at large.
URL:https://idss-stage.mit.edu/calendar/lids-student-conference-3/
LOCATION:32-141\, United States
CATEGORIES:Conferences and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161213T160000
DTEND;TZID=America/New_York:20161213T160000
DTSTAMP:20260407T092422
CREATED:20190627T212143Z
LAST-MODIFIED:20190627T212143Z
UID:10118-1481644800-1481644800@idss-stage.mit.edu
SUMMARY:The Impact of Expanding Medicaid: Evidence from the Oregon Health Insurance Experiment 
DESCRIPTION:IDSS Distinguished Seminars is a monthly lecture series featuring prominent global leaders and academics sharing research in areas that include social networks\, causal inference\, data privacy\, computational social science and other areas that are impacted by the emergence of big data.  
URL:https://idss-stage.mit.edu/calendar/the-impact-of-expanding-medicaid-evidence-from-the-oregon-health-insurance-experiment-2/
LOCATION:32-141\, United States
CATEGORIES:IDSS Distinguished Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161202T110000
DTEND;TZID=America/New_York:20161202T110000
DTSTAMP:20260407T092422
CREATED:20190627T212143Z
LAST-MODIFIED:20190627T212143Z
UID:10119-1480676400-1480676400@idss-stage.mit.edu
SUMMARY:Shotgun Assembly of Graphs
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/shotgun-assembly-of-graphs-2/
LOCATION:25-111\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161129T160000
DTEND;TZID=America/New_York:20161129T160000
DTSTAMP:20260407T092422
CREATED:20190627T212143Z
LAST-MODIFIED:20190627T212143Z
UID:10120-1480435200-1480435200@idss-stage.mit.edu
SUMMARY:Estimating High-Dimensional Autoregressive Point Processes
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/estimating-high-dimensional-autoregressive-point-processes-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161122T160000
DTEND;TZID=America/New_York:20161122T160000
DTSTAMP:20260407T092422
CREATED:20190627T212143Z
LAST-MODIFIED:20190627T212143Z
UID:10121-1479830400-1479830400@idss-stage.mit.edu
SUMMARY:Locality and Message Passing in Network Optimization
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/locality-and-message-passing-in-network-optimization-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161118T110000
DTEND;TZID=America/New_York:20161118T110000
DTSTAMP:20260407T092422
CREATED:20190627T212143Z
LAST-MODIFIED:20190627T212143Z
UID:10122-1479466800-1479466800@idss-stage.mit.edu
SUMMARY:Interpretable prediction models for network-linked data
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/interpretable-prediction-models-for-network-linked-data-2/
LOCATION:32-141\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161108T160000
DTEND;TZID=America/New_York:20161108T160000
DTSTAMP:20260407T092422
CREATED:20190627T212144Z
LAST-MODIFIED:20190627T212144Z
UID:10123-1478620800-1478620800@idss-stage.mit.edu
SUMMARY:IDSS Distinguished Seminar 
DESCRIPTION:IDSS Distinguished Seminars is a monthly lecture series featuring prominent global leaders and academics sharing research in areas that include social networks\, causal inference\, data privacy\, computational social science and other areas that are impacted by the emergence of big data.  
