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Monday, January 31, 2005
An Auction of Computing History
Posted by Lance
From Ryan O'Donnell
Christie's is auctioning off a bunch of documents related to the
history of computing.
A '46 IAS report by von Neumann and others to the US Army on the
concept of a computer is expected to go for around $35k, an original
copy of Turing's "On computable numbers" for about $17.5k, a letter
from Gödel to Skolem for about $15k, Shannon's collected works for
about $10k, etc.
More from Anupam Gupta: Some related info
(including dates of exhibitions in Cambridge MA, and Palo Alto) and also on Boing Boing.
4:49 PM
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Sunday, January 30, 2005
DIMACS
Posted by Lance
This week I'm in the great Garden State of New Jersey (my home state)
for back to back DIMACS workshops on Bounded
Rationality and Markets as
Predictive Devices.
Since 1989 DIMACS (the Center
for Discrete Mathematics and Theoretical Computer Science) has greatly
served
our community with a collection of workshops, visitor and
postdoc programs built around special years (later
becoming special foci as they extended to several years). The
workshops this week come under the Special Focus
on Computation and the Socio-Economic Sciences. DIMACS also has a
strong educational mission with programs for teacher training and
for high school and undergraduate students.
DIMACS started as a National Science Foundation Science and Technology
Center and when that program ended in 2000 DIMACS continues through a
series of smaller state and federal grants. DIMACS based at Rutgers
has partners
drawn from several New Jersey universities and research
laboratories. DIMACS has a strong but small staff and many volunteers
within our community but I attribute the recent continued strength of
DIMACS mostly to the tireless efforts of its director Fred Roberts.
DIMACS plays an important central organizing effort in theoretical
computer science and has often represented theory to the NSF and other
funding agencies. DIMACS has had an important direct and indirect role
in my academic career and I suspect the careers of most
theorists. Let's hope DIMACS can continue its multifaceted role in our
field for decades to come.
7:00 PM
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Friday, January 28, 2005
Choosing Your Advisor
Posted by Lance
Someone threw out this quote yesterday.
Choosing your advisor is like choosing your spouse.
I would say more like choosing your parent since the advisor-student
relationship is not symmetrical. But the point remains: No single
decision will make or break your graduate career more than the choice
of advisor.
A good advisor serves as a mentor and a colleague. Someone who will
represent you, fight for you, challenge you and push you but not
belittle you or take advantage of you. He or she will direct your
research to primarily address your future career. An ideal
advisor-student relationship will develop into a mutually strong
research environment and will last well beyond the student's graduate
career.
You should ideally choose an advisor whose expertise matches your
research interests. But more importantly you need to find the advisor
with which you can have a strong working relationship. You don't have
to see eye-to-eye on every issue but you need to have mutual
respect. Like in marriage, an advisor might work well with one kind of
student but not with another. You need to find the right advisor that
fits your needs and personality. If the advisor relationship goes sour
for any reason, you need to change advisors. Being stuck in bad
advisor-student relationship is almost a guarantee of a disastrous
graduate career.
5:35 PM
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Thursday, January 27, 2005
Remembering the Holocaust
Posted by Lance
As you probably know today was the sixtieth
anniverary of the liberation of Auschwitz. In religious school as
a kid we read books, saw gruesome movies, met holocaust survivors and
I visited a concentration camp during a college trip to Europe. But
the enormity of the holocaust hit me most during my sabbatical year in
Amsterdam in 1996. One fourth of the population of the city was
Jewish in the 30's. We had to work hard to find the small Jewish
population so we could properly celebrate the Jewish holidays during
our year there.
I worry sometimes about how to keep my children aware of the
holocaust. How do I prevent them from just thinking it was just some
event that happened a long time ago? When they reach my age what will
they and the world do for the 100th anniversary of Auschwitz? Let us
hope we can always remember.
7:22 PM
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Tuesday, January 25, 2005
STOC Papers
Posted by Lance
The list of
accepted papers for STOC is up. Nice to see they
accepted Trifonov's
paper in addition to Reingold. Many other nice complexity results
too. Take a look.
8:12 PM
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Blink
Posted by Lance
A publisher sent me a copy of Blink
a new book by Malcolm Gladwell. Gladwell wrote the very popular Tipping
Point about phase transitions which I haven't read.
