Ian Waudby-Smith

57 posts

Ian Waudby-Smith

Ian Waudby-Smith

@ianws0

Postdoc @ UC Berkeley | statistics, probability, machine learning, privacy 🇨🇦

Katılım Temmuz 2020
278 Takip Edilen216 Takipçiler
Ian Waudby-Smith
Ian Waudby-Smith@ianws0·
@Yjg_oo There is some work out there on DP being used as a means to a statistical end (e.g. at the interface of privacy and robustness). In the above work, the end is "statistical inference for a population but with DP protections on the collected data".
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Yijie
Yijie@Yjg_oo·
@ianws0 In the past, the focus was on queries and private release of datasets. It appears that the stat community picked up DP for statistical procedures. Were there specific data attacking schemes that prompted this attention?Thank you!
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Ian Waudby-Smith
Ian Waudby-Smith@ianws0·
At ICML at 11am Hawaiian time, I'll have a poster on differentially private confidence sets at board 801. Come hang out if interested! Paper: arxiv.org/abs/2202.08728
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Edward Kennedy
Edward Kennedy@edwardhkennedy·
Very excited about this new paper by Tiger Zeng (tigerzhzeng.com) We study causal inference w/ high-dimensional discrete confounders We give new bias/variance results & minimax lower bounds, which characterize fundamental limits of causal inference in high dimensions
Edward Kennedy tweet mediaEdward Kennedy tweet mediaEdward Kennedy tweet mediaEdward Kennedy tweet media
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YJ Choe
YJ Choe@_Mr_YJ·
For the Stats crowd: unlike P-values, E-values (en.wikipedia.org/wiki/E-values) can be combined easily under arbitrary dependence. But can we say the same for their sequential analog, e-processes? Sadly the answer is *no*, motivating our recent work: arxiv.org/abs/2402.09698 (A thread)
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Chinmaya Kausik
Chinmaya Kausik@ChinmayaKausik·
Does anyone know if there is a matrix version of empirical Bernstein inequalities, as in this paper? I can use covering arguments to get one version, but that's not the "right" empirical equivalent of the matrix Bernstein inequality. arxiv.org/abs/0907.3740
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Ian Waudby-Smith
Ian Waudby-Smith@ianws0·
@sp_monte_carlo A boring construction: X_1, X_1, X_1, ... Perhaps you want to impose that (X_t)_t has infinite variation (otherwise desideratum 4 leads to constant martingales).
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Ian Waudby-Smith
Ian Waudby-Smith@ianws0·
And giving an oral presentation in room 316 happening now.
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apoorva.lal
apoorva.lal@Apoorva__Lal·
@pedrohcgs Either setup works well if you use screen space. Default window snapping on windows (esp on w11) is good, linux has i3, and macos has ... nothing (last time i checked). I've installed rectangle whenever I've had to use a mac rectangleapp.com
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Pedro H. C. Sant'Anna
Pedro H. C. Sant'Anna@pedrohcgs·
Question for #EconTwitter. I am deciding between two 32'' monitors and an ultrawide 40+'' monitor for my work desktop setup. What are the pros and cons of each? What should I get?
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Royal Statistical Society
Royal Statistical Society@RoyalStatSoc·
Join us in person or online for our Discussion Meeting next Tuesday, 23 May. Your comments are keenly invited on the paper ‘Estimating means of bounded random variables by betting'. Register for the meeting at rss.org.uk/training-event…
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krishn
krishn@KrishnRamesh·
our new home in Calgary 🙌🏽
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Blair Bilodeau
Blair Bilodeau@blairbilodeau·
I am on the job market for faculty and research scientist positions. I develop statistical theory and algorithms to make data-based decisions that balance the need for robustness in high-stakes settings with strong performance in practice. Some highlights below: 1/n
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Ian Waudby-Smith
Ian Waudby-Smith@ianws0·
@lakens @GregoryFaletto @LajeunesseLab This is true for simple settings (such as point nulls/alternatives in parametric problems) but in practice one might care about composite nulls/alternatives under nonparametric assumptions. For those settings, a bit more machinery is needed.
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Marc J. Lajeunesse
Marc J. Lajeunesse@LajeunesseLab·
There is tremendous risk in repeatedly analyzing data as it comes in… For example, in the absence of any effect, the p-values of repeated t-tests on a growing dataset will randomly walk between 1 and 0! Thanks to @lakens for inspiring this simulation! #RStats #dataviz
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Matteo Bonvini
Matteo Bonvini@bonv3·
My advisor @edwardhkennedy and I have posted an article on continuous trt effects estimation: arxiv.org/pdf/2207.11825… We study nonparam models where the dose-response curve has its own smoothness, which may differ from that of the outcome regression or cond dens of trt given X.
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Ron Yurko
Ron Yurko@Stat_Ron·
I find it hard to believe that 10 years ago I graduated high school to begin @CarnegieMellon - now I'm incredibly excited to share I will be an Assistant Teaching Professor @CMU_Stats! I owe everything to my amazing advisors, mentors, friends, & family for all of their support!
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