URL:https://idss-stage.mit.edu/calendar/idss-distinguished-seminar-3/
LOCATION:32-141\, United States
CATEGORIES:IDSS Distinguished Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161104T110000
DTEND;TZID=America/New_York:20161104T110000
DTSTAMP:20260407T092422
CREATED:20190627T212144Z
LAST-MODIFIED:20190627T212144Z
UID:10124-1478257200-1478257200@idss-stage.mit.edu
SUMMARY:Stochastics and Statistics Seminar Series
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/stochastics-and-statistics-seminar-series-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161101T160000
DTEND;TZID=America/New_York:20161101T160000
DTSTAMP:20260407T092422
CREATED:20190627T212144Z
LAST-MODIFIED:20190627T212144Z
UID:10125-1478016000-1478016000@idss-stage.mit.edu
SUMMARY:Community Detection in Networks: Algorithms\, Complexity\, and Information Limits
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/community-detection-in-networks-algorithms-complexity-and-information-limits-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161028T110000
DTEND;TZID=America/New_York:20161028T110000
DTSTAMP:20260407T092422
CREATED:20190627T212145Z
LAST-MODIFIED:20190627T212145Z
UID:10126-1477652400-1477652400@idss-stage.mit.edu
SUMMARY:Matrix estimation by Universal Singular Value Thresholding
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/matrix-estimation-by-universal-singular-value-thresholding-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161025T160000
DTEND;TZID=America/New_York:20161025T160000
DTSTAMP:20260407T092422
CREATED:20190627T212145Z
LAST-MODIFIED:20190627T212145Z
UID:10127-1477411200-1477411200@idss-stage.mit.edu
SUMMARY:Deep Submodular Functions: Learning and Applications in Data Science
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/deep-submodular-functions-learning-and-applications-in-data-science-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161021T110000
DTEND;TZID=America/New_York:20161021T110000
DTSTAMP:20260407T092422
CREATED:20190627T212146Z
LAST-MODIFIED:20190627T212146Z
UID:10128-1477047600-1477047600@idss-stage.mit.edu
SUMMARY:On The Asymptotic Performance of fq-regularized LeastSquares
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/on-the-asymptotic-performance-of-fq-regularized-leastsquares-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161018T160000
DTEND;TZID=America/New_York:20161018T160000
DTSTAMP:20260407T092422
CREATED:20190627T212146Z
LAST-MODIFIED:20190627T212146Z
UID:10129-1476806400-1476806400@idss-stage.mit.edu
SUMMARY:The Moral Character of Cryptographic Work
DESCRIPTION:IDSS Distinguished Seminars is a monthly lecture series featuring prominent global leaders and academics sharing research in areas that include social networks\, causal inference\, data privacy\, computational social science and other areas that are impacted by the emergence of big data.  
URL:https://idss-stage.mit.edu/calendar/the-moral-character-of-cryptographic-work-2/
LOCATION:32-141\, United States
CATEGORIES:IDSS Distinguished Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161014T110000
DTEND;TZID=America/New_York:20161014T110000
DTSTAMP:20260407T092422
CREATED:20190627T212146Z
LAST-MODIFIED:20190627T212146Z
UID:10130-1476442800-1476442800@idss-stage.mit.edu
SUMMARY:Eigenvectors of Orthogonally Decomposable Functions and Applications
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/eigenvectors-of-orthogonally-decomposable-functions-and-applications-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161011T160000
DTEND;TZID=America/New_York:20161011T160000
DTSTAMP:20260407T092422
CREATED:20190627T212146Z
LAST-MODIFIED:20190627T212146Z
UID:10131-1476201600-1476201600@idss-stage.mit.edu
SUMMARY:Innovations for the 21st Century Electricity Grid
DESCRIPTION:IDSS Distinguished Seminars is a monthly lecture series featuring prominent global leaders and academics sharing research in areas that include social networks\, causal inference\, data privacy\, computational social science and other areas that are impacted by the emergence of big data.  
URL:https://idss-stage.mit.edu/calendar/innovations-for-the-21st-century-electricity-grid-2/
LOCATION:32-141\, United States
CATEGORIES:IDSS Distinguished Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161007T110000
DTEND;TZID=America/New_York:20161007T110000
DTSTAMP:20260407T092422
CREATED:20190627T212146Z
LAST-MODIFIED:20190627T212146Z
UID:10132-1475838000-1475838000@idss-stage.mit.edu
SUMMARY:Invertibility and Condition Number of Sparse Random Matrices
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/invertibility-and-condition-number-of-sparse-random-matrices-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161004T160000
DTEND;TZID=America/New_York:20161004T160000
DTSTAMP:20260407T092422
CREATED:20190627T212147Z
LAST-MODIFIED:20190627T212147Z
UID:10133-1475596800-1475596800@idss-stage.mit.edu
SUMMARY:Fiber-Optic Communication via the Nonlinear Fourier Transform
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/fiber-optic-communication-via-the-nonlinear-fourier-transform-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20161004
DTEND;VALUE=DATE:20161005
DTSTAMP:20260407T092422
CREATED:20190627T212147Z
LAST-MODIFIED:20190627T212147Z
UID:10134-1475539200-1475625599@idss-stage.mit.edu
SUMMARY:Data Science: Data to Insights
DESCRIPTION:MIT Professional Education partners with IDSS to offer this new\, six-week online course focusing on analytics.