The main thesis of Blink states that people can make good predictions
quickly and with a small amount of information if they have experience
or are properly trained. The real challenge is to get people to ignore
excess information and focus on the few bits that can really can
accurately determine an outcome. Often people make better decisions
when rushed since they won't have time to focus on the extraneous
details.
Gladwell does his homework and makes his case best by describing
experts who do a good job predicting the longevity of a marriage, the
flight of a tennis ball or the popularity of a new food item. I find
his one-time examples less convincing since anyone can get lucky and
even his best experts make occasional mistakes.
How do these ideas relate to computer science? In many more ways than
I can mention in this post. Juntas (or NC0 as we used to
call them) are functions that depend on a constant number of input bits
and we've seen recent work
on learning juntas. In general most of learning theory focuses on
finding a short description that predicts well. Transformations like
Fourier transforms and wavelets which allow researchers to focus on a
small amount of important information useful in many areas like
computer vision. The recent areas of sublinear algorithms and property
testing often can say something interesting about an input by only
looking at a small part.
In my job I also find myself using less information to make just as
good decisions. I can often get a good feel about a research paper or
a recommendation letter by a quick focus on a few key elements. I can
almost always predict the quality of a talk within the first thirty
seconds. Even in research where one has to narrow the list of
techniques, I can eliminate large sets of approaches without having to
work them out thoroughly.
One needs care not to weed out a good idea too quickly but if you
allow yourself to get bogged down in details you will spend too much
time often making the same or possibly worse choices.
4:06 PM
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Monday, January 24, 2005
The Premier of Numb3rs
Posted by Lance
Feel free to comment on last night's premier of Numb3rs, a
show that has seemed to capture the interest of this community. For
good reason as apparently
the P versus NP problem will get mentioned
on episode four, the best publicity we'll get since Homer
Simpson went 3-D.
My wife and I enjoyed the show. Charlie, the mathematician character,
definitely fits within the convex hull of math types I know. I liked
the scene where Charlie asked several people to position themselves
randomly and remarked that they were evenly spaced while real random
points would have some clusters. Viewers might actually learn some
interesting mathematical concepts watching this show.
At one point Charlie's physicist friend says something like "You
are almost thirty at the peak of your game and most mathematicians
only have five to six good years in them." Generally accurate but
a little disheartening to this forty-one year old.
8:57 AM
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Saturday, January 22, 2005
Machine Learning, Information Markets and Love
Posted by Lance
John Langford starts a new weblog Machine
Learning & Theory.
2004 Year
End Awards from Chris Masse's Predictions
Market Digest (from David Pennock)
Is love
more complicated than computational complexity? I can't make
this up.
2:15 PM
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Thursday, January 20, 2005
Does a Chess Program have Free Will?
Posted by Lance
A non-CS Chicago Alum asked me a question about free will and
computation. I passed the question to David McAllester, an AI
professor at TTI, and he gave the following interesting reply.
The idea that I could be simulated on a computer seems at odds with my
subjective experience of free will and my intuition that my future
actions are not yet determined — I am free to choose them. But
consider a computer program that plays chess. In actual chess playing
programs the program "considers" individual moves and
"works out" the consequences of each move. This is a rather
high level description of the calculation that is done, but it is fair
to say that the program "considers options" and
"evaluates consequences". When I say, as a human being,
that I have to choose between two options, and that I have not decided
yet, this seems no different to me from the situation of a chess
playing computer before it has finished its calculation. The
computer's move is determined — it is a deterministic process —
and yet it still has "options". To say "the computer
could move pawn to king four" is true provided that we interpret
"could do x" as "it is a legal option for the computer
to do x". To say that I am free is simply so say that I have
options (and I should consider them and look before I leap). But
having options, in the sense of the legal moves of chess, is
compatible with selecting an option using a deterministic computation.
A chess playing program shows that a determined system can have free
will, i.e., can have options. So free will (having options) is
compatible with determinism and there is no conflict.
8:02 AM
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Tuesday, January 18, 2005
Favorite Theorems: The First Decade
Posted by Lance
I have listed my favorite theorems for the first
and second
decades of my research career corresponding roughly to the third and
fourth decades of research in computational complexity. This year I
will list my favorite theorems for the first decade of complexity,
1965-1974.
As opposed to the previous lists, we have 30-40 years of hindsight to
see what theorems have stood the test of time. Each month starting in
February I will highlight one result and mention related work to show
how computational complexity went from a simple but beautiful idea to
an important subdiscipline of computer science.
