8 ms·

Michel Talagrand wins Abel Prize for work wrangling randomness

278 points by jnord 3y ago

agumonkey 3y ago
Following Shaw Price in 2019 https://invidious.projectsegfau.lt/watch?v=22hR2CkNGXE https://invidious.projectsegfau.lt/watch?v=22hR2CkNGXE
novariation 3y ago
I've used and read about many concentration inequalities in machine learning and other applied math disciplines (Hoeffdings, McDiarmid, etc). Talagrands' results seem to generalize those, but I haven't had the chance to see them in the wild (yet).
wslh 3y ago
Ironically, the Wikipedia pages about him in French [1] and English [2] are, currently, super short. It will help if Wikipedia (just giving them as an example) could handle the focus on certain people and topics in an smarter way and not after the facts. Wikipedia has a special opportunity about handling this because it is the canonical general reference on Internet. Hallucinated or not I found a better starting point on [3], a Reddit post of 2 years ago with a comment saying: "Even professional mathematicians are barely qualified to choose the best mathematician in their narrow field of expertise, let alone in general… (Before I left math, the most difficult work I encountered was by Michel Talagrand.)" [4] and last, but would be first indeed his own web page [5]. He even gives prizes ala Knuth for solving specific math problems. Last, really few mentions in *stackexchange.com and Reddit. [1] https://fr.wikipedia.org/wiki/Michel_Talagrand https://fr.wikipedia.org/wiki/Michel_Talagrand [2] https://en.wikipedia.org/wiki/Michel_Talagrand https://en.wikipedia.org/wiki/Michel_Talagrand [3] https://chat.openai.com/share/39374448-da85-4897-977a-aaa37ed8e004 https://chat.openai.com/share/39374448-da85-4897-977a-aaa37e... [4] https://www.reddit.com/r/math/comments/s81ysm/who_would_you_consider_the_greatest_mathematician/ https://www.reddit.com/r/math/comments/s81ysm/who_would_you_... [5] https://michel.talagrand.net/ https://michel.talagrand.net/ [6] https://www.google.com/search?q=Michel+Talagrand+site%3Astackexchange.com&rlz=1C5CHFA_enAR1036AR1039&oq=Michel+Talagrand+site%3Astackexchange.com&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIGCAEQRRg7MgYIAhBFGDvSAQg3MzA5ajBqN6gCALACAA&sourceid=chrome&ie=UTF-8 https://www.google.com/search?q=Michel+Talagrand+site%3Astac... and https://www.google.com/search?q=Michel+Talagrand+site%3Areddit.com&sca_esv=58652087346d5a22&rlz=1C5CHFA_enAR1036AR1039&sxsrf=ACQVn08F-0FLq0EBmFSbTE8fcZ38fVz1Lw%3A1710938754916&ei=gtr6ZcfFN6mZwbkPlr6QgA8&ved=0ahUKEwjHjuDF74KFAxWpTDABHRYfBPAQ4dUDCBA&uact=5&oq=Michel+Talagrand+site%3Areddit.com&gs_lp=Egxnd3Mtd2l6LXNlcnAiIE1pY2hlbCBUYWxhZ3JhbmQgc2l0ZTpyZWRkaXQuY29tSKQbUMMJWJkScAF4AJABAJgBogKgAYwLqgEFNS40LjK4AQPIAQD4AQGYAgCgAgCYAwCIBgGSBwCgB-8D&sclient=gws-wiz-serp https://www.google.com/search?q=Michel+Talagrand+site%3Aredd...
- hopfenspergerj 3y ago
  That was me on Reddit. I emailed him asking about some of his work on invariant means in the 1970s. He said “I had no taste then”, and told me what a waste of time it was. At that point, I decided to go into data science instead of trying to get a post doc…
  - jebarker 3y ago
    How do you feel about that decision now? I left math after my PhD and often find myself feeling nostalgic about it.
    - otoburb 3y ago
      Always something to look forward to in [early] retirement to keep the mind active.
- epgui 3y ago
  > [...] and not after the facts Wikipedia is an encyclopedia, they intentionally only cover topics retroactively, and preferably after the dust has settled. They're intentionally not intending to be many things, including a source of up to date news: https://en.wikipedia.org/wiki/Wikipedia:What_Wikipedia_is_not https://en.wikipedia.org/wiki/Wikipedia:What_Wikipedia_is_no...
  - wslh 3y ago
    No pun intended. We all see (right?) that one of the cultural topics of the XXI is about focus. In a relative past people could study and/or read "all" texts and be intellectuals or feel like that. It is obvious that the focus economy always existed but now there are zillions of potential content to consume (good or not, doesn't matter). Wikipedia, as an example, has the opportunity to add layers (not many) of content in the quest of helping (not solving) this focus problem. As you said Wikipedia does not currently has this purpose, but this does not mean that they cannot carry the lit torch and pay attention to the focus economy (wordplay just by chance). It is also important to highlight that Wikipedia has many externalities, it is not just them. For example, Wikipedia results are generally the first that cames up in a search engine and their content is much used in machine learning. In this context, the problem of focus is not just about Wikipedia itself but the "focus graph" that has Wikipedia as one of the top releveant nodes.