URL:https://idss-stage.mit.edu/calendar/data-science-data-to-insights-4/
CATEGORIES:Online events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160930T110000
DTEND;TZID=America/New_York:20160930T110000
DTSTAMP:20260407T092422
CREATED:20190627T212148Z
LAST-MODIFIED:20190627T212148Z
UID:10135-1475233200-1475233200@idss-stage.mit.edu
SUMMARY:Theory to gain insight and inform practice: re-run of IMS Rietz Lecture\, 2016
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/theory-to-gain-insight-and-inform-practice-re-run-of-ims-rietz-lecture-2016-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160927T160000
DTEND;TZID=America/New_York:20160927T160000
DTSTAMP:20260407T092422
CREATED:20190627T212148Z
LAST-MODIFIED:20190627T212148Z
UID:10136-1474992000-1474992000@idss-stage.mit.edu
SUMMARY:Optimization Problems Involving Permutations
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/optimization-problems-involving-permutations-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20160922
DTEND;VALUE=DATE:20160924
DTSTAMP:20260407T092422
CREATED:20190627T212148Z
LAST-MODIFIED:20190724T184801Z
UID:10137-1474502400-1474675199@idss-stage.mit.edu
SUMMARY:Institute for Data\, Systems\, and Society Launch
DESCRIPTION:This two-day “launch” event celebrated the inaugural year of the Institute for Data\, Systems\, and Society (IDSS) and set the stage for this new\, multi-disciplinary endeavor moving forward. The launch brought together thought leaders from academia\, industry\, and government to discuss the challenges and opportunities for research at the forefront of society’s greatest challenges. \nIDSS’s mission is to address complex societal challenges through the advancement of education and research at the intersections of statistics and data science\, information and decision systems\, engineering\, and social sciences. Energy systems\, health analytics\, urban sciences\, financial systems\, and social networks: society’s greatest challenges emerge in these several domains\, as well as in interactions between them. To provide answers to these critical challenges\, IDSS fosters research utilizing vast amounts of available data\, an in-depth understanding of fundamental engineering systems\, and the investigation of social and institutional behaviors. \n  \nOpening Remarks\n \nMIT President L. Rafael Reif & Professor Munther Dahleh\, Director of the Institute for Data\, Systems\, and Society\nSession 1: The Future of Voting \nThe role of technology in voting has gained increasing prominence over the past decade\, creating interdisciplinary collaborations between political\, computer\, and data scientists. Voting data contains an abundance of information that goes beyond the actual vote. This session looked at the complexity of voting\, the usability of computing technologies (such as cryptography) in designing future voting systems\, and how data is playing a role in understanding and predicting voting patterns and the outcome of elections.   \n  \n\nModerator: Professor Charles Stewart\, MIT\n \n \n\nKeynote: Mr. Nate Silver\, fivethirtyeight.com\n \n \n\nProfessor Michael Alvarez\, Caltech\n \n \n\nMs. Kassia DeVorsey\, Chief Analytics Officer\, Messina Group Analytics\nSession 2: Data-Driven Policy \nWhile communities are collecting more data than ever before to measure effects of public policy\, such data sets tend to be quite small. With the absence of a control group\, the assessment of existing policies and the design of new ones utilizing such data bring new challenges to statistics and data science. This panel explored such challenges and highlighted how data analysis has been quite effective in some applications.   \n  \n\nModerator: Professor Alberto Abadie\, MIT\n \n \n\nKeynote: Professor Enrico Giovannini\, University of Rome Tor Vergata\n  \nSession 3: Risk in Financial Systems \nRecent research has been successful in deriving abstracted models of the interconnected financial systems that quantify systemic risk and address cascaded failures of such systems. However\, combining such models with recorded data for the purpose of monitoring and mitigation continues to be a major research and practical challenge. This session discussed such challenges\, as well as the progress that has been made.   \n  \n\nModerator: Professor Asu Ozdaglar\, MIT\n \n \n\nKeynote: Professor Bengt Holmstrom\, MIT\nSession 4: Social Networks \nSocial networks through social media have brought to bear very large data representing people’s preferences and opinions\, and have highlighted effective incentive mechanisms. Such networks also impact and inform a variety of complex systems in our society. Such data has brought in new security and privacy challenges that have occupied much of the research in data science. This panel looked at new opportunities for understanding social networks and human behavior\, as well as technological methods for ensuring security and privacy. \n  \n\nRemarks by Professor Ian A. Waitz\, Dean of the School of Engineering\n  \n\nModerator: Professor Ali Jadbabaie\, MIT\n  \n\nProfessor Jon Kleinberg\, Cornell University\n \n \n\nProfessor Matthew Jackson\, Stanford University\n \n \n\nDr. Jeannette M. Wing\, Microsoft Research\n  \n\nDr. Cynthia Dwork\, Microsoft Research\n  \n\nQuestion and Answer\nSession 5: Future Electric Grid\, 3:00pm-4:00pm\nThe electric grid presents some of the most challenging engineering\, social\, and economic challenges of the future. With increased demands on electricity and increased penetration of renewable sources\, the need for new innovations in dynamic demand response\, spot markets\, and distributed control is rapidly increasing. This session discussed some of these challenges and current work. \n  \n\nModerator: Professor Bob Armstrong\, MIT\n \n \n\nProfessor William Hogan\, Harvard University\n \n \n\nProfessor Michael Greenstone\, University of Chicago\n \n \n\nProfessor Sally Benson\, Stanford University\n \n \n\nProfessor Steven Low\, Caltech\nSession 6: Student Session\, 4:30pm-5:15pm \n\nStudent Session Chair: Professor Sandy Pentland\, MIT\n\nSession 7: Analyzing our Health\nThe collection\, aggregation\, and analysis of medical data presents possibilities for future healthcare developments\, including opportunities for personalized medicine and patient care. The use of big data in medicine also raises serious questions about patient privacy. This session discussed ways in which the practice of medicine is being transformed by data. \n  \n\nRemarks by Professor Melissa Nobles\, Dean of the School of Humanities\, Arts\, and Social Sciences\, MIT\, 9:00am\n \n \n\nKeynote: Dr. DJ Patil\, U.S. Office of Science and Technology Policy\n \n \n\nModerator: Professor Peter Szolovits\, MIT\n \n \n\nDr. John Halamka\, MD\, Chief Information Officer\, Beth Israel Deaconess Medical Center\n \n \n\nProfessor Deborah Estrin\, Cornell Tech\n \n \n\nDr. Elazer Edelman\, MD\, Brigham & Women’s Hospital & Professor of Medicine at Harvard Medical School of Medicine (HMS) and MIT Health Sciences and Technology Program (HST).\nSession 8: Driving Smart Cities forward \nCities will become increasingly interconnected through an ever-expanding “internet of things\,” allowing governments\, urban planners and engineers access to massive amounts of data about urban life. This data is being used to design\, plan\, and structure cities in the United States and around the world. This session sought to explore the many facets of smart-cities research\, design\, planning\, and transportation. \n  \n\nModerator: Professor Sarah Williams\, MIT\n \n \n\nKeynote: Dr. Steven Koonin\, NYU\n \n \n\nProfessor Rob Kitchin\, Maynooth University\n \n \n\nProfessor Balaji Prabhakar\, Stanford University\n \n \n\nProfessor Susan Crawford\, Harvard Law School\n \n \n\nProfessor Alexandre Bayen\, UC Berkeley\nSession 