8:47 PM
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Monday, January 17, 2005
Recommendation Letters
Posted by Lance
A few random comments as I read and write recommendation letters for
various academic positions:
Back in the old days, a candidate would send a department a list of
references and the department would send to each reference by postal
mail a request for a letter which would be sent back by postal mail
and followed up by a thank you sent again by postal mail. Faculty had
a lot more secretarial support back then. This year I only got one
such request, from a math department. Many departments have the
candidates ask the recommendors to send letters directly by post
and/or email. The best organized departments send the recommendors a
link that leads to a secure upload page that puts the letter directly in the
department's database.
Some misguided people like to send letters by post because they worry
about the security of email and the electronic storage of their
letters. Letters sent by post are far less secure. Copies of these
letters must be made and these copies get left, on copy machines, in
mailboxes in public areas, on peoples desks and in conference rooms. In
any case it doesn't make sense to go crazy over security, any student
with a little imagination can find a way to see their
letters. Students: Don't do this. No good will come out of it.
There is an old saying "If a price is advertised as under $30 you
can rest assured it is not $19.99." I take this saying into
account when I read recommendation letters, particularly lines like
"among the top half of complexity theorists graduating this
year". In general I read letters more for what is not said than
what is said.
"Strong potential" looks good for a fresh Ph.D. and the kiss
of death for a senior candidate.
I ignore negative recommendations as probably personal issues. If you
really dislike someone write a lukewarm letter. Seriously, if you
don't feel you can write a strong letter for someone make up an excuse
for why they shouldn't list you as a reference. Don't refuse to write
if you get a request directly from a department. No letter is seen as
a negative letter.
"I recommend" is a weak recommendation. "I very
strongly recommend" is a strong recommendation. "I give my
strongest recommendation" is a meaningless lie. "Don't hire
this person because we plan to make him/her an offer and we want him/her
for ourselves" is as strong as they get.
4:04 PM
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Sunday, January 16, 2005
Theory for Dentists
Posted by Lance
Thanks to Rahul Santhanam for covering for me last week. If you are looking for
a smart hard-working postdoc in complexity take
a look at Rahul.
On the plane last week the passenger sitting next to me, a dentist
from Vancouver, was reading a Scientific American
article
on quantum cryptography. Quantum cryptography got its start from
people in the theoretical computer science field like Charlie Bennett
and Gilles Brassard. For our field to flourish we must produce
research of interest to others and to see outsiders reading about
the fruits of our labor just for fun is a good sign.
7:38 PM
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Your Patience Has Been Rewarded (by guest blogger Rahul Santhanam)
Posted by Cheshire Cat
For Lance is back, and raring to go. It has been an interesting one week, but on the whole, research is probably easier than blogging, and certainly less nerve-wracking. I wish I could say the same about my job search. Wish me luck.
1:27 AM
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Saturday, January 15, 2005
Open papers (by guest blogger Rahul Santhanam)
Posted by Cheshire Cat
Lance has posted quite a lot on conference papers, review processes and the like recently, so one more won't hurt. Because of the resource constraints on program committees and the page limits on submissions, we have "standard" FOCS/STOC papers, which may contain two or three main results which improve in a natural way on previous results, proofs for the results which have a certain minimum technical complexity, and a few clever new ideas underlying the proofs. This is a good thing in that it steadily advances the state of the art in established areas, and in that it creates a congenial climate for collaboration because results are efficiently transmitted (one need only note the difference from previous results) and proofs easily digested (by understanding the role of the new ideas).
But my personal preference is for papers which are more mysterious, in which the results may be a little less clean. Research is often awkward (as opposed to the products of research, which are more often beautiful than not). I like papers which reflect this, in which perhaps there is some backtracking and re-examination of assumptions because a conventional line of research is stalled , or in which the motivation is not a technical but rather a philosophical question, or in which a promising idea is proposed which hasn't yet found an interesting application, or in which a connection between two disparate areas is hinted at but not completely formalized. By their very nature, their acknowledgement of contingency, these papers open themselves up to the reader; they are speculative, not authoritative, and by their speculativeness they inspire speculation in the reader. Also, since the results in open papers may not be compelling in themselves, the authors may be forced to make a stronger case for their ideas - this lays bare intuitions which in normal circumstances are shrouded within proofs.
