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DTSTART:20150308T070000
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DTSTART;TZID=America/New_York:20170413T160000
DTEND;TZID=America/New_York:20170413T160000
DTSTAMP:20260407T092438
CREATED:20190627T212127Z
LAST-MODIFIED:20190627T212127Z
UID:10093-1492099200-1492099200@idss-stage.mit.edu
SUMMARY:Data-Driven Models in Power Systems
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/data-driven-models-in-power-systems-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170411T160000
DTEND;TZID=America/New_York:20170411T160000
DTSTAMP:20260407T092438
CREATED:20190627T212127Z
LAST-MODIFIED:20190627T212127Z
UID:10094-1491926400-1491926400@idss-stage.mit.edu
SUMMARY:Geometries of Word Embeddings
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/geometries-of-word-embeddings-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170410T093000
DTEND;TZID=America/New_York:20170410T093000
DTSTAMP:20260407T092438
CREATED:20190627T212127Z
LAST-MODIFIED:20190627T212127Z
UID:10095-1491816600-1491816600@idss-stage.mit.edu
SUMMARY:From Theory to Methodology and Data Analysis: A Study of Model (Mis)specification
DESCRIPTION:
URL:https://idss-stage.mit.edu/calendar/from-theory-to-methodology-and-data-analysis-a-study-of-model-misspecification-2/
LOCATION:46-3002\, United States
CATEGORIES:Conferences and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170407T110000
DTEND;TZID=America/New_York:20170407T110000
DTSTAMP:20260407T092438
CREATED:20190627T212127Z
LAST-MODIFIED:20190627T212127Z
UID:10096-1491562800-1491562800@idss-stage.mit.edu
SUMMARY:Sample-optimal inference\, computational thresholds\, and the methods of moments 
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/sample-optimal-inference-computational-thresholds-and-the-methods-of-moments-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170406T160000
DTEND;TZID=America/New_York:20170406T160000
DTSTAMP:20260407T092438
CREATED:20190627T212128Z
LAST-MODIFIED:20190627T212128Z
UID:10097-1491494400-1491494400@idss-stage.mit.edu
SUMMARY:A System Level Approach to Controller Synthesis
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/a-system-level-approach-to-controller-synthesis-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170404T160000
DTEND;TZID=America/New_York:20170404T160000
DTSTAMP:20260407T092438
CREATED:20190627T212132Z
LAST-MODIFIED:20190627T212132Z
UID:10098-1491321600-1491321600@idss-stage.mit.edu
SUMMARY:Capacity via Symmetry: Extensions and Practical Consequences
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/capacity-via-symmetry-extensions-and-practical-consequences-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170324T110000
DTEND;TZID=America/New_York:20170324T110000
DTSTAMP:20260407T092438
CREATED:20190627T212132Z
LAST-MODIFIED:20190627T212132Z
UID:10099-1490353200-1490353200@idss-stage.mit.edu
SUMMARY:Jagers-Nerman stable age distribution theory\, change point detection and power of two choices in evolving networks
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/jagers-nerman-stable-age-distribution-theory-change-point-detection-and-power-of-two-choices-in-evolving-networks-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170322T160000
DTEND;TZID=America/New_York:20170322T160000
DTSTAMP:20260407T092438
CREATED:20190627T212133Z
LAST-MODIFIED:20190627T212133Z
UID:10100-1490198400-1490198400@idss-stage.mit.edu
SUMMARY:Inference and Control in Routing Games
DESCRIPTION:
URL:https://idss-stage.mit.edu/calendar/inference-and-control-in-routing-games-2/
LOCATION:1-131\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170317T110000
DTEND;TZID=America/New_York:20170317T110000
DTSTAMP:20260407T092438
CREATED:20190627T212133Z
LAST-MODIFIED:20190627T212133Z
UID:10101-1489748400-1489748400@idss-stage.mit.edu
SUMMARY:Probabilistic factorizations of big tables and networks
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/probabilistic-factorizations-of-big-tables-and-networks-2/
LOCATION:32-141\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170313T150000
DTEND;TZID=America/New_York:20170313T163000
DTSTAMP:20260407T092438
CREATED:20190904T175423Z
LAST-MODIFIED:20190904T175423Z
UID:10617-1489417200-1489422600@idss-stage.mit.edu
SUMMARY:Learning from People
