Ian Waudby-Smith

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

[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".

[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: https://t.co/cnQYIG0owu

[Ian Waudby-Smith @ianws0]

@edwardhkennedy Tiger is incredible

[Edward Kennedy @edwardhkennedy]

Very excited about this new paper by Tiger Zeng (https://t.co/fwyuSRaazD)

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

[YJ Choe @_Mr_YJ]

For the Stats crowd: unlike P-values, E-values (https://t.co/nhHuBKQBvp) 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: https://t.co/ChO8uwYzD4

(A thread)

[Ian Waudby-Smith @ianws0]

@RdeHeide Wonderful news and well-deserved

[Ian Waudby-Smith @ianws0]

@ChinmayaKausik Theorem 5.6 might be of interest. https://t.co/frcU7u5Neh

[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).

[Ian Waudby-Smith @ianws0]

@Apoorva__Lal Yussef Dayes!

Here are some of my fav tracks. The first one takes a while to heat up but it's so worth the wait.

https://t.co/BaIOEcHFn0

https://t.co/p2R8NsaJra

https://t.co/Pa6anQSr2z

https://t.co/raUNXX4l3m

[Ian Waudby-Smith @ianws0]

And giving an oral presentation in room 316 happening now.

[Ian Waudby-Smith @ianws0]

@Apoorva__Lal @pedrohcgs Check out yabai (+skhd) next time you use a Mac!

https://t.co/HLn8NcJaUq

[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 https://t.co/jOVmvRDxYi

[Ian Waudby-Smith @ianws0]

@KrishnRamesh Congrats Krishn!!

[Carnegie Mellon Statistics & Data Science @CMU_StatDS]

Ramping up for this weekend’s #WiDSPittsburgh @CarnegieMellon events! Come join us for #datascience talks and networking with Keynote by Sheryl Skolnick, Strategic Advisor @UnitedHealthGrp @Optum! https://t.co/fwdCrsstpz Registration is free! @WiDS_Worldwide @CMU_DietrichHSS

[Carnegie Mellon University @CarnegieMellon]

Shantanu Gupta, Emre Yolcu and Minji Yoon of @SCSatCMU and Ian Waudby-Smith of @CMU_DietrichHSS have been named 2023 @amazon Graduate Research Fellows.
https://t.co/vfuBG0J0el

[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

[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.

[Matteo Bonvini @bonv3]

My advisor @edwardhkennedy and I have posted an article on continuous trt effects estimation:

https://t.co/LGXVu6FOMg 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.

[Anupreet Porwal @porwalanupreet]

Super excited to share new work "Comparing methods for statistical inference with model uncertainty" with @AdrianRaftery1 that just got published in PNAS (@PNASNews) ! #Statistics #DataScience #BMA (1/n)

Paper: https://t.co/RjACkbXmLd

[Ian Waudby-Smith @ianws0]

@Stat_Ron @CarnegieMellon @CMU_Stats Congratulations Ron! 🔥🎉