andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-403 knowledge-graph by maker-knowledge-mining
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Introduction: Chris Wiggins sends along this . It’s a meetup at Davis Auditorium, CEPSR Bldg, Columbia University, on Wed 10 Nov (that’s tomorrow! or maybe today! depending on when you’re reading this), 6-8pm.
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same-blog 1 1.0 403 andrew gelman stats-2010-11-09-Society for Industrial and Applied Mathematics startup-math meetup
Introduction: Chris Wiggins sends along this . It’s a meetup at Davis Auditorium, CEPSR Bldg, Columbia University, on Wed 10 Nov (that’s tomorrow! or maybe today! depending on when you’re reading this), 6-8pm.
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Introduction: Here’s Bob’s talk from the NYC machine learning meetup . And here’s Stan himself:
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Introduction: We have a Stan users meetup for NYC. We’ll have monthly sessions where we can discuss modeling, success stories, pain points, and really have a chance for the user base and the developers to interact in NYC. The first meetup will be on Tuesday, 5/13. I’ll be giving a overview of Stan aimed at a general audience. If you’re interested, please register for the group / talk. Space is limited.
Introduction: That’s the title of my talk at Montana State University this Thursday (21 Mar). For those of you who happen to be in the area, it’s 3:30-5:00pm in the Procrastinator Theater. I’m also speaking in the statistics seminar from 11-12:15 in the Byker Auditorium in the Chemistry building. Topic: Causality and Statistical Learning . P.S. My title is a bit Geng-inspired, which reminds me that I recently came across this interesting mini-bio.
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Introduction: Xian sends along this link that might be of interest to some of you.
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same-blog 1 0.97570056 403 andrew gelman stats-2010-11-09-Society for Industrial and Applied Mathematics startup-math meetup
Introduction: Chris Wiggins sends along this . It’s a meetup at Davis Auditorium, CEPSR Bldg, Columbia University, on Wed 10 Nov (that’s tomorrow! or maybe today! depending on when you’re reading this), 6-8pm.
Introduction: My talks at Cambridge this Wed and Thurs in the department of Machine Learning . Powerpoints are here and here . Also some videos are here (but no videos of the “Nothing is Linear, Nothing is Additive” talk).
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Introduction: Xian sends along this link that might be of interest to some of you.
4 0.53297573 1821 andrew gelman stats-2013-04-24-My talk midtown this Friday noon (and at Columbia Monday afternoon)
Introduction: At the City University of New York Graduate Center, 365 Fifth Avenue (between 34th and 35th street), room 6002. The topic: causality and statistical learning . Announcement is here (scroll down). It says that if you would like to attend any event, please respond by emailing datamining@gc.cuny.edu I’m also giving a shorter talk on the same topic in the Sustainable Development Seminar Series 4pm Monday 29 Apr in room 407 International Affairs Bldg (at 118th St. and Amsterdam Ave.). It’s just a coincidence that I’m giving the same talk twice. I was asked at different times to speak for these groups. When someone asks me to speak, I let them pick from recent talks on the list .
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Introduction: Mike Jordan sends along this National Academies report on “big data.” This is not a research report but it could be interesting in that it conveys what are believed to be important technical challenges.
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Introduction: Chris Wiggins sends along this . It’s a meetup at Davis Auditorium, CEPSR Bldg, Columbia University, on Wed 10 Nov (that’s tomorrow! or maybe today! depending on when you’re reading this), 6-8pm.
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Introduction: WeatherSpark : prediction and observation quantiles, historic data, multiple predictors, zoomable, draggable, colorful, wonderful: Via Jure Cuhalev .
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Introduction: Burak Bayramli writes: I wanted to inform you on iPython Notebook technology – allowing markup, Python code to reside in one document. Someone ported one of your examples from ARM . iPynb file is actually a live document, can be downloaded and reran locally, hence change of code on document means change of images, results. Graphs (as well as text output) which are generated by the code, are placed inside the document automatically. No more referencing image files seperately. For now running notebooks locally require a notebook server, but that part can live “on the cloud” as part of an educational software. Viewers, such as nbviewer.ipython.org, do not even need that much, since all recent results of a notebook are embedded in the notebook itself. A lot of people are excited about this; Also out of nowhere, Alfred P. Sloan Foundation dropped a $1.15 million grant on the developers of ipython which provided some extra energy on the project. Cool. We’ll have to do that ex
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Introduction: Lyric Semiconductor posted: For over 60 years, computers have been based on digital computing principles. Data is represented as bits (0s and 1s). Boolean logic gates perform operations on these bits. A processor steps through many of these operations serially in order to perform a function. However, today’s most interesting problems are not at all suited to this approach. Here at Lyric Semiconductor, we are redesigning information processing circuits from the ground up to natively process probabilities: from the gate circuits to the processor architecture to the programming language. As a result, many applications that today require a thousand conventional processors will soon run in just one Lyric processor, providing 1,000x efficiencies in cost, power, and size. Om Malik has some more information, also relating to the team and the business. The fundamental idea is that computing architectures work deterministically, even though the world is fundamentally stochastic.
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Introduction: Jenny Anderson reports on a discussion of the practice of colleges preferential admission of children of alumni: [Richard] Kahlenberg citing research from his book “Affirmative Action for the Rich: Legacy Preferences in College Admissions” made the case that getting into good schools matters — 12 institutions making up less than 1 percent of the U.S. population produced 42 percent of government leaders and 54 percent of corporate leaders. And being a legacy helps improve an applicant’s chances of getting in, with one study finding that being a primary legacy — the son or daughter of an undergraduate alumnus or alumna — increases one’s chance of admission by 45.1 percent. I’d call that 45 percent but I get the basic idea. But then Jeffrey Brenzel of the Yale admissions office replied: “We turn away 80 percent of our legacies, and we feel it every day,” Mr. Brenzel said, adding that he rejected more offspring of the school’s Sterling donors than he accepted this year (
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