DESCRIPTION:Abstract:\nLearning from people represents a new and expanding frontier for data science. Two critical challenges in this domain are of developing algorithms for robust learning and designing incentive mechanisms for eliciting high-quality data. In this talk\, I describe progress on these challenges in the context of two canonical settings\, namely those of ranking and classification. In addressing the first challenge\, I introduce a class of “permutation-based” models that are considerably richer than classical models\, and present algorithms for estimation that are both rate-optimal and significantly more robust than prior state-of-the-art methods. I also discuss how these estimators automatically adapt and are simultaneously also rate-optimal over the classical models\, thereby enjoying a surprising a win-win in the bias-variance tradeoff. As for the second challenge\, I present a class of “multiplicative” incentive mechanisms\, and show that they are the unique mechanisms that can guarantee honest responses. Extensive experiments on a popular crowdsourcing platform reveal that the theoretical guarantees of robustness and efficiency indeed translate to practice\, yielding several-fold improvements over prior art. \nBio:\nNihar B. Shah is a PhD candidate in the EECS department at the University of California\, Berkeley. He is the recipient of the Microsoft Research PhD Fellowship 2014-16\, the Berkeley Fellowship 2011-13\, the IEEE Data Storage Best Paper and Best Student Paper Awards for the years 2011/2012\, and the SVC Aiya Medal from the Indian Institute of Science for the best master’s thesis in the department. His research interests include statistics and machine learning\, with a current focus on applications to learning from people.
URL:https://idss-stage.mit.edu/calendar/learning-from-people/
LOCATION:34-401 (Grier Room)\, The Stata Center (34-401)\, 50 Vassar Street\, Cambridge\, 02139\, United States
CATEGORIES:IDSS Special Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170310T110000
DTEND;TZID=America/New_York:20170310T110000
DTSTAMP:20260407T092438
CREATED:20190627T212133Z
LAST-MODIFIED:20190627T212133Z
UID:10102-1489143600-1489143600@idss-stage.mit.edu
SUMMARY:Robust Statistics\, Revisited 
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/robust-statistics-revisited-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20170308
DTEND;VALUE=DATE:20170309
DTSTAMP:20260407T092438
CREATED:20190627T212134Z
LAST-MODIFIED:20190627T212134Z
UID:10103-1488931200-1489017599@idss-stage.mit.edu
SUMMARY:Infrastructure\, Smart Cities & Transportation Workshop
DESCRIPTION:Some IDSS faculty are among the list of speakers at this workshop hosted by MIT Department of Civil and Environmental Engineering and Parsons.
URL:https://idss-stage.mit.edu/calendar/infrastructure-smart-cities-transportation-workshop-2/
LOCATION:Samberg Conference Center (E52 6th floor)\, United States
CATEGORIES:Conferences and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170307T160000
DTEND;TZID=America/New_York:20170307T160000
DTSTAMP:20260407T092438
CREATED:20190627T212134Z
LAST-MODIFIED:20190627T212134Z
UID:10104-1488902400-1488902400@idss-stage.mit.edu
SUMMARY:How the Chinese Government Fabricates Social Media Posts for Strategic Distraction\, not Engaged Arguments
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/how-the-chinese-government-fabricates-social-media-posts-for-strategic-distraction-not-engaged-arguments-2/
LOCATION:32-141\, United States
CATEGORIES:IDSS Distinguished Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170306T173000
DTEND;TZID=America/New_York:20170306T173000
DTSTAMP:20260407T092438
CREATED:20190627T212134Z
LAST-MODIFIED:20190829T195456Z
UID:10105-1488821400-1488821400@idss-stage.mit.edu
SUMMARY:Gene Regulation in Space and Time\, or From Ellipsoid Packing to Causal Inference - DaVinci Lecture (presented by Tau Beta Pi)
DESCRIPTION:Abstract: Although the genetic information in each cell within an organism is identical\, gene expression varies widely between different cell types. The quest to understand this phenomenon has led to many interesting mathematics problems. Experimental evidence suggests that the differential gene expression is related to the spatial organization of chromosomes in the cell nucleus. I will present a new model\, based on ellipsoid packing and causal inference\, that can link the 3d organization of chromosomes with gene regulation. Such models have important implications in understanding the mechanisms underlying cellular reprogramming events.
