# SimonsTV

Our videos can also be found on YouTube.
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.

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.

==========================================

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: 15 videos

Feb. 2022

Jennifer Listgarten (UC Berkeley)

https://simons.berkeley.edu/talks/machine-learning-based-design-proteins

Learning from Interventions

https://simons.berkeley.edu/talks/machine-learning-based-design-proteins

Learning from Interventions

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

https://simons.berkeley.edu/talks/tbd-283

50 Years of Satisfiability: The Centrality of SAT in the Theory of Computing

Dec. 2020

Rahul Jain (USC)

https://simons.berkeley.edu/talks/tbd-241

Reinforcement Learning from Batch Data and Simulation

https://simons.berkeley.edu/talks/tbd-241

Reinforcement Learning from Batch Data and Simulation

Sep. 2020

Chelsea Finn (Stanford University)

https://simons.berkeley.edu/talks/tbd-214

Deep Reinforcement Learning

https://simons.berkeley.edu/talks/tbd-214

Deep Reinforcement Learning

Feb. 2020

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

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

https://simons.berkeley.edu/talks/tba-92

Emerging Challenges in Deep Learning

Apr. 2018

S. Murray Sherman, University of Chicago

https://simons.berkeley.edu/talks/s-murray-sherman-4-18-18

Computational Theories of the Brain

https://simons.berkeley.edu/talks/s-murray-sherman-4-18-18

Computational Theories of the Brain

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

Mar. 2017

Tom Griffiths, UC Berkeley

Representation Learning

https://simons.berkeley.edu/talks/tom-griffiths-2017-3-29

Representation Learning

https://simons.berkeley.edu/talks/tom-griffiths-2017-3-29

Apr. 25 – Apr. 26, 2016

Playlist: 9 videos

Nov. 16 – Nov. 20, 2015

Playlist: 23 videos

Apr. 21 – Apr. 24, 2014

Playlist: 20 videos