Blum Biography
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1 Lenore Blum, Matemática Computacional, Algoritmos, Lógica, Geometría Algebraica
MATEMATICOS ACTUALES Lenore Blum, Matemática computacional, Algoritmos, Lógica, Geometría algebraica. Debemos dejar claro desde el comienzo de esta biografía de Lenore Blum que Blum es su apellido de casada, que solo tomó después de casarse con Manuel Blum, que también era matemático. Sin embargo, para evitar confusiones, nos referiremos a ella como Blum a lo largo de este artículo. Los padres de Lenore eran Irving y Rose y, además de una hermana, Harriet, que era dos años menor que Lenore, ella era parte de una extensa familia judía con varias tías y tíos. Su madre Rose era maestra de ciencias de secundaria en Nueva York. Lenore asistió a una escuela pública en la ciudad de Nueva York hasta que tuvo nueve años cuando su familia se mudó a América del Sur. Su padre Irving trabajaba en el negocio de importación/exportación y él y su esposa se instalaron en Venezuela con Lenore y Harriet. Durante su primer año en Caracas, Lenore no asistió a la escuela, sin embargo su madre le enseñó. Básicamente, la familia era demasiado pobre para poder pagar las tasas escolares. Al cabo de un año, Rose ocupó un puesto docente en la Escuela Americana E. Campo Alegre, en Caracas, y esto proporcionó suficiente dinero para permitir que Lenore asistiera a la escuela secundaria y luego a la escuela secundaria en Caracas. Mientras estaba en Caracas, conoció a Manuel Blum, quien también era de una familia judía. Manuel salió de Caracas mientras Lenore todavía estaba allí en la escuela y se fue a los Estados Unidos donde ingresó como estudiante en el Instituto de Tecnología de Massachusetts. -
The Association for Women in Mathematics: How and Why It Was
Mathematical Communities t’s 2011 and the Association for Women in Mathematics The Association (AWM) is celebrating 40 years of supporting and II promoting female students, teachers, and researchers. It’s a joyous occasion filled with good food, warm for Women conversation, and great mathematics—four plenary lectures and eighteen special sessions. There’s even a song for the conference, titled ‘‘((3 + 1) 9 3 + 1) 9 3 + 1 Anniversary in Mathematics: How of the AWM’’ and sung (robustly!) to the tune of ‘‘This Land is Your Land’’ [ICERM 2011]. The spirit of community and and Why It Was the beautiful mathematics on display during ‘‘40 Years and Counting: AWM’s Celebration of Women in Mathematics’’ are truly a triumph for the organization and for women in Founded, and Why mathematics. It’s Still Needed in the 21st Century SARAH J. GREENWALD,ANNE M. LEGGETT, AND JILL E. THOMLEY This column is a forum for discussion of mathematical communities throughout the world, and through all time. Our definition of ‘‘mathematical community’’ is Participants from the Special Session in Number Theory at the broadest: ‘‘schools’’ of mathematics, circles of AWM’s 40th Anniversary Celebration. Back row: Cristina Ballantine, Melanie Matchett Wood, Jackie Anderson, Alina correspondence, mathematical societies, student Bucur, Ekin Ozman, Adriana Salerno, Laura Hall-Seelig, Li-Mei organizations, extra-curricular educational activities Lim, Michelle Manes, Kristin Lauter; Middle row: Brooke Feigon, Jessica Libertini-Mikhaylov, Jen Balakrishnan, Renate (math camps, math museums, math clubs), and more. Scheidler; Front row: Lola Thompson, Hatice Sahinoglu, Bianca Viray, Alice Silverberg, Nadia Heninger. (Photo Cour- What we say about the communities is just as tesy of Kiran Kedlaya.) unrestricted. -
HHMC 2017 (2017 Workshop on Hybrid Human-Machine Computing)
