Following the highly successful [authorised opinion!, from objective sources] MCMski IV, in Chamonix last year, the BayesComp section of ISBA has decided in favour of a two-year period, which means the great item of news that next year we will meet again for MCMski V [or MCMskv for short], this time on the snowy slopes of the Swiss town of Lenzerheide, south of Zürich. The committees are headed by the indefatigable Antonietta Mira and Mark Girolami. The plenary speakers have already been contacted and Steve Scott (Google), Steve Fienberg (CMU), David Dunson (Duke), Krys Latuszynski (Warwick), and Tony Lelièvre (Mines, Paris), have agreed to talk. Similarly, the nine invited sessions have been selected and will include Hamiltonian Monte Carlo, Algorithms for Intractable Problems (ABC included!), Theory of (Ultra)High-Dimensional Bayesian Computation, Bayesian NonParametrics, Bayesian Econometrics, Quasi Monte Carlo, Statistics of Deep Learning, Uncertainty Quantification in Mathematical Models, and Biostatistics. There will be afternoon tutorials, including a practical session from the Stan team, tutorials for which call is open, poster sessions, a conference dinner at which we will be entertained by the unstoppable Imposteriors. The Richard Tweedie ski race is back as well, with a pair of Blossom skis for the winner!
Archive for ISBA
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.
Inside Academia: confirming and mitigating the widely-shared post-graduate’s impostor syndrome
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 “How to do Research at MIT AI Lab – Emotional Factors”, relevant far beyond its original lab. I recommend it to any Ph.D. student; the feedback from readers is unanimous.
Outside Academia: incredibly increased readability
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.
On Thursday, I will travel to Montréal for the two days of NIPS workshop there. On Friday, there is the ABC in Montréal workshop that I cannot but attend! (First occurrence of an “ABC in…” in North America! Sponsored by ISBA as well.) And on Saturday, there is the 3rd NIPS Workshop on Probabilistic Programming where I am invited to give a talk on… ABC! And maybe will manage to get a sneak at the nearby workshop on Advances in variational inference… (0n a very personal side, I wonder if the weather will remain warm enough to go running in the early morning.)
Here are my tee-shirt design proposals for the official ISBA tee-shirt competition! (I used the facilities of CustomInk.com as I could not easily find a free software around. Except for the last one where I recycled my vistaprint mug design…)
While I do not have any expectation of seeing one of these the winner (!), what is your favourite one?!
Sonia Petrone announced today at BAYSM’14 that a competition was open for the design of an official ISBA tee-shirt! The deadline is October 15 and the designs are to be sent to Clara Grazian, currently at CEREMADE, Université Dauphine [that should be enough to guess her email!]. I will most certainly submit my mug design. And maybe find enough free time to design a fake eleven Paris with moustache tee-shirt. With Bayes’ [presumed] portrait of course…
[An announcement from ISBA about sponsoring young researchers at NIPS that links with my earlier post that our ABC in Montréal proposal for a workshop had been accepted and a more global feeling that we (as a society) should do more to reach towards machine-learning.]
The International Society for Bayesian Analysis (ISBA) is pleased to announce its new initiative *ISBA@NIPS*, an initiative aimed at highlighting the importance and impact of Bayesian methods in the new era of data science.
Among the first actions of this initiative, ISBA is endorsing a number of *Bayesian satellite workshops* at the Neural Information Processing Systems (NIPS) Conference, that will be held in Montréal, Québec, Canada, December 8-13, 2014.
Furthermore, a special ISBA@NIPS Travel Award will be granted to the best Bayesian invited and contributed paper(s) among all the ISBA endorsed workshops.
ISBA endorsed workshops at NIPS
- ABC in Montréal. This workshop will include topics on: Applications of ABC to machine learning, e.g., computer vision, other inverse problems (RL); ABC Reinforcement Learning (other inverse problems); Machine learning models of simulations, e.g., NN models of simulation responses, GPs etc.; Selection of sufficient statistics and massive dimension reduction methods; Online and post-hoc error; ABC with very expensive simulations and acceleration methods (surrogate modelling, choice of design/simulation points).
- Networks: From Graphs to Rich Data. This workshop aims to bring together a diverse and cross-disciplinary set of researchers to discuss recent advances and future directions for developing new network methods in statistics and machine learning.
- Advances in Variational Inference. This workshop aims at highlighting recent advancements in variational methods, including new methods for scalability using stochastic gradient methods, , extensions to the streaming variational setting, improved local variational methods, inference in non-linear dynamical systems, principled regularisation in deep neural networks, and inference-based decision making in reinforcement learning, amongst others.
- Women in Machine Learning (WiML 2014). This is a day-long workshop that gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, exchange ideas and learn from each other. Under-represented minorities and undergraduates interested in machine learning research are encouraged to attend.