functions support vector machines and neural networks

... e.g Lee and Myaeng’s (2002) genre and subject detection work and Boulis and Ostendorf’s (2005) work on feature selection for topic classification For our LM classifiers, we followed Boulis and Ostendorf’s ... categorization with support vector machines: learning with many relevant features In Proc of the European Conference on Machine Learning, pages 137–142, 1998a T Joachims Making large-scale support vector ... scores are relative to the most common 100, 200 and 500 words in the lowest grade level c∈C P (c|w) log P (c|w) c∈C + P (w) ¯ 4.3 Support Vector Machines • 12 language model perplexity scores...

Ngày tải lên: 20/02/2014, 15:20

... III and e Marcu (2005)’s R-2 score was 0.071 [0.067–0.074] and R-SU4 was 0.126 [0.123–0.129] and it is better than the DUC-2005 Fisher and Roark supervised approach with an R-2 of 0.066 and an ... (which happens in The mean, median, standard deviation and histogram of the overlapping distribution are calculated and included as features this case), and a simple iterative procedure called ... text in the SCU label and all its contributors is stemmed and stop words are removed, obtaining a set of stem vectors for each SCU The system summary text is also stemmed and freed from stop words...

Ngày tải lên: 20/02/2014, 12:20

... h b ` `9' h )' R ` Ơ 6ƠHD#@#Vq kFsvHIPH&H&@3F9 pn#ƠHbq 400 500 600 700 Number of Support Vectors 800 900 1000 X 300 0.5 0 0.5 1.5 2.5 3.5 Number of Samples 4.5 x 10 41 Time (hours) ... hE F9 0 300 0.5 1.5 2.5 3.5 Number of Samples x 10 4 4.5 0.5 400 Time (hours) Number of Support Vectors 1.5 2.5 3.5 500 600 700 800 900 4.5 1000 G 9' ) & ) b X & G RrAA )1 RA y 15 A5' B...

Ngày tải lên: 24/04/2014, 12:33

... Introduction Linear support vector machines Nonlinear support vector machines Multiclass support vector machines Other issues Challenges for kernel methods and SVMs 10 Linear support vector machines The ... Introduction Linear support vector machines Nonlinear support vector machines Multiclass support vector machines Other issues Challenges for kernel methods and SVMs 36 Multiclass support vector machines ... optimal weight vector 18 Content Introduction Linear support vector machines Nonlinear support vector machines Multiclass support vector machines Other issues Challenges for kernel methods and SVMs...

Ngày tải lên: 12/10/2015, 08:47

Ngày tải lên: 01/03/2013, 17:01

... scalar random variables; generalization of the theory to vector random variables is a straightforward matter Suppose we are given the observable yk ¼ xk þ vk ; where xk is an unknown signal and vk ... first-order Taylor approximation of the nonlinear functions Fðk; xk Þ and ^ ^k Hðk; xk Þ around xk and xÀ, respectively Specifically, Fðk; xk Þ and Hðk; xk Þ are approximated as follows ^ ^ Fðk; ... Wiley, 1986 [3] M.S Grewal and A.P Andrews, Kalman Filtering: Theory and Practice Englewood Cliffs, NJ: Prentice-Hall, 1993 [4] H.L Van Trees, Detection, Estimation, and Modulation Theory, Part...

Ngày tải lên: 13/12/2013, 13:15

... response vector yk as a nonlinear function of the input vector uk , the weight parameter vector wk , and, for recurrent networks, the recurrent node activations vk ; this equation is augmented by random ... Saad, D.V Prokhorov, and D.C Wunsch III, ‘‘Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks, ’’ IEEE Transactions on Neural Networks, 9, 1456–1470 ... (1998) [21] K.-C Jim, C.L Giles, and B.G Horne, ‘‘An analysis of noise in recurrent neural networks: convergence and generalization,’’ IEEE Transactions on Neural Networks, 7, 1424–1438 (1996) [22]...

Ngày tải lên: 14/12/2013, 13:15

...  circle moving right and up; square moving right and down; triangle moving right and up; circle moving right and down; square moving right and up; triangle moving right and down Training was ... Cortex, 1, 1–47 (1991) [2] J.S Lund, Q Wu and J.B Levitt, ‘‘Visual cortex cell types and connections’’, in M.A Arbib, Ed., Handbook of Brain Theory and Neural Networks, Cambridge, MA: MIT Press, 1995 ... Rao and Ballard [10] have proposed an alternative neural network implementation of the EKF that employs topdown feedback between layers, and have applied their model to both static images and...

Ngày tải lên: 14/12/2013, 13:15

... selected similar to the noise-free case, and two distinct networks were trained using the noisy Lorenz signals with 25 dB SNR and 10 dB SNR, respectively The networks were trained with a learning ... in D.A Rand and L.S Young, Eds Dynamical Systems and Turbulence, Warwick 1980, Lecture Notes in Mathematics Vol 898 1981, p 230 Berlin: Springer-Verlag [6] A.M Fraser, ‘‘Information and entropy ... prediction, a delay vector consisting of taps spaced by 10 samples apart is constructed as dictated by the embedding parameters dE and t The RMLP is initialized with a delay vector, constructed...