CRonEM CRonEM HHMC 2017 (2017 Workshop on Hybrid Human-Machine Computing) 20 & 21 September 2017 Treetops, Wates House, University of Surrey Guildford, Surrey, UK Programme INTRODUCTION KEYNOTE 1 The 2017 Workshop on Hybrid Human-Machine Computing (HHMC 2017) is 2-day workshop, to be held Title: Password Generation, an Example of Human Computation at the University of Surrey, Guildford, UK, on 20 and 21 September, 2017. It is a workshop co-funded by Abstract: University of Surrey’s Institute for Advanced Studies (IAS), a number of other organizations and related research projects. A password schema is an algorithm for humans - working in their heads - without paper and pencil - to transform challenges (typically website names) into responses (passwords). When we talk about “computing” we often mean computers do something (for humans), but due to the more and more blurred boundary between humans and computers, this old paradigm of “computing” has To start this talk, the speaker will ask for 2 or 3 volunteers, whisper instructions in their ears, then have them changed drastically, e.g., in human computation humans do all or part of the computing (for machines), transform audience-proposed challenges (like AMAZON and FACEBOOK) into passwords. in computer-supported cooperative work (CSCW) humans are working together with assistance from The passwords will look random. The audience will be challenged to guess properties of the passwords but computers to conduct cooperative work, in social computing and computer-mediated communication even the simple schema the speaker whispered to the volunteers will produce passwords that look random. people’s social behaviors are intermingled with computer systems so computing happens with humans and These passwords can be easily made so strong that they pass virtually all password tests, like passwordmeter. -
Tarjan Transcript Final with Timestamps
A.M. Turing Award Oral History Interview with Robert (Bob) Endre Tarjan by Roy Levin San Mateo, California July 12, 2017 Levin: My name is Roy Levin. Today is July 12th, 2017, and I’m in San Mateo, California at the home of Robert Tarjan, where I’ll be interviewing him for the ACM Turing Award Winners project. Good afternoon, Bob, and thanks for spending the time to talk to me today. Tarjan: You’re welcome. Levin: I’d like to start by talking about your early technical interests and where they came from. When do you first recall being interested in what we might call technical things? Tarjan: Well, the first thing I would say in that direction is my mom took me to the public library in Pomona, where I grew up, which opened up a huge world to me. I started reading science fiction books and stories. Originally, I wanted to be the first person on Mars, that was what I was thinking, and I got interested in astronomy, started reading a lot of science stuff. I got to junior high school and I had an amazing math teacher. His name was Mr. Wall. I had him two years, in the eighth and ninth grade. He was teaching the New Math to us before there was such a thing as “New Math.” He taught us Peano’s axioms and things like that. It was a wonderful thing for a kid like me who was really excited about science and mathematics and so on. The other thing that happened was I discovered Scientific American in the public library and started reading Martin Gardner’s columns on mathematical games and was completely fascinated. -
Single-To-Multi-Theorem Transformations for Non-Interactive Statistical Zero-Knowledge
Single-to-Multi-Theorem Transformations for Non-Interactive Statistical Zero-Knowledge Marc Fischlin Felix Rohrbach Cryptoplexity, Technische Universität Darmstadt, Germany www.cryptoplexity.de [email protected] [email protected] Abstract. Non-interactive zero-knowledge proofs or arguments allow a prover to show validity of a statement without further interaction. For non-trivial statements such protocols require a setup assumption in form of a common random or reference string (CRS). Generally, the CRS can only be used for one statement (single-theorem zero-knowledge) such that a fresh CRS would need to be generated for each proof. Fortunately, Feige, Lapidot and Shamir (FOCS 1990) presented a transformation for any non-interactive zero-knowledge proof system that allows the CRS to be reused any polynomial number of times (multi-theorem zero-knowledge). This FLS transformation, however, is only known to work for either computational zero-knowledge or requires a structured, non-uniform common reference string. In this paper we present FLS-like transformations that work for non-interactive statistical zero-knowledge arguments in the common random string model. They allow to go from single-theorem to multi-theorem zero-knowledge and also preserve soundness, for both properties in the adaptive and non-adaptive case. Our first transformation is based on the general assumption that one-way permutations exist, while our second transformation uses lattice-based assumptions. Additionally, we define different possible soundness notions for non-interactive arguments and discuss their relationships. Keywords. Non-interactive arguments, statistical zero-knowledge, soundness, transformation, one-way permutation, lattices, dual-mode commitments 1 Introduction In a non-interactive proof for a language L the prover P shows validity of some theorem x ∈ L via a proof π based on a common string crs chosen by some external setup procedure. -
