SDSCon 2022
SDSCon 2022
SDSCon 2022 is the fourth celebration of the statistics and data science community at MIT and beyond, organized by MIT’s Statistics and Data Science Center (SDSC).
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Calendar of Events
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IDSS Distinguished Seminars Mikhail Belkin (UC San Diego)
Neural networks: optimization, transition to linearity and deviations therefrom
Please join us on Monday, April 4 at 4:00pm for the IDSS Distinguished Speaker Seminar with Mikhail Belkin (UC San Diego).
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Stochastics and Statistics Seminar Li-Yang Tan, Stanford University
The query complexity of certification
Abstract: We study the problem of certification: given queries to an n-variable boolean function f with certificate complexity k and an input x, output a size-k certificate for f's value on x. This abstractly models a problem of interest in explainable machine learning, where we think of f as a blackbox model that we seek to…
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Stochastics and Statistics Seminar Caroline Uhler, MIT
Causal Representation Learning – A Proposal
Abstract: The development of CRISPR-based assays and small molecule screens holds the promise of engineering precise cell state transitions to move cells from one cell type to another or from a diseased state to a healthy state. The main bottleneck is the huge space of possible perturbations/interventions, where even with the breathtaking technological advances in…
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Stochastics and Statistics Seminar Yue M. Lu, Harvard University
Learning with Random Features and Kernels: Sharp Asymptotics and Universality Laws
Abstract: Many new random matrix ensembles arise in learning and modern signal processing. As shown in recent studies, the spectral properties of these matrices help answer crucial questions regarding the training and generalization performance of neural networks, and the fundamental limits of high-dimensional signal recovery. As a result, there has been growing interest in precisely…
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Beyond Fairness: Big Data, Racial Justice & Housing
Beyond Fairness: Big Data, Racial Justice & Housing
Please join us for the one-day symposium Beyond Fairness: Big Data, Racial Justice & Housing on Wednesday, April 27, 2022 from 9:00-4:30pm at the MIT Media Lab (E14-674). Organized by the ICSR Housing vertical team, this one-day symposium explores the intersection of data, algorithms and AI in relation to housing insecurity, home ownership and evictions.…
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Stochastics and Statistics Seminar Giedre Lideikyte Huber and Marta Pittavino, University of Geneva
Is quantile regression a suitable method to understand tax incentives for charitable giving? Case study from the Canton of Geneva, Switzerland
Abstract: Under the current Swiss law, taxpayers can deduct charitable donations from their individual’s taxable income subject to a 20%-ceiling. This deductible ceiling was increased at the communal and cantonal level from a previous 5%-ceiling in 2009. The goal of the reform was boosting charitable giving to non-profit entities. However, the effects of this reform,…
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SDSCon 2022
SDSCon 2022 is the fourth celebration of the statistics and data science community at MIT and beyond, organized by MIT’s Statistics and Data Science Center (SDSC).
Neural networks: optimization, transition to linearity and deviations therefrom
Mikhail Belkin (UC San Diego)
E18-304
Please join us on Monday, April 4 at 4:00pm for the IDSS Distinguished Speaker Seminar with Mikhail Belkin (UC San Diego).
The query complexity of certification
Li-Yang Tan, Stanford University
E18-304
Abstract: We study the problem of certification: given queries to an n-variable boolean function f with certificate complexity k and an input x, output a size-k certificate for f's value on x. This abstractly models a problem of interest in explainable machine learning, where we think of f as a blackbox model that we seek to…
Causal Representation Learning – A Proposal
Caroline Uhler, MIT
E18-304
Abstract: The development of CRISPR-based assays and small molecule screens holds the promise of engineering precise cell state transitions to move cells from one cell type to another or from a diseased state to a healthy state. The main bottleneck is the huge space of possible perturbations/interventions, where even with the breathtaking technological advances in…
Learning with Random Features and Kernels: Sharp Asymptotics and Universality Laws
Yue M. Lu, Harvard University
E18-304
Abstract: Many new random matrix ensembles arise in learning and modern signal processing. As shown in recent studies, the spectral properties of these matrices help answer crucial questions regarding the training and generalization performance of neural networks, and the fundamental limits of high-dimensional signal recovery. As a result, there has been growing interest in precisely…
Beyond Fairness: Big Data, Racial Justice & Housing
Please join us for the one-day symposium Beyond Fairness: Big Data, Racial Justice & Housing on Wednesday, April 27, 2022 from 9:00-4:30pm at the MIT Media Lab (E14-674). Organized by the ICSR Housing vertical team, this one-day symposium explores the intersection of data, algorithms and AI in relation to housing insecurity, home ownership and evictions.…
Is quantile regression a suitable method to understand tax incentives for charitable giving? Case study from the Canton of Geneva, Switzerland
Giedre Lideikyte Huber and Marta Pittavino, University of Geneva
E18-304
Abstract: Under the current Swiss law, taxpayers can deduct charitable donations from their individual’s taxable income subject to a 20%-ceiling. This deductible ceiling was increased at the communal and cantonal level from a previous 5%-ceiling in 2009. The goal of the reform was boosting charitable giving to non-profit entities. However, the effects of this reform,…
