MONET
2002
13 years 9 months ago
2002
The wireless networking environment presents formidable challenges to the study of broadcasting and multicasting problems. In this paper we focus on the problem of multicast tree c...
MONET
2002
13 years 9 months ago
2002
Data broadcasting as a means of efficient data dissemination is a key technology facilitating ubiquitous computing. For this reason, broadcast scheduling algorithms have received ...
ML
2002
ACM
13 years 9 months ago
2002
ACM
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
JSS
1998
13 years 9 months ago
1998
An important problem in the ®eld of distributed systems is that of detecting the termination of a distributed computation. Distributed termination detection (DTD) is a dicult p...
ML
2002
ACM
13 years 9 months ago
2002
ACM
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
JSAC
1998
13 years 9 months ago
1998
—In this paper, we will describe the close connection between the now celebrated iterative turbo decoding algorithm of Berrou et al. and an algorithm that has been well known in ...
JPDC
1998
13 years 9 months ago
1998
In this paper we present a parallel formulation of a multilevel k-way graph partitioning algorithm. A key feature of this parallel formulation is that it is able to achieve a high ...
JUCS
2002
13 years 9 months ago
2002
: In this paper, we present a fast and simple algorithm for constructing a minimal acyclic deterministic finite automaton from a finite set of words. Such automata are useful in a ...
JSC
2002
13 years 9 months ago
2002
This paper describes algorithms for computing the structure of finite transformation semigroups. The algorithms depend crucially on a new data structure for an R-class in terms of...
JMLR
2002
13 years 9 months ago
2002
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...