ginnungagap 3y ago
I know Talagrand because some of his work comes up in topological dynamics (work around Rosenthal's l¹-dichotomy culminating in the Bourgain-Fremlin-Talagrand dicothomy for compact sets of Baire class 1 functions), but I had no idea he has such accomplishments in other fields! Impressive
webwanderings 3y ago
This is such a great quote for everyone! No matter the age. No matter what one wants to do. > “I’m not able to learn mathematics easily,” Talagrand tells ... “I have to work. It takes a very long time and I have a terrible memory. I forget things. So I try to work, despite handicaps, and the way I worked was trying to understand really well the simple things. Really, really well, in complete detail. And that turned out to be a successful approach.” Just imagine. You may be super smart who gets things easily and right away. Or, you may be average. Using this philosophy in life, one can excel further.
zafka 3y ago
I really enjoy this sort of story. Someone persevering in an unpopular arena for the love of it, and then having it become quite essential for the advancement of humanities goals as it is developed.
- strikelaserclaw 3y ago
  thats pretty much also the story of deep learning isn't it, i too enjoy reading about researchers who have a pure devotion to their subject.
deleted 3y ago
[deleted]
mturmon 3y ago
What an amazing output. Reading his papers, he manages to connect basic geometric ideas (like the notion of "isoperimetry", i.e., enclosing the maximum volume within a given perimeter) to probabilistic notions like convergence of averages. It links together stuff you learn in information theory (the probability mass of the "typical set"), and in machine learning (deviations of an training-set error rate from a true error rate), and in probability theory (empirical processes). His papers typically had an introduction that related the main theorem to some of these basic geometric notions. The introduction would reveal a whole new, very intuitive and geometric connection between a very abstract theorem to basic geometry, like the volume of a spherical shell. It would routinely blow my mind.
matsemann 3y ago
> fell in love with his future wife, a statistician, at first sight (he proposed to her three days after meeting her) Was that after sampling 1/e prospects? (The "marriage problem" is applied statistics on when it's optimal to stop searching for something https://en.wikipedia.org/wiki/Secretary_problem https://en.wikipedia.org/wiki/Secretary_problem )
esafak 3y ago
> He recalls with delight that he once used a cab service whose owner recognized his name, having learned the inequality during a probability class in business school. The taxi drivers in France are cut from different cloth!
- sn9 3y ago
  As well as their business students, apparently.
  - addcommitpush 3y ago
    The French higher education system is such that a lot of business students come from somewhat math-heavy undergraduate programs: 9h hours of math class plus one hour of one-on-one oral examination for 2-3 years.
- hervature 3y ago
  I think you missed the part about the owner was the one who went to business school.
2716057 3y ago
Slightly off-topic - has anyone read his book "What is a Quantum Field Theory"? Can you recommend it?
- amai 3y ago
  See a review here: https://www.math.columbia.edu/~woit/wordpress/?p=12819 https://www.math.columbia.edu/~woit/wordpress/?p=12819
  - 2716057 3y ago
    Thanks! I just saw Peter Woit's post on the Abel Prize https://www.math.columbia.edu/~woit/wordpress/?p=13877 https://www.math.columbia.edu/~woit/wordpress/?p=13877 also speaks positively about that book.
- cevi 3y ago
  I've been reading it over the past few days (picked it up after seeing it mentioned here). It's fantastic, much better than many similar attempts to make quantum field theory comprehensible to mathematicians.
idkdotcom 3y ago
[dead]
nyc111 3y ago
In the NewScientist interview he said, I tried “to understand really well the simple things.”
bruturis 3y ago
I didn't know about his inequalities, but I found (1) that provides an example of using Talagrand inequality applied to the longest increasing subsequence problem (12 pages, easy to read). It seems to be a broad generalization of the Hamming distance. (1) https://www.cs.purdue.edu/homes/hmaji/teaching/Spring%202018/lectures/11.pdf https://www.cs.purdue.edu/homes/hmaji/teaching/Spring%202018...
- anthk 3y ago
  I was about to say that. Also, check out this http://doc.9gridchan.info/blog/181230.ncubic.routing http://doc.9gridchan.info/blog/181230.ncubic.routing http://doc.9gridchan.info/blog/190104.ncubic.algorithms http://doc.9gridchan.info/blog/190104.ncubic.algorithms Fromm mycrovtif (RIP), a guy from the plan9/9front community.
tilakxd 3y ago
[flagged]
tilakxd 3y ago
[flagged]