Ngày tải lên: 14/12/2013, 13:15

... Atlas, ‘‘Recurrent neural networks and robust time series prediction,’’ IEEE Transactions on Neural Networks, 5(2), 240–254 (1994) [15] S.C Stubberud and M Owen, ‘‘Artificial neural network feedback ... Puskorius and L.A Feldkamp, ‘ Neural control of nonlinear dynamic systems with Kalman filter trained recurrent networks, ’’ IEEE Transactions on Neural Networks, (1994) [32] E.S Plumer, ‘‘Training neural ... Recognition and Neural Networks Cambridge University Press, 1996 [39] T.M Cover and J.A Thomas, Elements of Information Theory New York: Wiley, 1991 [40] G.V Puskorius and L.A Feldkamp, ‘‘Extensions and...

Ngày tải lên: 14/12/2013, 13:15

... matrices A and B multiplying inputs x and u, respectively; and an output bias vector b, and the noise covariance Q Each RBF is assumed to be a Gaussian in x space, with center ci and width given ... RBF networks with a center on each data point has been used by Tipping [50] successfully for nonlinear regression, and given the name ‘‘relevance vector machine’’ in analogy to support vector machines ... estimation for nonlinear dynamical systems and also as a basis for on-line learning algorithms for feedforward neural networks [15] and radial basis function networks [16, 17] For more details, see...

Ngày tải lên: 14/12/2013, 13:15

... learning the parameters The use of the EKF for training neural networks has been developed by Singhal and Wu [8] and Puskorious and Feldkamp [9], and is covered in Chapter of this book The use of the ... estimation with neural networks Double Inverted Pendulum A double inverted pendulum (see Fig 7.4) has states corresponding to cart position and velocity, and top and _ _ _ bottom pendulum angle and angular ... autoregressive neural network with random weights driven by Gaussian process noise and also corrupted by additive white Gaussian noise (SNR % dB) A standard 6-10-1 MLP with hidden activation functions and...

Ngày tải lên: 14/12/2013, 13:15

... selected similar to the noise-free case, and two distinct networks were trained using the noisy Lorenz signals with 25 dB SNR and 10 dB SNR, respectively The networks were trained with a learning ... in D.A Rand and L.S Young, Eds Dynamical Systems and Turbulence, Warwick 1980, Lecture Notes in Mathematics Vol 898 1981, p 230 Berlin: Springer-Verlag [6] A.M Fraser, ‘‘Information and entropy ... prediction, a delay vector consisting of taps spaced by 10 samples apart is constructed as dictated by the embedding parameters dE and t The RMLP is initialized with a delay vector, constructed...

Ngày tải lên: 23/12/2013, 07:16

... Atlas, ‘‘Recurrent neural networks and robust time series prediction,’’ IEEE Transactions on Neural Networks, 5(2), 240–254 (1994) [15] S.C Stubberud and M Owen, ‘‘Artificial neural network feedback ... Puskorius and L.A Feldkamp, ‘ Neural control of nonlinear dynamic systems with Kalman filter trained recurrent networks, ’’ IEEE Transactions on Neural Networks, (1994) [32] E.S Plumer, ‘‘Training neural ... Recognition and Neural Networks Cambridge University Press, 1996 [39] T.M Cover and J.A Thomas, Elements of Information Theory New York: Wiley, 1991 [40] G.V Puskorius and L.A Feldkamp, ‘‘Extensions and...

Ngày tải lên: 23/12/2013, 07:16

... matrices A and B multiplying inputs x and u, respectively; and an output bias vector b, and the noise covariance Q Each RBF is assumed to be a Gaussian in x space, with center ci and width given ... RBF networks with a center on each data point has been used by Tipping [50] successfully for nonlinear regression, and given the name ‘‘relevance vector machine’’ in analogy to support vector machines ... estimation for nonlinear dynamical systems and also as a basis for on-line learning algorithms for feedforward neural networks [15] and radial basis function networks [16, 17] For more details, see...

Ngày tải lên: 23/12/2013, 07:16

... learning the parameters The use of the EKF for training neural networks has been developed by Singhal and Wu [8] and Puskorious and Feldkamp [9], and is covered in Chapter of this book The use of the ... estimation with neural networks Double Inverted Pendulum A double inverted pendulum (see Fig 7.4) has states corresponding to cart position and velocity, and top and _ _ _ bottom pendulum angle and angular ... autoregressive neural network with random weights driven by Gaussian process noise and also corrupted by additive white Gaussian noise (SNR % dB) A standard 6-10-1 MLP with hidden activation functions and...

Ngày tải lên: 23/12/2013, 07:16

... Cherkassky and Mulier = LEARNING FROM DATA: Concepts, Theory, and Methods Diamantaras and Kung = PRINCIPAL COMPONENT NEURAL NETWORKS: Theory and Applications Haykin = KALMAN FILTERING AND NEURAL NETWORKS ... Sanchez-Pena and Sznaler = ROBUST SYSTEMS THEORY AND ´ ˜ APPLICATIONS Sandberg, Lo, Fancourt, Principe, Katagiri, and Haykin = NONLINEAR DYNAMICAL SYSTEMS: Feedforward Neural Network Perspectives ´ Tao and ... Kristic, Kanellakopoulos, and Kokotovic = NONLINEAR AND ADAPTIVE CONTROL DESIGN Nikias and Shao = SIGNAL PROCESSING WITH ALPHA-STABLE DISTRIBUTIONS AND APPLICATIONS Passino and Burgess = STABILITY...

Ngày tải lên: 23/12/2013, 07:16