Author pages are created from data sourced from our academic publisher partnerships and public sources.
Share This Author
Algorithmic Mechanism Design
This work considers algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own self-interest, and suggests a framework for studying such algorithms.
Hardness vs Randomness
Pseudorandom generators for space-bounded computation
- N. Nisan
- Computer Science, MathematicsComb.
- 1 December 1992
Pseudorandom generators are constructed which convertO(SlogR) truly random bits toR bits that appear random to any algorithm that runs inSPACE(S) that can be simulated using onlyO(Slogn) random bits.
Randomness is Linear in Space
Of independent interest is the main technical tool: a procedure which extracts randomness from a defective random source using a small additional number of truly random bits.
Fairplay - Secure Two-Party Computation System
- D. Malkhi, N. Nisan, Benny Pinkas, Yaron Sella
- Computer ScienceUSENIX Security Symposium
- 13 August 2004
Fairplay is introduced, a full-fledged system that implements generic secure function evaluation (SFE) and provides a test-bed of ideas and enhancements concerning SFE, whether by replacing parts of it, or by integrating with it.
Bidding and allocation in combinatorial auctions
- N. Nisan
- Computer ScienceEC '00
- 17 October 2000
It is proved that the LP approach is an optimal allocation if and only if prices can be attached to single items in the auction, and suggests greedy and branch-andbound heuristics based on LP for other cases.
On the degree of Boolean functions as real polynomials
This paper characterize the degree of this polynomial in terms of certain combinatorial properties of the boolean function in order to establish a tight lower bound on the degree needed to represent any boolean function that depends on n variables.
Hardness vs. randomness
This generator reveals an equivalence between the problems of proving lower bounds and the problem of generating good pseudorandom sequences, and combines this construction with other arguments, a number of consequences are obtained.
Constant depth circuits, Fourier transform, and learnability
It is shown that an ACO Boolean function has almost all of its "power spectrum" on the low-order coefficients, implying several new properties of functions in -4C(': Functions in AC() have low "average sensitivity;" they may be approximated well by a real polynomial of low degree and they cannot be pseudorandom function generators.