Results 1  10
of
1,296,252
Fibonacci Heaps and Their Uses in Improved Network optimization algorithms
, 1987
"... In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated Fheaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. Fheaps support arbitrary deletion from an nitem heap in qlogn) amortized tim ..."
Abstract

Cited by 739 (18 self)
 Add to MetaCart
time and all other standard heap operations in o ( 1) amortized time. Using Fheaps we are able to obtain improved running times for several network optimization algorithms. In particular, we obtain the following worstcase bounds, where n is the number of vertices and m the number of edges
Optimal Brain Damage
, 1990
"... We have used informationtheoretic ideas to derive a class of practical and nearly optimal schemes for adapting the size of a neural network. By removing unimportant weights from a network, several improvements can be expected: better generalization, fewer training examples required, and improved sp ..."
Abstract

Cited by 510 (5 self)
 Add to MetaCart
We have used informationtheoretic ideas to derive a class of practical and nearly optimal schemes for adapting the size of a neural network. By removing unimportant weights from a network, several improvements can be expected: better generalization, fewer training examples required, and improved
Particle swarm optimization
, 1995
"... A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear fun ..."
Abstract

Cited by 3769 (22 self)
 Add to MetaCart
function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described.
Locationaided routing (LAR) in mobile ad hoc networks, in:
 Proc. of MOBICOM
, 1998
"... A mobile ad hoc network consists of wireless hosts that may move often. Movement of hosts results in a change in routes, requiring some mechanism for determining new routes. Several routing protocols have already been proposed for ad hoc networks. This paper suggests an approach to utilize location ..."
Abstract

Cited by 901 (10 self)
 Add to MetaCart
" of the ad hoc network. This results in a significant reduction in the number of routing messages. We present two algorithms to determine the request zone, and also suggest potential optimizations to our algorithms.
The capacity of wireless networks
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 2000
"... When n identical randomly located nodes, each capable of transmitting at bits per second and using a fixed range, form a wireless network, the throughput @ A obtainable by each node for a randomly chosen destination is 2 bits per second under a noninterference protocol. If the nodes are optimally p ..."
Abstract

Cited by 3243 (42 self)
 Add to MetaCart
When n identical randomly located nodes, each capable of transmitting at bits per second and using a fixed range, form a wireless network, the throughput @ A obtainable by each node for a randomly chosen destination is 2 bits per second under a noninterference protocol. If the nodes are optimally
Markov Logic Networks
 MACHINE LEARNING
, 2006
"... We propose a simple approach to combining firstorder logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a firstorder knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
Abstract

Cited by 816 (39 self)
 Add to MetaCart
We propose a simple approach to combining firstorder logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a firstorder knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects
How practical is network coding?
, 2006
"... With network coding, intermediate nodes between the source and the receivers of an endtoend communication session are not only capable of relaying and replicating data messages, but also of coding incoming messages to produce coded outgoing ones. Recent studies have shown that network coding is ..."
Abstract

Cited by 1016 (23 self)
 Add to MetaCart
is beneficial for peertopeer content distribution, since it eliminates the need for content reconciliation, and is highly resilient to peer failures. In this paper, we present our recent experiences with a highly optimized and highperformance C++ implementation of randomized network coding at the application
Network information flow
 IEEE TRANS. INFORM. THEORY
, 2000
"... We introduce a new class of problems called network information flow which is inspired by computer network applications. Consider a pointtopoint communication network on which a number of information sources are to be mulitcast to certain sets of destinations. We assume that the information source ..."
Abstract

Cited by 1967 (24 self)
 Add to MetaCart
coding rate region. Our result can be regarded as the Maxflow Mincut Theorem for network information flow. Contrary to one’s intuition, our work reveals that it is in general not optimal to regard the information to be multicast as a “fluid” which can simply be routed or replicated. Rather
Mining the Network Value of Customers
 In Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining
, 2002
"... One of the major applications of data mining is in helping companies determine which potential customers to market to. If the expected pro t from a customer is greater than the cost of marketing to her, the marketing action for that customer is executed. So far, work in this area has considered only ..."
Abstract

Cited by 568 (11 self)
 Add to MetaCart
One of the major applications of data mining is in helping companies determine which potential customers to market to. If the expected pro t from a customer is greater than the cost of marketing to her, the marketing action for that customer is executed. So far, work in this area has considered
Ant algorithms for discrete optimization
 ARTIFICIAL LIFE
, 1999
"... This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies’ foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic ..."
Abstract

Cited by 489 (42 self)
 Add to MetaCart
biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a
Results 1  10
of
1,296,252