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Efficient exact stochastic simulation of chemical systems with many species and many channels

by Michael A. Gibson, Jehoshua Bruck - J. Phys. Chem. A , 2000
"... There are two fundamental ways to view coupled systems of chemical equations: as continuous, represented by differential equations whose variables are concentrations, or as discrete, represented by stochastic processes whose variables are numbers of molecules. Although the former is by far more comm ..."
Abstract - Cited by 427 (5 self) - Add to MetaCart
common, systems with very small numbers of molecules are important in some applications (e.g., in small biological cells or in surface processes). In both views, most complicated systems with multiple reaction channels and multiple chemical species cannot be solved analytically. There are exact numerical

Studies of transformation of Escherichia coli with plasmids

by Douglas Hanahan - J. Mol. Biol , 1983
"... Factors that affect he probability of genetic transformation f Escherichia coli by plasmids have been evaluated. A set of conditions is described under which about one in every 400 plasmid molecules produces a transformed cell. These conditions include cell growth in medium containing elevated level ..."
Abstract - Cited by 1632 (1 self) - Add to MetaCart
probabilities. Non-transforming DNAs compete consistent with mass. No significant variation is observed between competing DNAs of difi~rent source, complexity, length or form. Competition with both transforming and non-transforming plasmids indicates that each cell is capable of taking up many DNA molecules

Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers

by Erin L. Allwein, Robert E. Schapire, Yoram Singer - JOURNAL OF MACHINE LEARNING RESEARCH , 2000
"... We present a unifying framework for studying the solution of multiclass categorization problems by reducing them to multiple binary problems that are then solved using a margin-based binary learning algorithm. The proposed framework unifies some of the most popular approaches in which each class ..."
Abstract - Cited by 561 (20 self) - Add to MetaCart
We present a unifying framework for studying the solution of multiclass categorization problems by reducing them to multiple binary problems that are then solved using a margin-based binary learning algorithm. The proposed framework unifies some of the most popular approaches in which each class

SEAD: Secure Efficient Distance Vector Routing for Mobile Wireless Ad Hoc Networks

by Yih-Chun Hu, David B. Johnson, Adrian Perrig , 2003
"... An ad hoc network is a collection of wireless computers (nodes), communicating among themselves over possibly multihop paths, without the help of any infrastructure such as base stations or access points. Although many previous ad hoc network routing protocols have been based in part on distance vec ..."
Abstract - Cited by 534 (8 self) - Add to MetaCart
An ad hoc network is a collection of wireless computers (nodes), communicating among themselves over possibly multihop paths, without the help of any infrastructure such as base stations or access points. Although many previous ad hoc network routing protocols have been based in part on distance

Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks

by J. Nicholas Laneman, Gregory W. Wornell - IEEE TRANS. INF. THEORY , 2003
"... We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a m ..."
Abstract - Cited by 622 (5 self) - Add to MetaCart
We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a

Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms

by N. Srinivas, Kalyanmoy Deb - Evolutionary Computation , 1994
"... In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about t ..."
Abstract - Cited by 539 (5 self) - Add to MetaCart
In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about

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
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

K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation

by Michal Aharon, et al. , 2006
"... In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and inc ..."
Abstract - Cited by 935 (41 self) - Add to MetaCart
In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many

The Dantzig selector: statistical estimation when p is much larger than n

by Emmanuel Candes, Terence Tao , 2005
"... In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Ax + z, where x ∈ R p is a parameter vector of interest, A is a data matrix with possibly far fewer rows than columns, n ≪ ..."
Abstract - Cited by 879 (14 self) - Add to MetaCart
In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Ax + z, where x ∈ R p is a parameter vector of interest, A is a data matrix with possibly far fewer rows than columns, n

Max-margin Markov networks

by Ben Taskar, Carlos Guestrin, Daphne Koller , 2003
"... In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the margin of confidence of the classifier, are the method of choice for many such tasks. Their popularity stems both from the ..."
Abstract - Cited by 604 (15 self) - Add to MetaCart
the ability to use high-dimensional feature spaces, and from their strong theoretical guarantees. However, many real-world tasks involve sequential, spatial, or structured data, where multiple labels must be assigned. Existing kernel-based methods ignore structure in the problem, assigning labels
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