8,324 research outputs found
Improved Bounds on Quantum Learning Algorithms
In this article we give several new results on the complexity of algorithms
that learn Boolean functions from quantum queries and quantum examples.
Hunziker et al. conjectured that for any class C of Boolean functions, the
number of quantum black-box queries which are required to exactly identify an
unknown function from C is ,
where is a combinatorial parameter of the class C. We
essentially resolve this conjecture in the affirmative by giving a quantum
algorithm that, for any class C, identifies any unknown function from C using
quantum black-box
queries.
We consider a range of natural problems intermediate between the exact
learning problem (in which the learner must obtain all bits of information
about the black-box function) and the usual problem of computing a predicate
(in which the learner must obtain only one bit of information about the
black-box function). We give positive and negative results on when the quantum
and classical query complexities of these intermediate problems are
polynomially related to each other.
Finally, we improve the known lower bounds on the number of quantum examples
(as opposed to quantum black-box queries) required for -PAC
learning any concept class of Vapnik-Chervonenkis dimension d over the domain
from to . This new lower bound comes
closer to matching known upper bounds for classical PAC learning.Comment: Minor corrections. 18 pages. To appear in Quantum Information
Processing. Requires: algorithm.sty, algorithmic.sty to buil
On the black-box complexity of Sperner's Lemma
We present several results on the complexity of various forms of Sperner's
Lemma in the black-box model of computing. We give a deterministic algorithm
for Sperner problems over pseudo-manifolds of arbitrary dimension. The query
complexity of our algorithm is linear in the separation number of the skeleton
graph of the manifold and the size of its boundary. As a corollary we get an
deterministic query algorithm for the black-box version of the
problem {\bf 2D-SPERNER}, a well studied member of Papadimitriou's complexity
class PPAD. This upper bound matches the deterministic lower
bound of Crescenzi and Silvestri. The tightness of this bound was not known
before. In another result we prove for the same problem an
lower bound for its probabilistic, and an
lower bound for its quantum query complexity, showing
that all these measures are polynomially related.Comment: 16 pages with 1 figur
Modeling the Structure and Complexity of Engineering Routine Design Problems
This paper proposes a model to structure routine design problems as well as a model of its design complexity. The idea is that having a proper model of the structure of such problems enables understanding its complexity, and likewise, a proper understanding of its complexity enables the development of systematic approaches to solve them. The end goal is to develop computer systems capable of taking over routine design tasks based on generic and systematic solving approaches. It is proposed to structure routine design in three main states: problem class, problem instance, and problem solution. Design complexity is related to the degree of uncertainty in knowing how to move a design problem from one state to another. Axiomatic Design Theory is used as reference for understanding complexity in routine design
Pattern Matching in Multiple Streams
We investigate the problem of deterministic pattern matching in multiple
streams. In this model, one symbol arrives at a time and is associated with one
of s streaming texts. The task at each time step is to report if there is a new
match between a fixed pattern of length m and a newly updated stream. As is
usual in the streaming context, the goal is to use as little space as possible
while still reporting matches quickly. We give almost matching upper and lower
space bounds for three distinct pattern matching problems. For exact matching
we show that the problem can be solved in constant time per arriving symbol and
O(m+s) words of space. For the k-mismatch and k-difference problems we give
O(k) time solutions that require O(m+ks) words of space. In all three cases we
also give space lower bounds which show our methods are optimal up to a single
logarithmic factor. Finally we set out a number of open problems related to
this new model for pattern matching.Comment: 13 pages, 1 figur
Grammar-based Representation and Identification of Dynamical Systems
In this paper we propose a novel approach to identify dynamical systems. The
method estimates the model structure and the parameters of the model
simultaneously, automating the critical decisions involved in identification
such as model structure and complexity selection. In order to solve the
combined model structure and model parameter estimation problem, a new
representation of dynamical systems is proposed. The proposed representation is
based on Tree Adjoining Grammar, a formalism that was developed from linguistic
considerations. Using the proposed representation, the identification problem
can be interpreted as a multi-objective optimization problem and we propose a
Evolutionary Algorithm-based approach to solve the problem. A benchmark example
is used to demonstrate the proposed approach. The results were found to be
comparable to that obtained by state-of-the-art non-linear system
identification methods, without making use of knowledge of the system
description.Comment: Submitted to European Control Conference (ECC) 201
Quantum Algorithms for the Triangle Problem
We present two new quantum algorithms that either find a triangle (a copy of
) in an undirected graph on nodes, or reject if is triangle
free. The first algorithm uses combinatorial ideas with Grover Search and makes
queries. The second algorithm uses
queries, and it is based on a design concept of Ambainis~\cite{amb04} that
incorporates the benefits of quantum walks into Grover search~\cite{gro96}. The
first algorithm uses only qubits in its quantum subroutines,
whereas the second one uses O(n) qubits. The Triangle Problem was first treated
in~\cite{bdhhmsw01}, where an algorithm with query complexity
was presented, where is the number of edges of .Comment: Several typos are fixed, and full proofs are included. Full version
of the paper accepted to SODA'0
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