9: From Applications To Theory\, 1:30pm-2:30pm\nWhile applications have their own nuances\, there are overarching challenges that need to be identified and addressed. These include\, among others\, fundamental questions in prediction\, robustness/risk\, computation\, system architecture\, and privacy. This session addressed some of the emerging challenges in these foundational fields in this new era of large data and complex systems. \n  \n\nModerator: Caroline Uhler\, MIT\n \n \n\nProfessor Allen Tannenbaum\, Stony Brook University\n \n \n\nProfessor Elchanan Mossel\, MIT\n \n \n\nProfessor David Tse\, Stanford University\n \n \n\nProfessor Vincent Blondel\, Rector\, Université catholique de Louvain
URL:https://idss-stage.mit.edu/calendar/institute-for-data-systems-and-society-launch/
LOCATION:MIT Media Lab (E14-674)\, United States
CATEGORIES:Conferences and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160916T110000
DTEND;TZID=America/New_York:20160916T110000
DTSTAMP:20260407T092422
CREATED:20190627T212152Z
LAST-MODIFIED:20190627T212152Z
UID:10138-1474023600-1474023600@idss-stage.mit.edu
SUMMARY:Less is more: optimal learning by subsampling and regularization
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/less-is-more-optimal-learning-by-subsampling-and-regularization-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160915T110000
DTEND;TZID=America/New_York:20160915T110000
DTSTAMP:20260407T092422
CREATED:20190627T212152Z
LAST-MODIFIED:20190829T195738Z
UID:10139-1473937200-1473937200@idss-stage.mit.edu
SUMMARY:Duration and deadline differentiated electricity demand: a model of flexible demand Speaker
DESCRIPTION:
URL:https://idss-stage.mit.edu/calendar/duration-and-deadline-differentiated-electricity-demand-a-model-of-flexible-demand-speaker-2/
LOCATION:E18-304\, United States
CATEGORIES:IDSS Special Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160913T160000
DTEND;TZID=America/New_York:20160913T160000
DTSTAMP:20260407T092422
CREATED:20190627T212153Z
LAST-MODIFIED:20190627T212153Z
UID:10140-1473782400-1473782400@idss-stage.mit.edu
SUMMARY:Geometric Optimization
DESCRIPTION:The LIDS Seminar Series features distinguished speakers in the information and decision sciences who provide an overview of a research area\, as well as exciting recent progress in that area. Intended for a broad audience\, seminar topics span the areas of communications\, computation\, control\, learning\, networks\, probability and statistics\, optimization\, and signal processing. 
URL:https://idss-stage.mit.edu/calendar/geometric-optimization-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160909T110000
DTEND;TZID=America/New_York:20160909T110000
DTSTAMP:20260407T092422
CREATED:20190627T212153Z
LAST-MODIFIED:20190627T212153Z
UID:10141-1473418800-1473418800@idss-stage.mit.edu
SUMMARY:Couplings of Particle Filters
DESCRIPTION:The Stochastics and Statistics Seminar is a weekly meeting organized by the Statistics and Data Science Center (SDSC). It consists of a series of one-hour presentations by worldwide leaders making cutting edge contributions to methodological and theoretical advances in data science. These fields include probability\, statistics\, optimization\, and applied mathematics. The seminar also regularly features experts in applications domains such as biology or engineering. This intellectual diversity has contributed to the organic assembly of a dynamic and diverse audience articulated around a core group composed of faculty\, postdocs and graduate students from different department and affiliated with IDSS. Every week\, this audience is supplemented by a large number—often more than doubled—of attendees from all of MIT reflecting the interdisciplinary nature of the stochastics and statistics seminar. 
URL:https://idss-stage.mit.edu/calendar/couplings-of-particle-filters-2/
LOCATION:32-141\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
END:VCALENDAR