## JSM 2015 [day #2]

Posted in Books, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , on August 11, 2015 by xi'an

Today, at JSM 2015, in Seattle, I attended several Bayesian sessions, having sadly missed the Dennis Lindley memorial session yesterday, as it clashed with my own session. In the morning sessions on Bayesian model choice, David Rossell (Warwick) defended non-local priors à la Johnson (& Rossell) as having better frequentist properties. Although I appreciate the concept of eliminating a neighbourhood of the null in the alternative prior, even from a Bayesian viewpoint since it forces us to declare explicitly when the null is no longer acceptable, I find the asymptotic motivation for the prior less commendable and open to arbitrary choices that may lead to huge variations in the numerical value of the Bayes factor. Another talk by Jin Wang merged spike and slab with EM with bootstrap with random forests in variable selection. But I could not fathom what the intended properties of the method were… Besides returning another type of MAP.

The second Bayesian session of the morn was mostly centred on sparsity and penalisation, with Carlos Carvalho and Rob McCulloch discussing a two step method that goes through a standard posterior  construction on the saturated model, before using a utility function to select the pertinent variables. Separation of utility from prior was a novel concept for me, if not for Jay Kadane who objected to Rob a few years ago that he put in the prior what should be in the utility… New for me because I always considered the product prior x utility as the main brick in building the Bayesian edifice… Following Herman Rubin’s motto! Veronika Rocková linked with this post-LASSO perspective by studying spike & slab priors based on Laplace priors. While Veronicka’s goal was to achieve sparsity and consistency, this modelling made me wonder at the potential equivalent in our mixtures for testing approach. I concluded that having a mixture of two priors could be translated in a mixture over the sample with two different parameters, each with a different prior. A different topic, namely multiple testing, was treated by Jim Berger, who showed convincingly in my opinion that a Bayesian approach provides a significant advantage.

In the afternoon finalists of the ISBA Savage Award presented their PhD work, both in the theory and  methods section and in the application section. Besides Veronicka Rocková’s work on a Bayesian approach to factor analysis, with a remarkable resolution via a non-parametric Indian buffet prior and a variable selection interpretation that avoids MCMC difficulties, Vinayak Rao wrote his thesis on MCMC methods for jump processes with a finite number of observations, using a highly convincing completion scheme that created independence between blocks and which reminded me of the Papaspiliopoulos et al. (2005) trick for continuous time processes. I do wonder at the potential impact of this method for processing the coalescent trees in population genetics. Two talks dealt with inference on graphical models, Masanao Yajima and  Christine Peterson, inferring the structure of a sparse graph by Bayesian methods.  With applications in protein networks. And with again a spike & slab prior in Christine’s work. The last talk by Sayantan Banerjee was connected to most others in this Savage session in that it also dealt with sparsity. When estimating a large covariance matrix. (It is always interesting to try to spot tendencies in awards and conferences. Following the Bayesian non-parametric era, are we now entering the Bayesian sparsity era? We will see if this is the case at ISBA 2016!) And the winner is..?! We will know tomorrow night! In the meanwhile, congrats to my friends Sudipto Banerjee, Igor Prünster, Sylvia Richardson, and Judith Rousseau who got nominated IMS Fellows tonight.

## On the Savage Award, advices to Ph.D. candidates [guest post]

Posted in Kids, Statistics, University life with tags , , , , , on January 22, 2015 by xi'an

This blog post was contributed by my friend Julien Cornebise, as a reprint of a column he wrote for the latest ISBA Bulletin.

This article is an occasion to pay forward ever so slightly, by encouraging current Ph.D. candidates on their path, the support ISBA gave me. Four years ago, I was honored and humbled to receive the ISBA 2010 Savage Award, category Theory and Methods, for my Ph.D. dissertation defended in 2009. Looking back, I can now testify how much this brought to me both inside and outside of Academia.

