Last month, I ordered several books on amazon, taking advantage of my amazon associate gains, and some of them were suggested by amazon algorithms based on my recent history. As I had recently read books involving thieves (like Giant Thief, or Broken Blade and the subsequent books), a lot of titles involved thieves or thievery related names… I picked Den of Thieves mainly for its cover as I did not know the author and the story sounded rather common. When I started reading the book, the story got more and more common, pertaining more to an extended Dungeons & Dragons scenario than to a genuine book! The theme of a bright young thief emerging from the gritty underworld of a close city has been over and over exploited in the fantasy literature, the best (?) example being The lies of Locke Lamora. (Whose third volume, The Republic of Thieves, is in my bag for Reykjavik!) This time, the thief does not appear particularly bright, except at times when he starts philosophy-sing with extremely dangerous enemies!, and the way he eventually overcomes insanely unbalanced odds is just too much. Most characters in the novel are not particularly engaging and way too much caricaturesque from the terribly evil sorcerer cavorting with she-demons to the rigid knight sticking to an idealistic vision of the world where ‘honour” and the code of chivalry is the solution to all problems. It is not even in the slightest sarcastic or tongue-in-cheek as the many novels by David Eddings and the main characters are mostly humourless. I wonder why the book did not get better edited as the weaknesses are very easy to spot! A good example where amazon software failed to make a worthy recommendation!
Archive for the Books Category
The English title of this 2007 book of Murakami is “What I talk about when I talk about running”. Which is a parody of Raymond Carver’s collection of [superb] short stories, “What we talk about when we talk about love”. (Murakami translated the complete œuvres of Raymond Carver in Japanese.) It is a sort of diary about Murakami’s running practice and the reasons why he is running. It definitely is not a novel and the style is quite loose or lazy, but this is not a drawback as the way the book is written somehow translates the way thoughts drift away and suddenly switch topics when one is running. At least during low-intensity practice, when I often realise I have been running for minutes without paying any attention to my route. Or when I cannot recall what I was thinking about for the past minutes. During races, the mind concentration is at a different level, first focussing on keeping the right pace, refraining from the deadly rush during the first km, then trying to merge with the right batch of runners, then fighting wind, slope, and eventually fatigue. While the book includes more general autobiographical entries than those related with Murakami’s runner’s life, there are many points most long-distance runners would relate with. From the righteous feeling of sticking to a strict training and diet, to the almost present depression catching us in the final kms of a race, to the very flimsy balance between under-training and over-training, to the strangely accurate control over one’s pace at the end of a training season, and, for us old runners, to the irremediable decline in one’s performances as years pass by… On a more personal basis, I also shared the pain of hitting one of the slopes in Central Park and the lack of nice long route along Boston’s Charles river. And shared the special pleasure of running near a river or seafront (which is completely uncorrelated with the fact it is flat, I believe!) Overall, what I think this book demonstrates is that there is no rational reason to run, which makes the title more than a parody, as fighting weight, age, health problems, depression, &tc. and seeking solitude, quiet, exhaustion, challenge, performances, zen, &tc. are only partial explanations. Maybe the reason stated in the book that I can relate the most with is this feeling of having an orderly structure one entirely controls (provided the body does not rebel!) at least once a day. Thus, I am not certain the book appeals to non-runners. And contrary to some reviews of the book, it certainly is not a training manual for novice runners. (Murakami clearly is a strong runner so some of his training practice could be harmful to weaker runners…)
After Broken Blade and its sequel Bared Blade, Kelly McCullough wrote Crossed Blades that I had ordered along with Bared Blade. And once again I read this volume within a few evenings. It is still very enjoyable, maybe the more given that there is a continuity in the characters and the plots. However, I did prefer Bared Blade to Crossed Blades as the former was creative in terms of plot and environment. Here, in Crossed Blades, the main character Aral is facing his past, from the destruction of his religious order and of his goddess to the possible treachery of former friends and mentors, to his attempt to drown this past in top quality whisky… While dealing with an adopted teenage daughter in the midst of a typical teenage crisis. This new instalment is thus full of introspection and reminiscence of past loves, and frankly a bit dull at times, even though there is a (spoiler warning!!) massive battle against the culprits for the destruction of the order. The very end is a bit disappointing, but it also hopefully closes a chapter in the hero’s life, which means that the next volume, Blade Reforged, may run into new territories and more into simili-detective stories. (Two more books in this Blade series are in the making!)