URL:https://idss-stage.mit.edu/calendar/gene-regulation-in-space-and-time-or-from-ellipsoid-packing-to-causal-inference-davinci-lecture-presented-by-tau-beta-pi-2/
LOCATION:4-237\, United States
CATEGORIES:IDSS Special Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170303T110000
DTEND;TZID=America/New_York:20170303T110000
DTSTAMP:20260407T092438
CREATED:20190627T212134Z
LAST-MODIFIED:20190627T212134Z
UID:10106-1488538800-1488538800@idss-stage.mit.edu
SUMMARY:Computing partition functions by interpolation
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/computing-partition-functions-by-interpolation-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170228T160000
DTEND;TZID=America/New_York:20170228T160000
DTSTAMP:20260407T092438
CREATED:20190627T212135Z
LAST-MODIFIED:20190627T212135Z
UID:10107-1488297600-1488297600@idss-stage.mit.edu
SUMMARY:Distributed Energy Resource Control and 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/distributed-energy-resource-control-and-network-optimization-2/
LOCATION:32-141\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170224T110000
DTEND;TZID=America/New_York:20170224T110000
DTSTAMP:20260407T092438
CREATED:20190627T212135Z
LAST-MODIFIED:20190627T212135Z
UID:10108-1487934000-1487934000@idss-stage.mit.edu
SUMMARY:Estimating the number of connected components of large graphs based on subgraph sampling
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/estimating-the-number-of-connected-components-of-large-graphs-based-on-subgraph-sampling-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170221T160000
DTEND;TZID=America/New_York:20170221T160000
DTSTAMP:20260407T092438
CREATED:20190627T212136Z
LAST-MODIFIED:20190627T212136Z
UID:10109-1487692800-1487692800@idss-stage.mit.edu
SUMMARY:Dynamic Learning in Strategic Pricing Games 
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/dynamic-learning-in-strategic-pricing-games-2/
LOCATION:E18-304\, United States
CATEGORIES:LIDS Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20170221
DTEND;VALUE=DATE:20170222
DTSTAMP:20260407T092438
CREATED:20190627T212136Z
LAST-MODIFIED:20190627T212136Z
UID:10110-1487635200-1487721599@idss-stage.mit.edu
SUMMARY:Data Science: Data to Insights
DESCRIPTION:MIT Professional Education and IDSS again offer “Data Science: Data to Insights\,” a six-week online course focusing on analytics.
URL:https://idss-stage.mit.edu/calendar/data-science-data-to-insights-3/
CATEGORIES:Online events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170217T110000
DTEND;TZID=America/New_York:20170217T110000
DTSTAMP:20260407T092438
CREATED:20190627T212136Z
LAST-MODIFIED:20190627T212136Z
UID:10111-1487329200-1487329200@idss-stage.mit.edu
SUMMARY:Causal Discovery in Systems with Feedback Cycles
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/causal-discovery-in-systems-with-feedback-cycles-2/
LOCATION:E18-304\, United States
CATEGORIES:Stochastics and Statistics Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170214T160000
DTEND;TZID=America/New_York:20170214T160000
DTSTAMP:20260407T092438
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:20260407T092438
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:20260407T092438
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:20260407T092438
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:20260407T092438
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:20260407T092438
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:20260407T092438
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:20260407T092438
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:20260407T092438
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:20260407T092438
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
END:VCALENDAR