Upon hearing of the great news, a brilliant multi-awarded senior researcher in my lab very kindly wrote to me that such awards meant never having to prove one’s worth again. Although genuinely touched by her congratulations, being far less accomplished and more junior than her, I felt all the more responsible to prove myself worth of this show of confidence from ISBA. It would be rather awkward to receive such an award only to fail miserably shortly after.

This resonated deeply with the shared secret of recent PhDs, discovered during my year at SAMSI, a vibrant institution where half a dozen new postdocs arrive each year: each and every one of us, fresh Ph.D.s from some of the best institutions (Cambridge, Duke, Waterloo, Paris…) secretly suffered the very same impostor syndrome. We were looking at each other’s CV/website and thinking “jeez! this guy/girl across the door is an expert of his/her field, look at all he/she has done, whereas I just barely scrape by on my own research!” – all the while putting up a convincing façade of self-assurance in front of audiences and whiteboards, to the point of apparent cockiness. Only after candid exchanges in SAMSI’s very open environment did we all discover being in the very same mindset.

In hindsight the explanation is simple: each young researcher in his/her own domain has the very expertise to measure how much he/she still does not know and has yet to learn, while he/she hears other young researchers, experts in their own other field, present results not as familiar to him/her, thus sounding so much more advanced. This take-away from SAMSI was perfectly confirmed by the Savage Award: yes, maybe indeed, I, just like my other colleagues, might actually know something relatively valuable, and my scraping by might just be not so bad – as is also the case of so many of my young colleagues.

Of course, impostor syndrome is a clingy beast and, healthily, I hope to never get entirely over it – merely overcoming it enough to say “Do not worry, thee young candidate, thy doubts pave a path well trodden”.

A similar message is also part of the little-known yet gem of a guide, relevant far beyond its original lab. I recommend it to any Ph.D. student; the feedback from readers is unanimous.

After two post-docs, and curious to see what was out there in atypical paths, I took a turn out of purely academic research, first as an independent consultant, then recruited out of the blue by a start-up’s recruiter, and eventually doing my small share to help convince investors. I discovered there another facet of ISBA’s Savage Award: tremendous readability.

In Academia, the dominating metric of quality is the length of the publication list – a debate for another day.  Outside of Academia, however, not all interlocutors know how remarkable is a JRSSB Read Paper, or an oral presentation at NIPS, or a publication in Nature.

This is where international learned societies, like ISBA, come into play: the awards they bestow can serve as headline-grabbing material in a biography, easily spotted. The interlocutors do not need to be familiar with the subtleties of Bayesian Analysis. All they see is a stamp of approval from an official association of this researcher’s peers. That, in itself, is enough of a quality metric to pass the first round of contact, raise interest, and get the chance to further the conversation.

First concrete example: the recruiter who contacted me for the start-up I joined in 2011 was tasked to find profiles for an Applied position. The Savage Award on the CV grabbed his attention, even though he had no inkling what Adaptive Sequential Monte Carlo Methods were, nor if they were immediately relevant to the start-up. Passing it to the start-up’s managers, they immediately changed focus and interviewed me for their Research track instead: a profile that was not what they were looking for originally, yet stood out enough to interest them for a position they had not thought of filling via a recruiter – and indeed a unique position that I would never have thought to find this way either!

Second concrete example, years later, hard at work in this start-up’s amazing team: investors were coming for a round of technical due diligence. Venture capitals sent their best scientists-in-residence to dive deeply into the technical details of our research. Of course what matters in the end is, and forever will be, the work that is done and presented. Yet, the Savage Award was mentioned in the first line of the biography that was sent ahead of time, as a salient point to give a strong first impression of our research team.