My personal favorite among open papers, reflecting my interest in pseudorandomness, is Sipser's "Expanders, randomness or time versus space", which is all of 4 pages long. I was wondering whether the STOC/FOCS climate has become less receptive to openness of late, but in fact during my time as a graduate student there have been several instances that have caught my attention... Here is a (necessarily subjective) list: this one, this one, this one and this one. And it is a vindication of openness, of the primacy of ideas over short-term results, that the last-mentioned paper led, directly or indirectly, to this.
1:41 AM
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Friday, January 14, 2005
Theory used to be Fun (by guest blogger Rahul Santhanam)
Posted by Cheshire Cat
Was leafing through some old copies of SIGACT News from the 80s. Once the forests of facial hair had ceased to distract me, I was intrigued by glimpses of a mysterious event known as the FOCS Follies. I have no information about the provenance and history of this event, but I amused myself by imagining such an event taking place in the hectic and efficient world of the contemporary FOCS... Of course, the globalization of theory is a good thing, and talks still provide a medium for the expression of individuality.
5:06 PM
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Thursday, January 13, 2005
Mandatory Technical Post (by guest blogger Rahul Santhanam)
Posted by Cheshire Cat
The theory of derandomization has had many successes, but challenges remain. Perhaps the most significant of these are finding a deterministic poly time (or even subexp time) algorithm for arithmetic circuit identity testing, and finding a deterministic NC algorithm for perfect matching. A question that hasn't received as much attention as the above is whether fully poly time randomized approximation schemes (FPRASs) for #P-complete problems can be derandomized.
Question 1: Is there a natural #P-complete problem which has a fully poly time deterministic approximation scheme?
A good candidate is counting satisfying assignments to DNF formula, for which the best deterministic algorithm is more than a decade old, and takes slightly super-poly time. There is a beautiful theory of Monte Carlo Markov Chain based FPRASs for #P-complete problems, but I don't believe it is known how to derandomize any of these FPRASs.
Now, to weaken Question 1 slightly... Say that a randomized approximation scheme A for a function f is an FPRAS with symmetry breaking if with high probability, A outputs a single value that's a good approximation to f (as opposed to garden-variety FPRASs, which may output different values on different sequences of random bits, subject to the condition that most of these values are good approximations to f). FPRASs with symmetry breaking were studied in a paper by Cai, Lipton, Longpre, Ogihara, Regan and Sivakumar.
Question 2: Is there a natural #P-complete problem which has an FPRAS with symmetry breaking?
Question 1 (and hence also Question 2) has a positive answer under Nisan-Wigderson style circuit lower bound assumptions, which imply that any FPRAS can be derandomized. Moreover, if any FPRAS can be derandomized, BPP = P. What about the weaker assumption that any FPRAS can be converted to an FPRAS with symmetry breaking?
Question 3: Does the assumption that every function f which has an FPRAS also has an FPRAS with symmetry breaking imply any collapse of conventional complexity classes?
1:10 AM
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Tuesday, January 11, 2005
Recreational Complexity (by guest blogger Rahul Santhanam)
Posted by Cheshire Cat
We all like problems. But it's sort of sad that as our careers develop, we get to spend less and less time on problems that don't offer opportunities for resume enhancement. I don't think twice about watching a 3-hour movie, but feel guilty if I spend more than an hour on a problem that has nothing to do with research...
A fellow grad student was TAing an algorithms class and posed a question about the change-making problem. In the change-making problem, you're given a set of denominations c1 > c2 > ... > cN and a value M and asked to find the minimum number of coins that add up to M. The greedy strategy is to choose as many c1's as possible, then as many c2's as possible etc. Is there a polynomial-time algorithm that, given a set of denominations as input, tells if the greedy strategy is always optimal for the set (i.e., optimal for every M)?
We pondered awhile, but then of course I had to ruin things by Googling the very elegant solution published by David Pearson a decade back.
Fresh-faced undergrads and first-year grads out there, resist the urge. Enjoy your freedom and treat each problem the same while you still can, before your research becomes too compelling (= compulsory)
1:38 AM
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World Series of Complexity Theorists (by guest blogger Rahul Santhanam)
Posted by Cheshire Cat
Ex-guest blogger Adam Klivans is off to become the resident learning theorist at Austin. But no matter, Eli Ben-Sasson will be at TTI till the summer, and Prahladh Harsha returns in the fall. What is it with Bostonian theorists and Chicago anyway?
