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ASA Statistical Learning and Data Science
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Добавлен 28 окт 2021
Song Mei: Revisiting neural network approximation theory in the age of generative AI
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS)
January webinar: Revisiting neural network approximation theory in the age of generative AI
Record: January 3, 2025
Presenter: Song Mei is an assistant professor of statistics and EECS at UC Berkeley. He received his Ph. D. from Stanford in June 2020. His research lies at the intersection of statistics and machine learning. His recent research focuses on the theory of deep learning and generative AI models. Song has received an NSF career award, an Amazon Research Award, and a Google Research Scholar Award.
Abstract: Textbooks on deep learning theory primarily perceive neural networks as universal...
January webinar: Revisiting neural network approximation theory in the age of generative AI
Record: January 3, 2025
Presenter: Song Mei is an assistant professor of statistics and EECS at UC Berkeley. He received his Ph. D. from Stanford in June 2020. His research lies at the intersection of statistics and machine learning. His recent research focuses on the theory of deep learning and generative AI models. Song has received an NSF career award, an Amazon Research Award, and a Google Research Scholar Award.
Abstract: Textbooks on deep learning theory primarily perceive neural networks as universal...
Просмотров: 243
Видео
Weijie Su: How Statistics Can Advance Large Language Models: Fairness Alignment and Watermarking
Просмотров 2922 месяца назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) December webinar: How Statistics Can Advance Large Language Models: Fairness Alignment and Watermarking Record: December 3, 2024 Presenter: Weijie Su is an Associate Professor in the Wharton Statistics and Data Science Department and, by courtesy, in the Departments of Computer Information Science an...
Nathaniel O’Connell: A Comparison of Methods of Cross-Validation for Small Data
Просмотров 1322 месяца назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) November webinar: A Comparison of Methods of Cross-Validation for Small Data - Practical Guidance for Prediction Model Development with limited sample sizes Record: November 19, 2024 Presenter: Dr. Nathaniel (Nate) O’Connell is an assistant professor in the Department of Biostatistics and Data Scienc...
Runze Li: High-Dimensional Statistical Inference
Просмотров 3593 месяца назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) October webinar: High-Dimensional Statistical Inference Record: October 29, 2024 Presenter: Runze Li is the Eberly Family Chair Professor in Statistics, The Pennsylvania State University. He served as Co-Editor of Annals of Statistics from 2013 to 2015. Runze Li is a Fellow of IMS, ASA and AAAS. His ...
Jing Lei: Winners with Confidence: Discrete Argmin Inference with an Application to Model Selection
Просмотров 3004 месяца назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) September webinar: Winners with Confidence: Discrete Argmin Inference with an Application to Model Selection Record: September 24, 2024 Presenter: Jing Lei is Professor of Statistics & Data Science at Carnegie Mellon University. He received his Bachelor of Science degree from the School of Mathematic...
Emmanuel Candès: Statistical methods for assessing the factual accuracy of large language models
Просмотров 2 тыс.5 месяцев назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) August webinar: Statistical methods for assessing the factual accuracy of large language models Record: August 29, 2024 Presenter: Emmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, professor of electrical engineering (by courtesy), and a member of the Institute of Computationa...
Bikram Karmakar: A new paradigm for causal inference in the presence of unmeasured confounders
Просмотров 2386 месяцев назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) July webinar: A new paradigm for causal inference in the presence of unmeasured confounders by calibrating a resistant population's variance Record: July 30, 2024 Presenter: Bikram Karmakar is an Assistant Professor in the Statistics Department at University of Florida. Prof Karmakar teaches advanced...
Bei Jiang: Online Local Differential Private Quantile Inference
Просмотров 1067 месяцев назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) June webinar: Online Local Differential Private Quantile Inference Record: June 21, 2024 Presenter: Dr. Bei Jiang is an Associate Professor at the Department of Mathematical and Statistical Sciences of the University of Alberta, a Fellow and a Canada CIFAR AI chair affiliated with the Alberta Machine...
Andrej Risteski: The statistical cost of score-based losses
Просмотров 6988 месяцев назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) December webinar: Can Statistics Save Machine Learning from a Crisis? A Regression Approach to Peer Review in NeurIPS/ICML Record: May 30, 2024 Presenter: Andrej Risteski is an Assistant Professor at the Machine Learning Department in Carnegie Mellon University. Prior to that, he was a Norbert Wiener...
Bin Yu: Why Veridical Data Science? And How?
Просмотров 28210 месяцев назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) March webinar: Why Veridical Data Science? And How? Record: April 4, 2023 Presenter: Bin Yu is Chancellor's Distinguished Professor and Class of 1936 Second Chair in Statistics, EECS, and Computational Biology at UC Berkeley. Her research focuses on the practice and theory of statistical machine lear...