Advices to Ph.D. Candidates: apply, you are the world best expert on your topic

That may sound trivial, but the first advice: apply. Discuss with your advisor the possibility to put your dissertation up for consideration. This might sound obvious to North-American students, whose educative system is rife with awards for high-performing students. Not so much in France, where those would be at odds with the sometimes over-present culture of égalité in the younger-age public education system. As a cultural consequence, few French Ph.D. students, even the most brilliant, would consider putting up their dissertation for consideration. I have been very lucky in that regard to benefit from the advice of a long-term Bayesian, who offered to send it for me – thanks again Xi’an! Not all students, regardless how brilliant their work, are made aware of this possibility.

The second advice, closely linked: do not underestimate the quality of your work. You are the foremost expert in the entire world on your Ph.D. topic. As discussed above, it is all too easy to see how advanced are the maths wielded by your office-mate, yet oversee the as-much-advanced maths you are juggling on a day-to-day basis, more familiar to you, and whose limitations you know better than anyone else. Actually, knowing these very limitations is what proves you are an expert.

A word of thanks and final advice

Finally, a word of thanks. I have been incredibly lucky, throughout my career so far, to meet great people. My dissertation already had four pages of acknowledgements: I doubt the Bulletin’s editor would appreciate me renewing (and extending!) them here. They are just as heartfelt today as they were then. I must, of course, add ISBA and the Savage Award committee for their support, as well as all those who, by their generous donations, allow the Savage Fund to stay alive throughout the years.

Of interest to Ph.D. candidates, though, one special mention of a dual tutelage system, that I have seen successfully at work many times. The most senior, a professor with the deep knowledge necessary to steer the project brings his endless fonts of knowledge collected over decades, wrapped in hardened tough-love. The youngest, a postdoc or fresh assistant professor, brings virtuosity, emulation and day-to-day patience. In my case they were Pr. Éric Moulines and Dr. Jimmy Olsson. That might be the final advice to a student: if you ever stumble, as many do, as I most surely did, because Ph.D. studies can be a hell of a roller-coaster to go through, reach out to the people around you and the joint set of skills they want to offer you. In combination, they can be amazing, and help you open doors that, in retrospect, can be worth all the efforts.

Julien Cornebise, Ph.D.
www.cornebise.com/julien

## JSM [4]

Posted in Books, pictures, Running, Statistics, Travel, University life with tags , , , , , , , on August 3, 2011 by xi'an

A new day at JSM 2011, admittedly not as tense as Monday, but still full. After a long run in the early hours when I took this picture, I started the day with the Controversies in the philosophy of Bayesian statistics with Jim Berger and Andrew Gelman, Rob Kass and Cosma Shalizi being unable to make it. From my point of view it was a fun session, even though I wish I had been more incisive! But I agreed with most of Jim said, so… It is too bad we could not cover his last point about the Bayesian procedures that were not Bayesianly justified (like posterior predictives) as I was quite interested in the potential discussion in this matter (incl. the position of the room on ABC!). Anyway, I am quite thankful to Andrew for setting up this session.As Jum said, we should have those more often, especially when the attendance was large enough to fill a double room at 8:30am.

Incidentally, I managed to have a glaring typo in my slides, pointed out by Susie Bayarri: Bayes theorem was written as

$\pi(\theta) \propto \pi(\theta) f(x|\theta)$

Aie, aie, aie! Short of better scapegoats, I will blame the AF plane for this… (This was a good way to start a controversy, however no one raised to the bait!) A more serious question reminded me of the debate surrounding A Search for Certainty: It was whether frequentist and subjective Bayes approaches had more justifications than the objective Bayes approach, in the light of von Mises‘ and personalistic (read, de Finetti) interpretations of probability.

While there were many possible alternatives for the next session, I went to attend Sylvia Richardson’s Medallion Lecture. This made sense on many levels, the primary one being that Sylvia and I worked and are working on rather close topics, from mixtures of distributions, to variable selection, to ABC. So I was looking forward the global picture she would provide on those topics. I particularly enjoyed the way she linked mixtures with more general modelling structures, through extensions in the distribution of the latent variables. (This is also why I am attending Chris Holmes’ Memorial Lecture tomorrow, with the exciting title of Loss, Actions, Decisions: Bayesian Analysis in High-Throughput Genomics.)