As the Le Monde mathematical puzzle of this week was a geometric one (the quadrangle ABCD is divided into two parts with the same area, &tc…) , with no clear R resolution, I chose to bypass it. In this April 3 issue, several items of interest: first, a report by Etienne Ghys on Yakov Sinaï’s Abel Prize for his work “between determinism and randomness”, centred on ergodic theory for dynamic systems, which sounded like the ultimate paradox the first time I heard my former colleague Denis Bosq give a talk about it in Paris 6. Then a frightening fact: the summer conditions have been so unusually harsh in Antarctica (or at least near the Dumont d’Urville French austral station) that none of the 15,000 Adélie penguin couples studied there managed to keep their chick alive. This was due to an ice shelf that did not melt at all over the summer, forcing the penguins to walk an extra 40k to reach the sea… Another entry on the legal obligation for all French universities to offer a second chance exam, no matter how students are evaluated in the first round. (Too bad, I always find writing a second round exam a nuisance.)
¨The idea is to calculate multiple likelihoods ahead of time (“pre-fetching”), and only use the ones which are needed.” A. Brockwell, 2006
Yet another paper on parallel MCMC, just arXived by Elaine Angelino, Eddie Kohler, Amos Waterland, Margo Seltzer, and Ryan P. Adams. Now, besides “prefetching” found in the title, I spotted “speculative execution”, “slapdash treatment”, “scheduling decisions” in the very first pages: this paper definitely is far from shying away from using fancy terminology! I actually found the paper rather difficult to read to the point I had to give up my first attempt during an endless university board of governors meeting yesterday. (I also think “prefetching” is awfully painful to type!)
What is “prefetching” then? It refers to a 2006 JCGS paper by Anthony Brockwell. As explained in the above quote from Brockwell, prefetching means computing the 2², 2³, … values of the likelihood that will be needed in 2, 3, … iterations. Running a regular Metropolis-Hastings algorithm then means building a decision tree back to the current iteration and drawing 2,3, … uniform to go down the tree to the appropriate branch. So in the end only one path of the tree is exploited, which does not seem particularly efficient when vanilla Rao-Blackwellisation and recycling could be implemented almost for free.
“Another intriguing possibility, suggested to the author by an anonymous referee, arises in the case where one can guess whether or not acceptance probabilities will be “high” or “low.” In this case, the tree could be made deeper down “high” probability paths and shallower in the “low” probability paths.” A. Brockwell, 2006
The current paper stems from Brockwell’s 2006 final remark, as reproduced above, by those “speculative moves” that considers the reject branch of the prefetching tree more often that not, based on some preliminary or dynamic evaluation of the acceptance rate. Using a fast but close enough approximation to the true target (and a fixed sequence of uniforms) may also produce a “single most likely path on which” prefetched simulations can be run. The basic idea is thus to run simulations and costly likelihood computations on many parallel processors along a prefetched path, path that has been prefetched for its high approximate likelihood. (With of courses cases where this speculative simulation is not helpful because we end up following another path with the genuine target.) The paper actually goes further than the basic idea to avoid spending useless time on paths that will not be chosen, by constructing sequences of approximations for the precomputations. The proposition for the sequence found therein is to subsample the original data and use a normal approximation to the difference of the log (sub-)likelihoods. Even though the authors describe the system implementation of the progressive approximation idea, it remains rather unclear (to me) how the adaptive estimation of the acceptance probability is compatible with the parallelisation idea. Because it seems (to me) that it induces a lot of communication between the cores. Also, the method is advocated mainly for burnin’ (or warmup, to follow Andrew’s terminology!), which seems to remove the need to use exact targets: if the approximation is close enough, the Markov chain will quickly reach a region of interest for the true target and from there there seems to be little speedup in implementing this nonetheless most interesting strategy.