1 Introduction
Logic Activities in Europ e y Yuri Gurevich Intro duction During Fall thanks to ONR I had an opp ortunity to visit a fair numb er of West Eu rop ean centers of logic research I tried to learn more ab out logic investigations and appli cations in Europ e with the hop e that my exp erience may b e useful to American researchers This rep ort is concerned only with logic activities related to computer science and Europ e here means usually Western Europ e one can learn only so much in one semester The idea of such a visit may seem ridiculous to some The mo dern world is quickly growing into a global village There is plenty of communication b etween Europ e and the US Many Europ ean researchers visit the US and many American researchers visit Europ e Neither Americans nor Europ eans make secret of their logic research Quite the opp osite is true They advertise their research From ESPRIT rep orts the Bulletin of Europ ean Asso ciation for Theoretical Computer Science the Newsletter of Europ ean Asso ciation for Computer Science Logics publications of Europ ean Foundation for Logic Language and Information publications of particular Europ ean universities etc one can get a go o d idea of what is going on in Europ e and who is doing what Some Europ ean colleagues asked me jokingly if I was on a reconnaissance mission Well sometimes a cow wants to suckle more than the calf wants to suck a Hebrew proverb It is amazing however how dierent computer science is esp ecially theoretical com puter science in Europ e and the US American theoretical -
2003 Newsletter
1.6180339887498948482045868343656381177203091798057628621354486227052604628189024497072072041893911374847540880753868917521266338622235369317931800607667263544333890865959395829056 M e t r o M a t h 2.7182818284590452353602874713526624977572470936999595749669676277240766303535475945713821785251664274274663919320030599218174135966290435729003342952605956307381323286279434907632 N e w s l e t t e r Metropolitan New York Section of The Mathematical Association of America February 2003 3.1415926535897932384626433832795028841971693993751058209749445923078164062862089986280348253421170679821480865132823066470938446095505822317253594081284811174502841027019385211055 Bronx Brooklyn Columbia Dutchess Greene Manhattan Nassau Orange Putnam Queens Richmond Rockland Suffolk Sullivan Ulster Westchester 1.7724538509055160272981674833411451827975494561223871282138077898529112845910321813749506567385446654162268236242825706662361528657244226025250937096027870684620376986531051228499 A N N U A L M E E T I N G Saturday, 3 May 2003 9:00 AM − 5:00 PM LaGuardia Community College (CUNY) Long Island City, New York (Inquire Within for More Information) E L E C T I O N B A L L O T E N C L O S E D SECTION OFFICERS Section Governor Raymond N. Greenwell (516) 463-5573 (2002 – 2005) Hofstra University [email protected] Chair John (Jack) Winn (631) 420-2182 (2001 – 2003) Farmingdale (SUNY) [email protected] Chair-Elect Abraham S. Mantell (516) 572-8092 (2001 – 2003) Nassau Community College (SUNY) [email protected] Secretary Dan King (914) 395-2424 (2000 – 2003) -
Jeremiah Blocki