In the afternoon, I only attended one talk by David Nott, Efficient MCMC Schemes for Computationally Expensive Posterior Distribution, which involved hybrid Monte Carlo on complex likelihoods. This was quite interesting, as hybrid Monte Carlo is indeed the solution to diminish the number of likelihood evaluations, since it moves along iso-density slices… After this, we went working on ABC model choice with Jean-Michel Marin and Natesh Pillai. Before joining the fun at the Section for Bayesian statistical mixer, where the Savage and Mitchell and student awards were presented. This was the opportunity to see friends, meet new Bayesians, and congratulate the winners, including Julien Cornebise and Robin Ryder of course.

## ISBA prizes

Posted in Statistics, University life with tags , , , , on May 4, 2011 by xi'an

Starting this year, the Savage, DeGroot, and Mitchell Prizes awarded by ISBA have a submission deadline of May 31. Given the rather short notice, this means that less people will apply for the 2011 version of those prizes. Hence higher probabilities of winning! Note that, for the Savage award, all Ph.D. theses that have not yet been submitted, no matter how old they are, are eligible. (Note: I have just re-typed this entry as it seems the earlier version had another coding error!)

## Two local recipients for the Savage award!

Posted in Statistics, University life with tags , , , , on April 4, 2011 by xi'an

Two Paris statisticians are recipients of the Savage award this year: Julien Cornebise (PhD from Telecom-Paristech with Eric Moulines, now at UCL in Mark Girolami’s group) is nominated for the Theory award and Robin Ryder (PhD in Oxford with Geoff Nicholls, now at CREST) is nominated for the Applied methodology award. Congratulations to both (and to the other two recipients) for well-deserved rewards! (Past local recipients were Billy Amzal in 2005 and Nicolas Chopin in 2002.)

## Impresiónes de València 9

Posted in Mountains, pictures, Statistics, Travel, University life with tags , , , , , , on June 10, 2010 by xi'an

The València 9 meeting in Benidorm is now over, even for those who stay till the end of the party (!)… In retrospect, I found the scientific quality of this last meeting of the series quite high and I am thus sad this series comes to an end. This mythical gathering of “true believers” on a Valencianos beach town certainly had a charm not found in other meetings (even though I have no particular love of beaches, of beach towns or of cabarets) in that it brought people really together for a rather long time in an intense and sometime heated exchange of ideas. (This secluded perspective of course reinforced the caricatures of Bayesians as sectarians!) This was particularly true this time as the huge majority of people stayed in the same (awful) hotel. Also, the fact that there was no parallel sessions was a major factor to keep people together… (The fact that the afternoon sessions were administered by ISBA rather than the València 9 scientific committee had the drawback of sometimes producing similar talks.) In my personal view, there were somehow too many non-parametric and sparsity sessions/talks, but this follows the research trends in the community (after all in the 1994 meeting, there were also “too many” MCMC talks!) And the discussions from the floor were much more limited than in the earlier meetings (but most invited discussions were a clear added value to the talks). Maybe this is due to the growing Bayesian community. As in earlier editions, the poster sessions were a strong moment with the frustrating drawback of having too many posters in a single session to allow for a complete coverage (unless you were ready to stay up till 2am…) Again a consequence of the size of the audience. But it was a pleasure to see how Bayesian statistics was well and alive and how the community was bridging old-timers having attending all of the nine Valencia meetings with newcomers still writing their PhD. (Congrats to Emily Fox and to James Scott for their respective Savage awards!)

Darren Wilkinson also gives an overview of the “last Valencia meeting” on his blog. This post includes a detailed analysis of the GPU solution enthusiatically defended by Chris Holmes. Since I came back from the meeting with ideas towards parallel accelerations for MCMC algorithms, I will look carefully at his arguments.