Results 1  10
of
294,578
Quantum algorithms for the subsetsum problem
"... Abstract. This paper introduces a subsetsum algorithm with heuristic asymptotic cost exponent below 0.25. The new algorithm combines the 2010 HowgraveGraham–Joux subsetsum algorithm with a new streamlined data structure for quantum walks on Johnson graphs. ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
Abstract. This paper introduces a subsetsum algorithm with heuristic asymptotic cost exponent below 0.25. The new algorithm combines the 2010 HowgraveGraham–Joux subsetsum algorithm with a new streamlined data structure for quantum walks on Johnson graphs.
On the Expressiveness of SubsetSum Representations
 Acta Inform
, 2000
"... We develop a general theory for representing information as sums of elements in a subset of the basic set A of numbers of cardinality n, often refered to as a "knapsack vector". How many numbers can be represented in this way depends heavily on A. The lower, resp. upper, bound for the c ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
for expressiveness. Keywords: subsetsum, knapsack vector, expressiveness, injectivity Introduction Consider a finite set A of positive integers. Actually we need only the assumption that a commutative and an associative operation + is defined on A. Then each subset SA of A represents a number, namely, the sum
Global Optimization with Polynomials and the Problem of Moments
 SIAM Journal on Optimization
, 2001
"... We consider the problem of finding the unconstrained global minimum of a realvalued polynomial p(x) : R R, as well as the global minimum of p(x), in a compact set K defined by polynomial inequalities. It is shown that this problem reduces to solving an (often finite) sequence of convex linear mat ..."
Abstract

Cited by 569 (47 self)
 Add to MetaCart
We consider the problem of finding the unconstrained global minimum of a realvalued polynomial p(x) : R R, as well as the global minimum of p(x), in a compact set K defined by polynomial inequalities. It is shown that this problem reduces to solving an (often finite) sequence of convex linear
A Fast Approximation Algorithm for the SubsetSum Problem
, 1999
"... The subsetsum problem (SSP) is defined as follows: given a positive integer bound and a set of n positive integers find a subset whose sum is closest to, but not greater than, the bound. We present a randomized approximation algorithm for this problem with linear space complexity and time complexit ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
The subsetsum problem (SSP) is defined as follows: given a positive integer bound and a set of n positive integers find a subset whose sum is closest to, but not greater than, the bound. We present a randomized approximation algorithm for this problem with linear space complexity and time
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a ViewBased Representation
 International Journal of Computer Vision
, 1998
"... This paper describes an approach for tracking rigid and articulated objects using a viewbased representation. The approach builds on and extends work on eigenspace representations, robust estimation techniques, and parameterized optical flow estimation. First, we note that the leastsquares image r ..."
Abstract

Cited by 656 (16 self)
 Add to MetaCart
This paper describes an approach for tracking rigid and articulated objects using a viewbased representation. The approach builds on and extends work on eigenspace representations, robust estimation techniques, and parameterized optical flow estimation. First, we note that the leastsquares image
A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge
 PSYCHOLOGICAL REVIEW
, 1997
"... How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LS ..."
Abstract

Cited by 1772 (10 self)
 Add to MetaCart
How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory of acquired similarity and knowledge representation, latent semantic analysis
The DLV System for Knowledge Representation and Reasoning
 ACM Transactions on Computational Logic
, 2002
"... Disjunctive Logic Programming (DLP) is an advanced formalism for knowledge representation and reasoning, which is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class ΣP 2 (NPNP). Thus, under widely believ ..."
Abstract

Cited by 455 (100 self)
 Add to MetaCart
Disjunctive Logic Programming (DLP) is an advanced formalism for knowledge representation and reasoning, which is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class ΣP 2 (NPNP). Thus, under widely
Boosting a Weak Learning Algorithm By Majority
, 1995
"... We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a large number of hypotheses, each of which is generated by training the given learning algorithm on a different set of examples. Our algorithm is based on ideas pr ..."
Abstract

Cited by 516 (15 self)
 Add to MetaCart
presented by Schapire in his paper "The strength of weak learnability", and represents an improvement over his results. The analysis of our algorithm provides general upper bounds on the resources required for learning in Valiant's polynomial PAC learning framework, which are the best general
Results 1  10
of
294,578