461 research outputs found
Weak Parity
We study the query complexity of Weak Parity: the problem of computing the
parity of an n-bit input string, where one only has to succeed on a 1/2+eps
fraction of input strings, but must do so with high probability on those inputs
where one does succeed. It is well-known that n randomized queries and n/2
quantum queries are needed to compute parity on all inputs. But surprisingly,
we give a randomized algorithm for Weak Parity that makes only
O(n/log^0.246(1/eps)) queries, as well as a quantum algorithm that makes only
O(n/sqrt(log(1/eps))) queries. We also prove a lower bound of
Omega(n/log(1/eps)) in both cases; and using extremal combinatorics, prove
lower bounds of Omega(log n) in the randomized case and Omega(sqrt(log n)) in
the quantum case for any eps>0. We show that improving our lower bounds is
intimately related to two longstanding open problems about Boolean functions:
the Sensitivity Conjecture, and the relationships between query complexity and
polynomial degree.Comment: 18 page
On Algorithmic Statistics for space-bounded algorithms
Algorithmic statistics studies explanations of observed data that are good in
the algorithmic sense: an explanation should be simple i.e. should have small
Kolmogorov complexity and capture all the algorithmically discoverable
regularities in the data. However this idea can not be used in practice because
Kolmogorov complexity is not computable.
In this paper we develop algorithmic statistics using space-bounded
Kolmogorov complexity. We prove an analogue of one of the main result of
`classic' algorithmic statistics (about the connection between optimality and
randomness deficiences). The main tool of our proof is the Nisan-Wigderson
generator.Comment: accepted to CSR 2017 conferenc
On the Limits of Depth Reduction at Depth 3 Over Small Finite Fields
Recently, Gupta et.al. [GKKS2013] proved that over Q any -variate
and -degree polynomial in VP can also be computed by a depth three
circuit of size . Over fixed-size
finite fields, Grigoriev and Karpinski proved that any
circuit that computes (or ) must be of size
[GK1998]. In this paper, we prove that over fixed-size finite fields, any
circuit for computing the iterated matrix multiplication
polynomial of generic matrices of size , must be of size
. The importance of this result is that over fixed-size
fields there is no depth reduction technique that can be used to compute all
the -variate and -degree polynomials in VP by depth 3 circuits of
size . The result [GK1998] can only rule out such a possibility
for depth 3 circuits of size .
We also give an example of an explicit polynomial () in
VNP (not known to be in VP), for which any circuit computing
it (over fixed-size fields) must be of size . The
polynomial we consider is constructed from the combinatorial design. An
interesting feature of this result is that we get the first examples of two
polynomials (one in VP and one in VNP) such that they have provably stronger
circuit size lower bounds than Permanent in a reasonably strong model of
computation.
Next, we prove that any depth 4
circuit computing
(over any field) must be of size . To the best of our knowledge, the polynomial is the
first example of an explicit polynomial in VNP such that it requires
size depth four circuits, but no known matching
upper bound
Single Parameter Combinatorial Auctions with Partially Public Valuations
We consider the problem of designing truthful auctions, when the bidders'
valuations have a public and a private component. In particular, we consider
combinatorial auctions where the valuation of an agent for a set of
items can be expressed as , where is a private single parameter
of the agent, and the function is publicly known. Our motivation behind
studying this problem is two-fold: (a) Such valuation functions arise naturally
in the case of ad-slots in broadcast media such as Television and Radio. For an
ad shown in a set of ad-slots, is, say, the number of {\em unique}
viewers reached by the ad, and is the valuation per-unique-viewer. (b)
From a theoretical point of view, this factorization of the valuation function
simplifies the bidding language, and renders the combinatorial auction more
amenable to better approximation factors. We present a general technique, based
on maximal-in-range mechanisms, that converts any -approximation
non-truthful algorithm () for this problem into
and -approximate truthful
mechanisms which run in polynomial time and quasi-polynomial time,
respectively
Towards More Practical Linear Programming-based Techniques for Algorithmic Mechanism Design
R. Lavy and C. Swamy (FOCS 2005, J. ACM 2011) introduced a general method for
obtaining truthful-in-expectation mechanisms from linear programming based
approximation algorithms. Due to the use of the Ellipsoid method, a direct
implementation of the method is unlikely to be efficient in practice. We
propose to use the much simpler and usually faster multiplicative weights
update method instead. The simplification comes at the cost of slightly weaker
approximation and truthfulness guarantees
On the expressive power of read-once determinants
We introduce and study the notion of read- projections of the determinant:
a polynomial is called a {\it read-
projection of determinant} if , where entries of matrix are
either field elements or variables such that each variable appears at most
times in . A monomial set is said to be expressible as read-
projection of determinant if there is a read- projection of determinant
such that the monomial set of is equal to . We obtain basic results
relating read- determinantal projections to the well-studied notion of
determinantal complexity. We show that for sufficiently large , the permanent polynomial and the elementary symmetric
polynomials of degree on variables for are
not expressible as read-once projection of determinant, whereas
and are expressible as read-once projections of determinant. We
also give examples of monomial sets which are not expressible as read-once
projections of determinant
A Survey on Approximation Mechanism Design without Money for Facility Games
In a facility game one or more facilities are placed in a metric space to
serve a set of selfish agents whose addresses are their private information. In
a classical facility game, each agent wants to be as close to a facility as
possible, and the cost of an agent can be defined as the distance between her
location and the closest facility. In an obnoxious facility game, each agent
wants to be far away from all facilities, and her utility is the distance from
her location to the facility set. The objective of each agent is to minimize
her cost or maximize her utility. An agent may lie if, by doing so, more
benefit can be obtained. We are interested in social choice mechanisms that do
not utilize payments. The game designer aims at a mechanism that is
strategy-proof, in the sense that any agent cannot benefit by misreporting her
address, or, even better, group strategy-proof, in the sense that any coalition
of agents cannot all benefit by lying. Meanwhile, it is desirable to have the
mechanism to be approximately optimal with respect to a chosen objective
function. Several models for such approximation mechanism design without money
for facility games have been proposed. In this paper we briefly review these
models and related results for both deterministic and randomized mechanisms,
and meanwhile we present a general framework for approximation mechanism design
without money for facility games
Simple extractors via constructions of cryptographic pseudo-random generators
Trevisan has shown that constructions of pseudo-random generators from hard
functions (the Nisan-Wigderson approach) also produce extractors. We show that
constructions of pseudo-random generators from one-way permutations (the
Blum-Micali-Yao approach) can be used for building extractors as well. Using
this new technique we build extractors that do not use designs and
polynomial-based error-correcting codes and that are very simple and efficient.
For example, one extractor produces each output bit separately in
time. These extractors work for weak sources with min entropy , for
arbitrary constant , have seed length , and their
output length is .Comment: 21 pages, an extended abstract will appear in Proc. ICALP 2005; small
corrections, some comments and references adde
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