Results 1 - 10 of 28,105

A Learning Algorithm for Continually Running Fully Recurrent Neural Networks

by Ronald J. Williams, David Zipser , 1989
"... The exact form of a gradient-following learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a precis ..."
Abstract - Cited by 534 (4 self) - Add to MetaCart
The exact form of a gradient-following learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a

A volumetric method for building complex models from range images,”

by Brian Curless , Marc Levoy - in Proceedings of the 23rd annual conference on Computer graphics and interactive techniques. ACM, , 1996
"... Abstract A number of techniques have been developed for reconstructing surfaces by integrating groups of aligned range images. A desirable set of properties for such algorithms includes: incremental updating, representation of directional uncertainty, the ability to fill gaps in the reconstruction, ..."
Abstract - Cited by 1020 (17 self) - Add to MetaCart
with one range image at a time, we first scan-convert it to a distance function, then combine this with the data already acquired using a simple additive scheme. To achieve space efficiency, we employ a run-length encoding of the volume. To achieve time efficiency, we resample the range image to align

Fibonacci Heaps and Their Uses in Improved Network optimization algorithms

by Michael L. Fredman, Robert Endre Tarjan , 1987
"... In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated F-heaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. F-heaps support arbitrary deletion from an n-item 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 F-heaps we are able to obtain improved running times for several network optimization algorithms. In particular, we obtain the following worst-case bounds, where n is the number of vertices and m the number of edges

The particel swarm: Explosion, stability, and convergence in a multi-dimensional complex space

by Maurice Clerc, James Kennedy - IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTION
"... The particle swarm is an algorithm for finding optimal regions of complex search spaces through interaction of individuals in a population of particles. Though the algorithm, which is based on a metaphor of social interaction, has been shown to perform well, researchers have not adequately explained ..."
Abstract - Cited by 852 (10 self) - Add to MetaCart
The particle swarm is an algorithm for finding optimal regions of complex search spaces through interaction of individuals in a population of particles. Though the algorithm, which is based on a metaphor of social interaction, has been shown to perform well, researchers have not adequately

A NEW POLYNOMIAL-TIME ALGORITHM FOR LINEAR PROGRAMMING

by N. Karmarkar - COMBINATORICA , 1984
"... We present a new polynomial-time algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than the ell ..."
Abstract - Cited by 860 (3 self) - Add to MetaCart
We present a new polynomial-time algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than

Depth-first Iterative-Deepening: An Optimal Admissible Tree Search

by Richard E. Korf - Artificial Intelligence , 1985
"... The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadth-first search requires too much space and depth-first search can use too much time and doesn't always find a cheapest path. A depth-first iteratiw-deepening a ..."
Abstract - Cited by 527 (24 self) - Add to MetaCart
The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadth-first search requires too much space and depth-first search can use too much time and doesn't always find a cheapest path. A depth-first iteratiw

Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization

by Farid Alizadeh - SIAM Journal on Optimization , 1993
"... We study the semidefinite programming problem (SDP), i.e the problem of optimization of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as specialized to S ..."
Abstract - Cited by 547 (12 self) - Add to MetaCart
mechanical way to algorithms for SDP with proofs of convergence and polynomial time complexity also carrying over in a similar fashion. Finally we study the significance of these results in a variety of combinatorial optimization problems including the general 0-1 integer programs, the maximum clique

Space-time block codes from orthogonal designs

by Vahid Tarokh, Hamid Jafarkhani, A. R. Calderbank - IEEE Trans. Inform. Theory , 1999
"... Abstract — We introduce space–time block coding, a new paradigm for communication over Rayleigh fading channels using multiple transmit antennas. Data is encoded using a space–time block code and the encoded data is split into � streams which are simultaneously transmitted using � transmit antennas. ..."
Abstract - Cited by 1524 (42 self) - Add to MetaCart
space–time block codes for both real and complex constellations for any number of transmit antennas. These codes achieve the maximum possible transmission rate for any number of transmit antennas using any arbitrary real constellation such as PAM. For an arbitrary complex constellation such as PSK

STATEMATE: A Working Environment for the Development of Complex Reactive Systems

by David Harel, Hagi Lachover, Amnon Naamad, Amir Pnueli, Michal Politi, Rivi Sherman, Aharon Shtull-trauring, Mark Trakhtenbrot - IEEE Transactions on Software Engineering , 1990
"... This paper provides an overview of the STATEMATE system, constructed over the past several years by the authors and their colleagues at Ad Cad Ltd., the R&D subsidiary of i-Logix, Inc. STATEMATE is a set of tools, with a heavy graphical orientation, in- tended for the specification, analysis, d ..."
Abstract - Cited by 485 (7 self) - Add to MetaCart
, design, and documentation of large and complex reactive systems, such as real-time embedded sys- tems, control and communication systems, and interactive software or hardware. It enables a user to prepare, analyze, and debug diagram- matic, yet precise, descriptions of the system under development from

CoSaMP: Iterative signal recovery from incomplete and inaccurate samples

by D. Needell, J. A. Tropp - California Institute of Technology, Pasadena , 2008
"... Abstract. Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery alg ..."
Abstract - Cited by 770 (13 self) - Add to MetaCart
with the sampling matrix. For compressible signals, the running time is just O(N log 2 N), where N is the length of the signal. 1.
Results 1 - 10 of 28,105