SimonsTV

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Playlist: 20 videos
Playlist: 18 videos
Nov. 2022
Jessica Hullman (Northwestern University)
https://simons.berkeley.edu/events/law-society-fellow-talk
Law & Society Fellow Talk

Abstract: Research and development in computer science and statistics have produced increasingly sophisticated software interfaces for interactive visual data analysis as well as data communication. However, our understanding of how to design robust visualizations for data-driven inference remains limited by researchers' heavy reliance on small user studies and hunches about the role of visual representations in inference. Using examples from recent visualization research, this talk will motivate the need for better-defined objectives and theoretical approaches for measuring the value of a visualization for supporting exploratory data analysis or communication. This talk will discuss recent work in progress at the intersection of visualization and theory.

Bio: Jessica Hullman is the Ginni Rometty Associate Professor of Computer Science at Northwestern University. Her research addresses challenges that arise when people draw inductive inferences from data summaries. Hullman's work has contributed visualization techniques, applications, and evaluative frameworks for improving data-driven inference in applications like visual data analysis, data communication, privacy budget setting, and responsive design. Her current interests include how theorizing reasoning under uncertainty as mediated by representations of data could transform research and practice by providing insight into the value of a better interface. Hullman's work has received best paper awards at top visualization and HCI venues, and she has received a Microsoft Research Faculty Fellowship and NSF CAREER, Medium, and Small awards as PI, among others.

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Established in 2020, the Simons Institute's Law and Society Fellowships enhance Institute programs that address technologies with profound impacts on human society and with implications for ethics, law, and policy, by supporting a researcher within each who is focused on addressing the broader societal implications of the techniques and technologies addressed within these programs.

Law and Society Fellows participate in the Institute's programs and engage with visiting scientists. Additional contributions include an initial talk on the fellow’s work for visiting researchers at the Simons Institute; and a white paper on recommendations and findings.
Playlist: 51 videos
Mar. 2021
Amin Coja-Oghlan (Goethe University)
https://simons.berkeley.edu/talks/tbd-283
50 Years of Satisfiability: The Centrality of SAT in the Theory of Computing
Sep. 2020
Chelsea Finn (Stanford University)
https://simons.berkeley.edu/talks/tbd-214
Deep Reinforcement Learning
Playlist: 21 videos
Sep. 2019
Elette Boyle (IDC Herzliya), Henry Corrigan-Gibbs (Stanford University)
https://simons.berkeley.edu/talks/fully-linear-pcps
Probabilistically Checkable and Interactive Proof Systems
Aug. 2019
Emma Brunskill (Stanford University)
https://simons.berkeley.edu/talks/tba-92
Emerging Challenges in Deep Learning
The Boot Camp is intended to acquaint program participants with the key themes of the program. It will consist of four days of tutorial presentations, each with ample time for questions and discussion, as follows:
Playlist: 16 videos
An important development in the area of convex relaxations has been the introduction of systematic ways of strengthening them by lift-and-project techniques. This leads to several hierarchies of LP/SDP relaxations: Lovasz-Schrijver, Sherali-Adams and Sum of Squares (also known as the Lasserre hierarchy). The benefits and limitations of these hierarchies have been studied extensively over the last decade. Recently, strong negative results have been obtained, not only for specific hierarchies but even for the more general notion of extended formulations. In this workshop we investigate the power and limitations of LP/SDP hierarchies as well as general extended formulations, and their ties to convex algebraic geometry. We also explore tools and concepts from matrix analysis with strong connections to SDP formulations: matrix concentration, matrix multiplicative weight updates, and various notions of matrix rank. Finally, the workshop will cover related areas where these kinds of techniques are employed: sparsification, discrepancy and hyperbolic/real stable polynomials.
Playlist: 24 videos
Nov. 16 – Nov. 20, 2015
Playlist: 23 videos
Apr. 21 – Apr. 24, 2014
Playlist: 20 videos