Jeremiah Blocki Current Position (August 2016 to present) Phone: (765) 494-9432 Assistant Professor Office: 1165 Lawson Computer Science Building Computer Science Department Email: [email protected] Purdue University Homepage: https://www.cs.purdue.edu/people/faculty/jblocki/ West Lafayette, IN 47907 Previous Positions (August 2015 - June 2016) (May 2015-August 2015) (June 2014-May 2015) Post-Doctoral Researcher Cryptography Research Fellow Post-Doctoral Fellow Microsoft Research Simons Institute Computer Science Department New England Lab (Summer of Cryptography) Carnegie Mellon University Cambridge, MA UC Berkeley Pittsburgh, PA 15213 Berkeley, CA Education Ph.D. in Computer Science, Carnegie Mellon University, 2014. Advisors: Manuel Blum and Anupam Datta. Committee: Manuel Blum, Anupam Datta, Luis Von Ahn, Ron Rivest Thesis Title: Usable Human Authentication: A Quantitative Treatment B.S. in Computer Science, Carnegie Mellon University, 2009. (3.92 GPA). Senior Research Thesis: Direct Zero-Knowledge Proofs Allen Newell Award for Excellence in Undergraduate Research Research Research Interests Passwords, Usable and Secure Password Management, Human Computable Cryptography, Password Hash- ing, Memory Hard Functions, Differential Privacy, Game Theory and Security Journal Publications 1. Blocki, J., Gandikota, V., Grigorescu, G. and Zhou, S. Relaxed Locally Correctable Codes in Computa- tionally Bounded Channels. IEEE Transactions on Information Theory, 2021. [https://ieeexplore. ieee.org/document/9417090] 2. Harsha, B., Morton, R., Blocki, J., Springer, J. and Dark, M. Bicycle Attacks Consider Harmful: Quantifying the Damage of Widespread Password Length Leakage. Computers & Security, Volume 100, 2021. [https://doi.org/10.1016/j.cose.2020.102068] 3. Chong, I., Proctor, R., Li, N. and Blocki, J. Surviving in the Digital Environment: Does Survival Processing Provide and Additional Memory Benefit to Password Generation Strategies. -
Computing Over the Reals: Where Turing Meets Newton, Volume 51
Computing over the Reals: Where Turing Meets Newton Lenore Blum he classical (Turing) theory of computation been a powerful tool in classical complexity theory. has been extraordinarily successful in pro- But now, in addition, the transfer of complexity re- Tviding the foundations and framework for sults from one domain to another becomes a real theoretical computer science. Yet its dependence possibility. For example, we can ask: Suppose we on 0s and 1s is fundamentally inadequate for pro- can show P = NP over C (using all the mathemat- viding such a foundation for modern scientific ics that is natural here). Then, can we conclude that computation, in which most algorithms—with ori- P = NP over another field, such as the algebraic gins in Newton, Euler, Gauss, et al.—are real num- numbers, or even over Z2? (Answer: Yes and es- ber algorithms. sentially yes.) In 1989, Mike Shub, Steve Smale, and I introduced In this article, I discuss these results and indi- a theory of computation and complexity over an cate how basic notions from numerical analysis arbitrary ring or field R [BSS89]. If R is such as condition, round-off, and approximation are Z2 = ({0, 1}, +, ·), the classical computer science being introduced into complexity theory, bringing theory is recovered. If R is the field of real num- together ideas germinating from the real calculus bers R, Newton’s algorithm, the paradigm algo- of Newton and the discrete computation of com- rithm of numerical analysis, fits naturally into our puter science. The canonical reference for this ma- model of computation. terial is the book Complexity and Real Computation Complexity classes P, NP and the fundamental [BCSS98]. -
March 1992 Council Minutes
AMERICAN MATHEMATICAL SOCIETY MINUTES OF THE COUNCIL Springfield, Missouri 19 March 1992 Abstract The Council of the American Mathematical Society met at 7:00 pm on Thursday, 19 March 1992, in the Texas Room of the Springfield Holiday Inn–University Plaza Hotel. Members present were Michael Artin, Salah Baouendi, Lenore Blum, Carl Cowen, Chandler Davis, Robert Fossum, Frank Gilfeather, Ronald Graham, Judy Green, Rebecca Herb, Linda Keen, Elliott Lieb, Andy Magid (Associate Secretary in charge of Springfield Meeting), Frank Peterson, Carl Pomerance, Frank Quinn, Marc Rieffel, John Selfridge (in place of BA Taylor), and Ruth Williams. Also attending were: William H. Jaco (ED), Jane Kister (MR-Ann Arbor), James Maxwell (AED), Ann Renauer (AMS Staff), Sylvia Wiegand (Committee on Committees), and Kelly Young (AMS Staff). President Artin presided. 1 2 CONTENTS Contents 0 Call to Order and Introductions. 4 0.1 Call to Order. ........................................ 4 0.2 Introduction of New Council Members. .......................... 4 1MINUTES 4 1.1 January 92 Council. .................................... 