278 points by jnord 3y ago

Following Shaw Price in 2019 https://invidious.projectsegfau.lt/watch?v=22hR2CkNGXE https://invidious.projectsegfau.lt/watch?v=22hR2CkNGXE

novariation 3y ago

I've used and read about many concentration inequalities in machine learning and other applied math disciplines (Hoeffdings, McDiarmid, etc). Talagrands' results seem to generalize those, but I haven't had the chance to see them in the wild (yet).

wslh 3y ago

Ironically, the Wikipedia pages about him in French [1] and English [2] are, currently, super short. It will help if Wikipedia (just giving them as an example) could handle the focus on certain people and topics in an smarter way and not after the facts. Wikipedia has a special opportunity about handling this because it is the canonical general reference on Internet. Hallucinated or not I found a better starting point on [3], a Reddit post of 2 years ago with a comment saying: "Even professional mathematicians are barely qualified to choose the best mathematician in their narrow field of expertise, let alone in general… (Before I left math, the most difficult work I encountered was by Michel Talagrand.)" [4] and last, but would be first indeed his own web page [5]. He even gives prizes ala Knuth for solving specific math problems. Last, really few mentions in *stackexchange.com and Reddit. [1] https://fr.wikipedia.org/wiki/Michel_Talagrand https://fr.wikipedia.org/wiki/Michel_Talagrand [2] https://en.wikipedia.org/wiki/Michel_Talagrand https://en.wikipedia.org/wiki/Michel_Talagrand [3] https://chat.openai.com/share/39374448-da85-4897-977a-aaa37ed8e004 https://chat.openai.com/share/39374448-da85-4897-977a-aaa37e... [4] https://www.reddit.com/r/math/comments/s81ysm/who_would_you_consider_the_greatest_mathematician/ https://www.reddit.com/r/math/comments/s81ysm/who_would_you_... [5] https://michel.talagrand.net/ https://michel.talagrand.net/ [6] https://www.google.com/search?q=Michel+Talagrand+site%3Astackexchange.com&rlz=1C5CHFA_enAR1036AR1039&oq=Michel+Talagrand+site%3Astackexchange.com&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIGCAEQRRg7MgYIAhBFGDvSAQg3MzA5ajBqN6gCALACAA&sourceid=chrome&ie=UTF-8 https://www.google.com/search?q=Michel+Talagrand+site%3Astac... and https://www.google.com/search?q=Michel+Talagrand+site%3Areddit.com&sca_esv=58652087346d5a22&rlz=1C5CHFA_enAR1036AR1039&sxsrf=ACQVn08F-0FLq0EBmFSbTE8fcZ38fVz1Lw%3A1710938754916&ei=gtr6ZcfFN6mZwbkPlr6QgA8&ved=0ahUKEwjHjuDF74KFAxWpTDABHRYfBPAQ4dUDCBA&uact=5&oq=Michel+Talagrand+site%3Areddit.com&gs_lp=Egxnd3Mtd2l6LXNlcnAiIE1pY2hlbCBUYWxhZ3JhbmQgc2l0ZTpyZWRkaXQuY29tSKQbUMMJWJkScAF4AJABAJgBogKgAYwLqgEFNS40LjK4AQPIAQD4AQGYAgCgAgCYAwCIBgGSBwCgB-8D&sclient=gws-wiz-serp https://www.google.com/search?q=Michel+Talagrand+site%3Aredd...

hopfenspergerj 3y ago
That was me on Reddit. I emailed him asking about some of his work on invariant means in the 1970s. He said “I had no taste then”, and told me what a waste of time it was. At that point, I decided to go into data science instead of trying to get a post doc…
- jebarker 3y ago
  How do you feel about that decision now? I left math after my PhD and often find myself feeling nostalgic about it.
  - otoburb 3y ago
    Always something to look forward to in [early] retirement to keep the mind active.
epgui 3y ago
> [...] and not after the facts Wikipedia is an encyclopedia, they intentionally only cover topics retroactively, and preferably after the dust has settled. They're intentionally not intending to be many things, including a source of up to date news: https://en.wikipedia.org/wiki/Wikipedia:What_Wikipedia_is_not https://en.wikipedia.org/wiki/Wikipedia:What_Wikipedia_is_no...
- wslh 3y ago
  No pun intended. We all see (right?) that one of the cultural topics of the XXI is about focus. In a relative past people could study and/or read "all" texts and be intellectuals or feel like that. It is obvious that the focus economy always existed but now there are zillions of potential content to consume (good or not, doesn't matter). Wikipedia, as an example, has the opportunity to add layers (not many) of content in the quest of helping (not solving) this focus problem. As you said Wikipedia does not currently has this purpose, but this does not mean that they cannot carry the lit torch and pay attention to the focus economy (wordplay just by chance). It is also important to highlight that Wikipedia has many externalities, it is not just them. For example, Wikipedia results are generally the first that cames up in a search engine and their content is much used in machine learning. In this context, the problem of focus is not just about Wikipedia itself but the "focus graph" that has Wikipedia as one of the top releveant nodes.

