Xi'an's Og

Final (half)day at JSM is always a sad thing as most people have left, people are busy dismantling booths and packing boxes, and the few remaining participants are fidgety and sitting on their suitcases (there may have been more suitcases than people in the main area that day!), cafés are minimally staffed or simply closed. Hence not the best time-slot to deliver one’s talk! Still, a few dozen people attended our session. The session topic was Bridge the Gap: Differential Privacy and Statistical Analysis, organised by Bei Jiang whom I met last summer in Kelowna, at a BIRS workshop on privacy. Where I spoke on setting up a complete decision-theoretic framework, as developed (and still in development) within our Ocean group, esp. Joshua Bon, Stan du Ché, and Judith Rousseau. (Rather than on the original plan of talking about convergence versus privacy, as a criticism of differential privacy.) The other talks were by Shurong Li, strongly set with differential privacy when record linkage is present, and Xuan Bi on a fully decentralised federated learning with local exchanges of global gradients that limit privacy leaks. (With a mention of gossip learning I hadn’t seen previously!)

I enjoyed even more the session due to Naisyin Wang giving a discussion on the three talks, in  closes the particular because I had not seen her in years, if a few times since she was my teaching assistant in Cornell in a Bayesian decision theory class I was building on the spot (with Linda Zhao as a student!). Which nicely closes the loop given the topic of my talk, of which she was quite supportive! While calling for debiasing post-processing and wondering about a two-dimensional decision theoretic perspective rather than a unidimensional one under hard privacy constraints.

On the way out, after parting from the few friends remaining in the convention centre, I spotted the nearby (steel) bridge being raised, although I could not see the boat responsible for it. I had been unaware of this possibility while running over and under it, as well as swimming thrice under it. And we left Portland in the early afternoon, heading for Seattle and a celebration of Adrian Raftery’s career.

This entry was posted on August 11, 2024 at 12:24 am and is filed under Books, pictures, Running, Statistics, Travel, University life with tags AI, American Statistical Association, ASA, Bayesian decision theory, Bayesian nonparametrics, Bayesian privacy, BIRS, British Columbia, classification, contextual integrity, data science, differential privacy, draw bridge, ERC, federated learning, generalised Bayesian inference, Joint Statistical Meeting, JSM 2024, Kelowna, Ocean, open water swimming, Oregon, Pacific North West, Portland, Seattle, United States of America, University of Washington, Willamette River. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.