Mladen Kolar: Adaptive Stochastic Optimization with Constraints
Просмотров 24411 месяцев назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) February webinar: Adaptive Stochastic Optimization with Constraints Record: February 27, 2024 Presenter: Mladen Kolar is a professor in the Department of Data Sciences and Operations at the USC Marshall School of Business. Mladen earned his PhD in Machine Learning from Carnegie Mellon University in 2...
Andrew Gelman: Learning from mistakes
Просмотров 1,6 тыс.Год назад
Links mentioned in the talk: Election poll example: web.archive.org/web/20090326143823/www.fivethirtyeight.com/2009/03/how-did-white-people-vote.html Nudge example: statmodeling.stat.columbia.edu/2009/05/11/discussion_and/ statmodeling.stat.columbia.edu/2022/06/04/pizzagate-and-nudge-an-opportunity-lost/ This talk: statmodeling.stat.columbia.edu/2024/01/23/learning-from-mistakes-my-online-talk-...
Weijie Su: A Regression Approach to Peer Review in NeurIPS/ICML
Просмотров 333Год назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) December webinar: Can Statistics Save Machine Learning from a Crisis? A Regression Approach to Peer Review in NeurIPS/ICML Record: December 15, 2023 Presenter: Weijie Su is an Associate Professor at the University of Pennsylvania, with an appointment in the Wharton Statistics and Data Science Departm...
Glen Wright Colopy: The Pareto Principle in Data Science: Maximizing Value and Efficiency
Просмотров 392Год назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) November webinar: The Pareto Principle in Data Science: Maximizing Value and Efficiency Record: November 30, 2023 Presenter: Glen Wright Colopy is the Head of Data Science & Statistics at Wildfell, a startup specializing in custom software and data science solutions for the biotech and life science i...
Mengye Ren: Lifelong Learning in Structured Environments
Просмотров 272Год назад
American Statistical Association (ASA), Section on Statistical Learning and Data Science (SLDS) October webinar: Lifelong Learning in Structured Environments Record: October 26, 2023 Presenter: Mengye Ren is an assistant professor of computer science and data science at New York University (NYU). Before joining NYU, he was a visiting faculty researcher at Google Brain Toronto working with Prof....
Krishna Balasubramanian: Optimization-based analysis of sampling algorithms
Просмотров 219Год назад
Krishna Balasubramanian: Optimization-based analysis of sampling algorithms
Lucas Janson: Exact Conditional Independence Testing and Conformal Inference
Просмотров 724Год назад
Lucas Janson: Exact Conditional Independence Testing and Conformal Inference
Hongtu Zhu: Statistical Learning Methods for Neuroimaging Data Analysis with Applications
Просмотров 382Год назад
Hongtu Zhu: Statistical Learning Methods for Neuroimaging Data Analysis with Applications
Rina Foygel Barber: Stability of black-box algorithms
Просмотров 593Год назад
Rina Foygel Barber: Stability of black-box algorithms
Qiqi Deng: A Brief introduction for drug development and how biostatistician can contribute
Просмотров 230Год назад
Qiqi Deng: A Brief introduction for drug development and how biostatistician can contribute
Jason Klusowski: Pointwise Behavior of Recursive Partitioning
Просмотров 246Год назад
Jason Klusowski: Pointwise Behavior of Recursive Partitioning
George Michailidis: Statistical models for mixed frequency data in forecasting economic indicators
Просмотров 1,3 тыс.2 года назад
George Michailidis: Statistical models for mixed frequency data in forecasting economic indicators
Hui Zou: Sparse Convoluted Rank Regression in High Dimensions
Просмотров 3942 года назад
Hui Zou: Sparse Convoluted Rank Regression in High Dimensions
Barbara Day: How to conduct a successful job search and negotiate your best offer
Просмотров 1052 года назад
Barbara Day: How to conduct a successful job search and negotiate your best offer
Ryan Tibshirani: Delphi's Epidata Project
Просмотров 2052 года назад
Ryan Tibshirani: Delphi's Epidata Project
Anderson Ye Zhang: Spectral Clustering
Просмотров 1672 года назад
Anderson Ye Zhang: Spectral Clustering
Linglong Kong: Exploration and Optimization in Deep Reinforcement Learning
Просмотров 1432 года назад
Linglong Kong: Exploration and Optimization in Deep Reinforcement Learning
I love lucas b Johnson
Very inspirational!
👍
Thanks for sharing!
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On the topic of being an asshole when giving criticism. It's like Gelman says, you're best positioned to try and see through the delivery to the content but on the other hand as someone giving feedback it's important to be clear so that the other party doesn't have to do that work. It means that it's on everybody to try and communicate clearly but also for us to acknowledge that the rough delivery comes not from bad people but from people who are feeling something which motivated them to say something in the first place but that can pollute the message. Being shocking is useful to catch people's attention but especially once the dialogue is going you need to cut it out ASAP. But if we need to rely on shock to cut through noise then ideally you don't rely on that but rather find a way to make the environment less noisy so that consensus is enough to make the right conversation happen.
Very Good Presentation！
😒 "Promo sm"
Great talk!
Thank you for this very helpful overview!