1:30 AM
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Sunday, January 09, 2005
What's in a Name? Complexity (by guest blogger Rahul Santhanam)
Posted by Cheshire Cat
Hullo, all. Nice of Lance to lease me this space for a week, I most sincerely hope he won't come to regret it.
I was thinking about names. Lance is most economical, so why the "computational" in "computational complexity"? Any theory attempts to understand and explain complexity, so it's no surprise there's an ambiguity about the term "complexity theory". A complexity theorist could be (1) one of us, i.e., someone studying the complexity of solving discrete mathematical problems (2) someone studying the evolution of complex dynamical systems with reference to phenomena such as chaos, self-organized criticality, emergent structures and suchlike (3) someone studying the complexity of doing continuous mathematics, where only
partial information is available about the input. And there may be further incarnations of which I am unaware. Journal names are instructive - the journal "Complexity" hosts theorists of type (2), "Journal of Complexity" harbors theorists of stripe (3), and of course we have "Computational Complexity" to ourselves. I wonder: when a non-scientist who is curious about science hears the term "complexity theorist", which of the above does he visualize? (2), most probably. I remember reading Mitchell Waldrop's book "Complexity" as an undergrad, and there have been several other popular books of the same flavor. Has computational complexity failed to reach out to a wider audience and define itself, or is it rather that we have aspired to a different goal: acknowledgement by the mathematics community of our significance?
4:12 PM
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Saturday, January 08, 2005
While the advisor is away ...
Posted by Lance
I'm off the net next week. My student Rahul Santhanam will guest post in my absence. Enjoy!
7:01 AM
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Thursday, January 06, 2005
Spamalot
Posted by Lance
A few years ago an undergrad in my class did his programming project
based on the movie Monty
Python and the Holy Grail. He attached a note
to the project suggesting that I see the movie. I should have failed
him right there and then. He should have known that every nerdy
American of
my generation saw that movie several times and memorized most of
the dialog.
To relive those glory days last night my wife and I went to see Spamalot, the
new Eric Idle musical based on Holy Grail with a nifty cast of
Tim Curry as King Arthur and David Hyde Pierce and Hank Azaria as lots
of other characters. The show had many of the great bits
from the movie ("just a flesh wound") but completely skipped
others ("answer me these questions three"). The songs lacked
memorable melodies but mostly had pretty funny lyrics. Besides
following the rough plot of the movie the show also parodies big
budget musicals allowing them to add a female lead who could sing
(Sara Ramirez) and leading up to a happy ending that made me miss the
non-ending of the movie.
In short I and the rest of the audience had a great time and laughed
throughout but it won't go down in history as one of the great musicals.
11:16 AM
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Wednesday, January 05, 2005
Big Omega
Posted by Lance
We define big-oh notation by saying f(n)=O(g(n)) if there exists some
constant c such that for all large enough n, f(n)≤ c g(n). If the
same holds for all c>0, then f(n)=o(g(n)), the little-oh notation.
Big-oh and little-oh
notation come in very handy in analyzing algorithms because we can
ignore implementation issues that could cost a constant factor.
To describe lower bounds we use the big-omega notation
f(n)=Ω(g(n)) usually defined by saying for some constant c>0
and all large enough n, f(n)≥c g(n). This has a nice symmetry
property, f(n)=O(g(n)) iff g(n)=Ω(f(n)). Unfortunately it does
not correspond to how we actually prove lower bounds.
For example consider the following algorithm to solve perfect
matching:
If the number of vertices is odd then output "No Perfect
Matching" otherwise try all possible matchings.
We would like to say the algorithm requires exponential time but in
fact you cannot prove a Ω(n2) lower bound using the
usual definition of Ω since the algorithm runs in linear time
for n odd. We should instead define
f(n)=Ω(g(n)) by saying for some constant c>0, f(n)≥ c g(n)
for infinitely many n. This gives a nice correspondence between upper
and lower bounds: f(n)=Ω(g(n)) iff f(n) is not o(g(n)).
On a related note some researchers like to say f(n)∈O(g(n))
viewing O(g(n)) as a set of functions. This trades off a nice clear
unambiguous notation with something ugly for the sake of
formality. Yuck.
