Results 1 - 10 of 104,431

Parameterized Complexity

by Rod G. Downey, Michael R. Fellows, Rolf Niedermeier, Peter Rossmanith, Rod G. Downey (wellington, New Zeal, Michael R. Fellows (newcastle, Rolf Niedermeier (tubingen, Peter Rossmanith (tu Munchen , 1998
"... the rapidly developing systematic connections between FPT and useful heuristic algorithms | a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs ..."
Abstract - Cited by 1218 (75 self) - Add to MetaCart
the rapidly developing systematic connections between FPT and useful heuristic algorithms | a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs

Planning Algorithms

by Steven M LaValle , 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
Abstract - Cited by 1108 (51 self) - Add to MetaCart
This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning

Loopy Belief Propagation for Approximate Inference: An Empirical Study

by Kevin P. Murphy, Yair Weiss, Michael I. Jordan - In Proceedings of Uncertainty in AI , 1999
"... Recently, researchers have demonstrated that "loopy belief propagation" --- the use of Pearl's polytree algorithm in a Bayesian network with loops --- can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performa ..."
Abstract - Cited by 680 (18 self) - Add to MetaCart
-limit performance of "Turbo Codes" --- codes whose decoding algorithm is equivalent to loopy belief propagation in a chain-structured Bayesian network. In this paper we ask: is there something special about the error-correcting code context, or does loopy propagation work as an approximate

Cost-Aware WWW Proxy Caching Algorithms

by Pei Cao, Sandy Irani - IN PROCEEDINGS OF THE 1997 USENIX SYMPOSIUM ON INTERNET TECHNOLOGY AND SYSTEMS , 1997
"... Web caches can not only reduce network traffic and downloading latency, but can also affect the distribution of web traffic over the network through costaware caching. This paper introduces GreedyDualSize, which incorporates locality with cost and size concerns in a simple and non-parameterized fash ..."
Abstract - Cited by 544 (6 self) - Add to MetaCart
Web caches can not only reduce network traffic and downloading latency, but can also affect the distribution of web traffic over the network through costaware caching. This paper introduces GreedyDualSize, which incorporates locality with cost and size concerns in a simple and non-parameterized

Greedy Function Approximation: A Gradient Boosting Machine

by Jerome H. Friedman - Annals of Statistics , 2000
"... Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed for additi ..."
Abstract - Cited by 951 (12 self) - Add to MetaCart
Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed

Factor Graphs and the Sum-Product Algorithm

by Frank R. Kschischang, Brendan J. Frey, Hans-Andrea Loeliger - IEEE TRANSACTIONS ON INFORMATION THEORY , 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
Abstract - Cited by 1787 (72 self) - Add to MetaCart
computational rule, the sum-product algorithm operates in factor graphs to compute---either exactly or approximately---various marginal functions by distributed message-passing in the graph. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can

A learning algorithm for Boltzmann machines

by H. Ackley, E. Hinton, J. Sejnowski - Cognitive Science , 1985
"... The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a probl ..."
Abstract - Cited by 586 (13 self) - Add to MetaCart
problem in o very short time. One kind of computation for which massively porollel networks appear to be well suited is large constraint satisfaction searches, but to use the connections efficiently two conditions must be met: First, a search technique that is suitable for parallel networks must be found

Irrelevant Features and the Subset Selection Problem

by George H. John, Ron Kohavi, Karl Pfleger - MACHINE LEARNING: PROCEEDINGS OF THE ELEVENTH INTERNATIONAL , 1994
"... We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small high-accuracy concepts. We examine notions of relevance and irrelevance, and show that the definitions used in the machine learning literature do not adequately partition the features ..."
Abstract - Cited by 741 (26 self) - Add to MetaCart
We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small high-accuracy concepts. We examine notions of relevance and irrelevance, and show that the definitions used in the machine learning literature do not adequately partition the features

Routing in a delay tolerant network

by Sushant Jain, Kevin Fall, Rabin Patra - Proceedings of ACM Sigcomm , 2004
"... We formulate the delay-tolerant networking routing problem, where messages are to be moved end-to-end across a connectivity graph that is time-varying but whose dynamics may be known in advance. The problem has the added constraints of finite buffers at each node and the general property that no con ..."
Abstract - Cited by 612 (8 self) - Add to MetaCart
We formulate the delay-tolerant networking routing problem, where messages are to be moved end-to-end across a connectivity graph that is time-varying but whose dynamics may be known in advance. The problem has the added constraints of finite buffers at each node and the general property

Consensus and cooperation in networked multi-agent systems

by Reza Olfati-saber, J. Alex Fax, Richard M. Murray - PROCEEDINGS OF THE IEEE
"... This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An overview of ..."
Abstract - Cited by 772 (2 self) - Add to MetaCart
of basic concepts of information consensus in networks and methods of convergence and performance analysis for the algorithms are provided. Our analysis framework is based on tools from matrix theory, algebraic graph theory, and control theory. We discuss the connections between consensus problems
Results 1 - 10 of 104,431