Category: Travel

Siem Reap conference

As I returned from the conference in Siem Reap. on a flight avoiding India and Pakistan and their [brittle and bristling!] boundary on the way back, instead flying far far north, near Arkhangelsk (but with nothing to show for it, as the flight back was fully in the dark), I reflected how enjoyable this conference […]

Le Monde puzzle [#1086]

A terse Le Monde mathematical puzzle in the optimisation mode: What is the maximal fraction of the surface of a triangle occupied by an inner triangle ABC where Abigail picks a summit A on a first side, Berenice B on a second side, and then Abigails picks C on the third side, towards Abigail maximising […]

distributed posteriors

Another presentation by our OxWaSP students introduced me to the notion of distributed posteriors, following a 2018 paper by Botond Szabó and Harry van Zanten. Which corresponds to the construction of posteriors when conducting a divide & conquer strategy. The authors show that an adaptation of the prior to the division of the sample is […]

off to Cambodia

Today, I am off to Cambodia for a small conference on Data Science and Finance, mostly finance, actually!, put together by a group of French and Cambodian colleagues and taking place in Siem Reap near the fabulous temples of Angkor Wat. Expect pictures in the following posts if I manage to stand the heat and […]

call for sessions and labs at Bay2sC0mp²⁰

A call to all potential participants to the incoming BayesComp 2020 conference at the University of Florida in Gainesville, Florida, 7-10 January 2020, to submit proposals [to me] for contributed sessions on everything computational or training labs [to David Rossell] on a specific language or software. The deadline is April 1 and the sessions will […]

and it only gets worse…

” A recent survey by Bankrate.com found that just 40% of US households have enough money to cover a $1,000 in emergency expenses.” The Guardian, Feb 2, 2019 ““Until we heard those cheers coming from Albany, we thought states were moving beyond such barbaric practices.” Mr. Pence offered his argument as a litmus test of […]

Bayesian intelligence in Warwick

This is an announcement for an exciting CRiSM Day in Warwick on 20 March 2019: with speakers 10:00-11:00 Xiao-Li Meng (Harvard): “Artificial Bayesian Monte Carlo Integration: A Practical Resolution to the Bayesian (Normalizing Constant) Paradox” 11:00-12:00 Julien Stoehr (Dauphine): “Gibbs sampling and ABC” 14:00-15:00 Arthur Ulysse Jacot-Guillarmod (École Polytechnique Fedérale de Lausanne): “Neural Tangent Kernel: […]

Bayesian intelligence in Warwick

This is an announcement for an exciting CRiSM Day in Warwick on 20 March 2019: with speakers 10:00-11:00 Xiao-Li Meng (Harvard): “Artificial Bayesian Monte Carlo Integration: A Practical Resolution to the Bayesian (Normalizing Constant) Paradox” 11:00-12:00 Julien Stoehr (Dauphine): “Gibbs sampling and ABC” 14:00-15:00 Arthur Ulysse Jacot-Guillarmod (École Polytechnique Fedérale de Lausanne): “Neural Tangent Kernel: […]

undecidable learnability

“There is an unknown probability distribution P over some finite subset of the interval [0,1]. We get to see m i.i.d. samples from P for m of our choice. We then need to find a finite subset of [0,1] whose P-measure is at least 2/3. The theorem says that the standard axioms of mathematics cannot […]

O’Bayes 19: registration and travel support

An update about the O’Bayes 19 conference next June-July:  the early registration period has now opened. And there should be funds for supporting early-career researchers, thanks to Google and CNRS sponsorships, as detailed below: Early-career researchers less than four years from PhD, are invited to apply for early-career scholarships. If you are a graduate student, […]

a pen for ABC

Among the flury of papers arXived around the ICML 2019 deadline, I read on my way back from Oxford a paper by Wiqvist et al. on learning summary statistics for ABC by neural nets. Pointing out at another recent paper by Jiang et al. (2017, Statistica Sinica) which constructed a neural network for predicting each […]

scalable Metropolis-Hastings

Among the flury of arXived papers of last week (414!), including a fair chunk of papers submitted to ICML 2019, I spotted one entry by Cornish et al. on scalable Metropolis-Hastings, which Arnaud Doucet had mentioned to me yesterday when in Oxford. The paper builds on the delayed acceptance paper we wrote with Marco Banterlé, […]

Fisher’s lost information

After a post on X validated and a good discussion at work, I came to the conclusion [after many years of sweeping the puzzle under the carpet] that the (a?) Fisher information obtained for the Uniform distribution U(0,θ) as θ⁻¹ is meaningless. Indeed, there are many arguments: The lack of derivability of the indicator function […]