7:22 AM
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Monday, January 03, 2005
Asher Peres, 1934-2005
Posted by Lance
By Netanel Lindner, Petra Scudo and Danny Terno via Christopher Fuchs
Quantum information science lost one of its founding fathers. Asher Peres
died on Sunday, January 1, 2005. He was 70 years old.
A distinguished professor at the Department of Physics, Technion -
Israel Institute of Technology, Asher described himself as "the
cat who walks by himself". His well-known independence in
thought and research is the best demonstration of this attitude.
Asher will be missed by all of us not only as a great scientist but
especially as a wonderful person. He was a surprisingly warm and
unpretentious man of stubborn integrity, with old-world grace and a
pungent sense of humor. He was a loving husband to his wife Aviva, a
father to his two daughters Lydia and Naomi, and a proud grandfather
of six. Asher was a demanding but inspiring teacher. Many physicists
considered him not only a valued colleague but also a dear friend and
a mentor.
Asher's scientific work is too vast to review, while its highlights are
well-known. One of the six fathers of quantum teleportation, he made
fundamental contributions to the definition and characterization of
quantum entanglement, helping to promote it from the realm of philosophy
to the world of physics. The importance of his contributions to other
research areas cannot be overestimated. Starting his career as a
graduate student of Nathan Rosen, he established the physicality of
gravitational waves and provided a textbook example of a strong
gravitational wave with his PP-wave. Asher was also able to point out
some of the signatures of quantum chaos, paving the way to many more
developments. All of these contributions are marked by a surprising
simplicity and unbeatable originality.
Of all his publications, Asher was most proud of his book Quantum
Theory: Concepts and Methods. The book is an example of Asher's
scientific style: an uncompromising and deep understanding of the
fundamental issues expressed in a form which is as simple and accessible
as possible. It took Asher six years to carefully weave the threads of
his book together. The great quality of the work is acknowledged by
anyone acquainted with the final result.
In a favorite anecdote, Asher told about a reporter who had
interviewed him on quantum teleportation. "Can you teleport only
the body, or also the spirit?" the reporter had asked.
"Only the spirit," was Asher's reply. Our community has
been privileged to know him and have been touched by his spirit.
I am the cat who walks
by himself is a charming
twelve-page autobiography covering his life from his birth in the
village Beaulieu-sur-Dordogne in France until his meeting with Aviva on
a train to Haifa. The rest of his story is in his
formal CV.
10:25 PM
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Embarrassing Mistakes
Posted by Lance
We talked about embarrassing moments in our careers recently. I've had
talks gone bad and conversations with person A thinking they were
person B. And once I had a little too much sake in Tokyo and I
… never mind.
But alas my biggest embarrassments were the serious problems with
published proofs in several of my early papers. So to start out the New Year
with a clean slate I will list my failings. Don't blame my
co-authors; I take full responsibility for all these mistakes.
- In my first major paper, The Complexity of Perfect Zero-Knowledge,
I showed some properties of zero-knowledge proofs using the coins of a
verifier. Turns out that doesn't work as I thought. Aiello and
Håstad give
a correct proof and new results using the coins of
the simulator. See the appendix of Goldreich-Ostrovsky-Petrank
for more details.
- In the conference version of the paper On
the power of multi-power interactive protocols
we had to reduce to
error of a multi-prover proof system and wrote
We can run the
protocol in parallel without any problem since all messages are
independent coin tosses.
Actually correct as long as you interpret "without any problem" as an forty-page
proof by Ran Raz. Section 6 of our journal
version describes the problem and some earlier fixes. - The
paper Probabilistic
Computation and Linear Time simply had a bad proof of the main
result giving a relativized world where BPP was in BPTIME(n). Berg and
Håstad discuss
the issue. Rettinger and Verbeek have a purported proof
of the non-adaptive case and Rettinger claims to have solved the
general version in his thesis (in German).
- In the FOCS paper Using
Autoreducibility to Separate Complexity Classes we claimed that
all the EXPSPACE complete sets were autoreducible. We later realized
this result would separate NP from L and discovered the FOCS paper had a
bad proof. The autoreducibility of EXPSPACE remains open and settling
it in either direction would have major complexity consequences. The
journal
version has more details.
The vast majority of my papers do have, to the best of my beliefs, correct
proofs. But four mistakes is enough to gain a reputation and means you
should not trust my proofs on face value. I have also learned this
lesson and try to get reliable people to check over my proofs before I
make them public.
9:39 AM
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