4 1.2 Minute of Business By Mail. ................................ 5 2 CONSENT AGENDA. 5 2.1 Discharge Committees. ................................... 5 2.1.1 Committee on Cooperative Symposia. ...................... 5 2.1.2 Liaison Committee with Sigma Xi ........................ 5 2.2 Society for Industrial and Applied Mathematics (SIAM). ................ 5 3 REPORTS OF BOARDS AND STANDING COMMITTEES. 6 3.1 EBC ............................................. 6 3.2 Nominating Committee .................................. 6 3.2.1 Vice-President. ................................... 6 3.2.2 Member-at-large of Council. ............................ 6 3.2.3 Trustee. ....................................... 7 3.3 Other action. ........................................ 7 3.4 Executive Committee and Board of Trustees (ECBT). ................. 7 3.5 Report from the Executive Director. -
Leonard (Len) Max Adleman 2002 Recipient of the ACM Turing Award Interviewed by Hugh Williams August 18, 2016
Leonard (Len) Max Adleman 2002 Recipient of the ACM Turing Award Interviewed by Hugh Williams August 18, 2016 HW: = Hugh Williams (Interviewer) LA = Len Adelman (ACM Turing Award Recipient) ?? = inaudible (with timestamp) or [ ] for phonetic HW: My name is Hugh Williams. It is the 18th day of August in 2016 and I’m here in the Lincoln Room of the Law Library at the University of Southern California. I’m here to interview Len Adleman for the Turing Award winners’ project. Hello, Len. LA: Hugh. HW: I’m going to ask you a series of questions about your life. They’ll be divided up roughly into about three parts – your early life, your accomplishments, and some reminiscing that you might like to do with regard to that. Let me begin with your early life and ask you to tell me a bit about your ancestors, where they came from, what they did, say up to the time you were born. LA: Up to the time I was born? HW: Yes, right. LA: Okay. What I know about my ancestors is that my father’s father was born somewhere in modern-day Belarus, the Minsk area, and was Jewish, came to the United States probably in the 1890s. My father was born in 1919 in New Jersey. He grew up in the Depression, hopped freight trains across the country, and came to California. And my mother is sort of an unknown. The only thing we know about my mother’s ancestry is a birth certificate, because my mother was born in 1919 and she was an orphan, and it’s not clear that she ever met her parents. -
The Origins of Computational Complexity
The Origins of Computational Complexity Some influences of Manuel Blum, Alan Cobham, Juris Hartmanis and Michael Rabin Abstract. This paper discusses some of the origins of Computational Complexity. It is shown that they can be traced back to the late 1950’s and early 1960’s. In particular, it is investigated to what extent Manuel Blum, Alan Cobham, Juris Hartmanis, and Michael Rabin contributed each in their own way to the existence of the theory of computational complexity that we know today. 1. Introduction The theory of computational complexity is concerned with the quantitative aspects of computation. An important branch of research in this area focused on measuring the difficulty of computing functions. When studying the computational difficulty of computable functions, abstract models of computation were used to carry out algorithms. The goal of computations on these abstract models was to provide a reasonable approximation of the results that a real computer would produce for a certain computation. These abstract models of computations were usually called “machine models”. In the late 1950’s and early 1960’s, the study of machine models was revived: the blossoming world of practical computing triggered the introduction of many new models and existing models that were previously thought of as computationally equivalent became different with respect to new insights re- garding time and space complexity measures. In order to define the difficulty of functions, computational complexity measures, that were defined for all possible computations and that assigned a complexity to each terminating computation, were proposed. Depending on the specific model that was used to carry out computations, there were many notions of computational complexity.