Strictly Positive-Definite Spike Train Kernels for Point-Process Divergences
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[1] N. Dyn,et al. Multivariate Approximation and Applications: Index , 2001 .
[2] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[3] J. McFadden. The Entropy of a Point Process , 1965 .
[4] Carl E. Rasmussen,et al. Prediction on Spike Data Using Kernel Algorithms , 2003, NIPS.
[5] M. DeWeese,et al. Binary Spiking in Auditory Cortex , 2003, The Journal of Neuroscience.
[6] José Carlos Príncipe,et al. Quantification of inter-trial non-stationarity in spike trains from periodically stimulated neural cultures , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.
[7] Alfréd Rényi,et al. On an extremal property of the poisson process , 1964 .
[8] Bernhard Schölkopf,et al. Injective Hilbert Space Embeddings of Probability Measures , 2008, COLT.
[9] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[10] Andreas Christmann,et al. Universal Kernels on Non-Standard Input Spaces , 2010, NIPS.
[11] G. P. Moore,et al. Neuronal spike trains and stochastic point processes. I. The single spike train. , 1967, Biophysical journal.
[12] Conor J. Houghton,et al. Studying spike trains using a van Rossum metric with a synapse-like filter , 2009, Journal of Computational Neuroscience.
[13] Le Song,et al. Hilbert Space Embeddings of Hidden Markov Models , 2010, ICML.
[14] T. Sejnowski,et al. Regulation of spike timing in visual cortical circuits , 2008, Nature Reviews Neuroscience.
[15] José Carlos Príncipe,et al. A comparison of binless spike train measures , 2010, Neural Computing and Applications.
[16] Shun-ichi Amari,et al. Discrimination with Spike Times and ISI Distributions , 2008, Neural Computation.
[17] Wulfram Gerstner,et al. Improved Similarity Measures for Small Sets of Spike Trains , 2010 .
[18] T. Albright. Direction and orientation selectivity of neurons in visual area MT of the macaque. , 1984, Journal of neurophysiology.
[19] Daryl J. Daley,et al. An Introduction to the Theory of Point Processes , 2013 .
[20] Yoram Singer,et al. Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces , 2005, Neural Computation.
[21] Kenji Fukumizu,et al. Universality, Characteristic Kernels and RKHS Embedding of Measures , 2010, J. Mach. Learn. Res..
[22] Peter Dayan,et al. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems , 2001 .
[23] M. Buhmann. Multivariate Approximation and Applications: Approximation and interpolation with radial functions , 2001 .
[24] José Carlos Príncipe,et al. 2011 Ieee International Workshop on Machine Learning for Signal Processing an Adaptive Decoder from Spike Trains to Micro-stimulation Using Kernel Least-mean-squares (klms) , 2022 .
[25] K. H. Britten,et al. A relationship between behavioral choice and the visual responses of neurons in macaque MT , 1996, Visual Neuroscience.
[26] D. Gardner. Neurodatabase.org: networking the microelectrode , 2004, Nature Neuroscience.
[27] Nicholas Fisher,et al. A Novel Kernel for Learning a Neuron Model from Spike Train Data , 2010, NIPS.
[28] Le Song,et al. A Hilbert Space Embedding for Distributions , 2007, Discovery Science.
[29] D. Hubel,et al. Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.
[30] R. Duin,et al. The dissimilarity representation for pattern recognition , a tutorial , 2009 .
[31] Austin J. Brockmeier,et al. A novel family of non-parametric cumulative based divergences for point processes , 2010, NIPS.
[32] Jonathan D. Victor,et al. Metric-space analysis of spike trains: theory, algorithms and application , 1998, q-bio/0309031.
[33] Stefan Rotter,et al. Measurement of variability dynamics in cortical spike trains , 2008, Journal of Neuroscience Methods.
[34] C. Berg,et al. Harmonic Analysis on Semigroups: Theory of Positive Definite and Related Functions , 1984 .
[35] Bernhard Schölkopf,et al. Support vector learning , 1997 .
[36] José Carlos Príncipe,et al. A Unified Framework for Quadratic Measures of Independence , 2011, IEEE Transactions on Signal Processing.
[37] Justin C. Sanchez,et al. Adaptive Inverse Control of Neural Spatiotemporal Spike Patterns With a Reproducing Kernel Hilbert Space (RKHS) Framework , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[38] C. Diks,et al. Nonparametric Tests for Serial Independence Based on Quadratic Forms , 2005 .
[39] Zaïd Harchaoui,et al. A Fast, Consistent Kernel Two-Sample Test , 2009, NIPS.
[40] Andrew M. Clark,et al. Stimulus onset quenches neural variability: a widespread cortical phenomenon , 2010, Nature Neuroscience.
[41] R. Reid,et al. Precise Firing Events Are Conserved across Neurons , 2002, The Journal of Neuroscience.
[42] Bernhard Schölkopf,et al. A Kernel Method for the Two-Sample-Problem , 2006, NIPS.
[43] J.C. Principe,et al. Innovating Signal Processing for Spike Train Data , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[44] J. Victor. Binless strategies for estimation of information from neural data. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[45] Robert P. W. Duin,et al. The Dissimilarity Representation for Pattern Recognition - Foundations and Applications , 2005, Series in Machine Perception and Artificial Intelligence.
[46] José Carlos Príncipe,et al. A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing , 2009, Neural Computation.
[47] A. Pinkus. Strictly Hermitian positive definite functions , 2004, math/0404013.
[48] Bernhard Schölkopf,et al. Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions , 2009, NIPS.
[49] C. Berg,et al. Harmonic Analysis on Semigroups , 1984 .
[50] Yunmei Chen,et al. A test of independence based on a generalized correlation function , 2011, Signal Process..
[51] Benjamin Schrauwen,et al. Linking non-binned spike train kernels to several existing spike train metrics , 2006, ESANN.
[52] R. Johansson,et al. First spikes in ensembles of human tactile afferents code complex spatial fingertip events , 2004, Nature Neuroscience.
[53] José Carlos Príncipe,et al. Kernel Methods on Spike Train Space for Neuroscience: A Tutorial , 2013, IEEE Signal Processing Magazine.
[54] Mark C. W. van Rossum,et al. A Novel Spike Distance , 2001, Neural Computation.