ginnungagap 3y ago

I know Talagrand because some of his work comes up in topological dynamics (work around Rosenthal's l¹-dichotomy culminating in the Bourgain-Fremlin-Talagrand dicothomy for compact sets of Baire class 1 functions), but I had no idea he has such accomplishments in other fields! Impressive

webwanderings 3y ago

This is such a great quote for everyone! No matter the age. No matter what one wants to do. > “I’m not able to learn mathematics easily,” Talagrand tells ... “I have to work. It takes a very long time and I have a terrible memory. I forget things. So I try to work, despite handicaps, and the way I worked was trying to understand really well the simple things. Really, really well, in complete detail. And that turned out to be a successful approach.” Just imagine. You may be super smart who gets things easily and right away. Or, you may be average. Using this philosophy in life, one can excel further.

zafka 3y ago

I really enjoy this sort of story. Someone persevering in an unpopular arena for the love of it, and then having it become quite essential for the advancement of humanities goals as it is developed.

strikelaserclaw 3y ago
thats pretty much also the story of deep learning isn't it, i too enjoy reading about researchers who have a pure devotion to their subject.

deleted 3y ago

[deleted]

mturmon 3y ago

What an amazing output. Reading his papers, he manages to connect basic geometric ideas (like the notion of "isoperimetry", i.e., enclosing the maximum volume within a given perimeter) to probabilistic notions like convergence of averages. It links together stuff you learn in information theory (the probability mass of the "typical set"), and in machine learning (deviations of an training-set error rate from a true error rate), and in probability theory (empirical processes). His papers typically had an introduction that related the main theorem to some of these basic geometric notions. The introduction would reveal a whole new, very intuitive and geometric connection between a very abstract theorem to basic geometry, like the volume of a spherical shell. It would routinely blow my mind.

matsemann 3y ago

> fell in love with his future wife, a statistician, at first sight (he proposed to her three days after meeting her) Was that after sampling 1/e prospects? (The "marriage problem" is applied statistics on when it's optimal to stop searching for something https://en.wikipedia.org/wiki/Secretary_problem https://en.wikipedia.org/wiki/Secretary_problem )

esafak 3y ago

> He recalls with delight that he once used a cab service whose owner recognized his name, having learned the inequality during a probability class in business school. The taxi drivers in France are cut from different cloth!

sn9 3y ago
As well as their business students, apparently.
- addcommitpush 3y ago
  The French higher education system is such that a lot of business students come from somewhat math-heavy undergraduate programs: 9h hours of math class plus one hour of one-on-one oral examination for 2-3 years.
hervature 3y ago
I think you missed the part about the owner was the one who went to business school.

2716057 3y ago

Slightly off-topic - has anyone read his book "What is a Quantum Field Theory"? Can you recommend it?

amai 3y ago
See a review here: https://www.math.columbia.edu/~woit/wordpress/?p=12819 https://www.math.columbia.edu/~woit/wordpress/?p=12819
- 2716057 3y ago
  Thanks! I just saw Peter Woit's post on the Abel Prize https://www.math.columbia.edu/~woit/wordpress/?p=13877 https://www.math.columbia.edu/~woit/wordpress/?p=13877 also speaks positively about that book.
cevi 3y ago
I've been reading it over the past few days (picked it up after seeing it mentioned here). It's fantastic, much better than many similar attempts to make quantum field theory comprehensible to mathematicians.

idkdotcom 3y ago

[dead]

nyc111 3y ago

In the NewScientist interview he said, I tried “to understand really well the simple things.”

bruturis 3y ago

I didn't know about his inequalities, but I found (1) that provides an example of using Talagrand inequality applied to the longest increasing subsequence problem (12 pages, easy to read). It seems to be a broad generalization of the Hamming distance. (1) https://www.cs.purdue.edu/homes/hmaji/teaching/Spring%202018/lectures/11.pdf https://www.cs.purdue.edu/homes/hmaji/teaching/Spring%202018...

anthk 3y ago
I was about to say that. Also, check out this http://doc.9gridchan.info/blog/181230.ncubic.routing http://doc.9gridchan.info/blog/181230.ncubic.routing http://doc.9gridchan.info/blog/190104.ncubic.algorithms http://doc.9gridchan.info/blog/190104.ncubic.algorithms Fromm mycrovtif (RIP), a guy from the plan9/9front community.

tilakxd 3y ago

[flagged]

tilakxd 3y ago

[flagged]