ESANN 2007 - PDF Preprint Papers

ESANN 2007

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ESANN
2007

242views Neural Networks» more ESANN 2007»

A hierarchical model for syllable recognition

13 years 6 months ago

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Inspired by recent ﬁndings on the similarities between the primary auditory and visual cortex we propose a neural network for speech recognition based on a hierarchical feedforw...

Xavier Domont, Martin Heckmann, Heiko Wersing, Fra...

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Id	Views	Title	Status

1	242	A hierarchical model for syllable recognition	claim
2	219	Agglomerative Independent Variable Group Analysis	claim
3	187	Toward a robust 2D spatio-temporal self-organization	claim
4	187	How to process uncertainty in machine learning?	claim
5	170	Feature clustering and mutual information for the selection of variables in spectral data	claim
6	152	Causality analysis of LFPs in micro-electrode arrays based on mutual information	claim
7	149	A novel kernel-based method for local pattern extraction in random process signals	claim
8	148	Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning	claim
9	147	Intrinsic plasticity for reservoir learning algorithms	claim
10	147	Several ways to solve the MSO problem	claim
11	144	Mixtures of robust probabilistic principal component analyzers	claim
12	144	One-class SVM regularization path and comparison with alpha seeding	claim
13	139	Exploring the causal order of binary variables via exponential hierarchies of Markov kernels	claim
14	139	Adaptive Global Metamodeling with Neural Networks	claim
15	136	Complexity bounds of radial basis functions and multi-objective learning	claim
16	135	Bat echolocation modelling using spike kernels with Support Vector Regression	claim
17	135	Kernel PCA based clustering for inducing features in text categorization	claim
18	135	Estimation of tangent planes for neighborhood graph correction	claim
19	134	Classifying n-back EEG data using entropy and mutual information features	claim
20	133	Model collisions in the dissimilarity SOM	claim
21	132	Systematicity in sentence processing with a recursive self-organizing neural network	claim
22	131	Computational Intelligence approaches to causality detection	claim
23	130	Three-dimensional self-organizing dynamical systems for discrete structures memorizing and retrieval	claim
24	130	"Kernelized" Self-Organizing Maps for Structured Data	claim
25	129	Controlling complexity of RBF networks by similarity	claim
26	128	A supervised learning approach based on STDP and polychronization in spiking neuron networks	claim
27	127	Optimizing kernel parameters by second-order methods	claim
28	127	Markovian blind separation of non-stationary temporally correlated sources	claim
29	126	Structured reservoir computing with spatiotemporal chaotic attractors	claim
30	125	A new feature selection scheme using data distribution factor for transactional data	claim
31	125	Replacing eligibility trace for action-value learning with function approximation	claim
32	124	Reinforcement learning in a nutshell	claim
33	123	Causality and communities in neural networks	claim
34	123	Clustering a medieval social network by SOM using a kernel based distance measure	claim
35	122	The Recurrent Control Neural Network	claim
36	121	SOM for intensity inhomogeneity correction in MRI	claim
37	117	An overview of reservoir computing: theory, applications and implementations	claim
38	117	Automatically searching near-optimal artificial neural networks	claim
39	116	The Intrinsic Recurrent Support Vector Machine	claim
40	115	Learning topology of a labeled data set with the supervised generative gaussian graph	claim
41	115	Ensemble neural classifier design for face recognition	claim
42	114	Deploying SDP for machine learning	claim
43	114	Tracking fast changing non-stationary distributions with a topologically adaptive neural network: application to video tracking	claim
44	113	Kernel-based online machine learning and support vector reduction	claim
45	112	Model Selection for Kernel Probit Regression	claim
46	110	A neural model of cross-modal association in insects	claim
47	110	Functional elements and networks in fMRI	claim
48	110	An Estimation of Response Certainty using Features of Eye-movements	claim
49	106	Order in Complex Systems of Nonlinear Oscillators: Phase Locked Subspaces	claim
50	106	Pattern Recognition using Chaotic Transients	claim
51	104	Self-organized chains for clustering	claim
52	104	Nearest Neighbor Distributions and Noise Variance Estimation	claim
53	103	Interval discriminant analysis using support vector machines	claim
54	102	ICA-based High Frequency VaR for Risk Management	claim
55	100	Collaborative Filtering with interlaced Generalized Linear Models	claim
56	99	Transition from initialization to working stage in biologically realistic networks	claim
57	99	Visualisation of tree-structured data through generative probabilistic modelling	claim
58	96	A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning	claim
59	96	SOM+EOF for finding missing values	claim
60	96	Informational cost in correlation-based neuronal networks	claim
61	89	Kernel on Bag of Paths For Measuring Similarity of Shapes	claim
62	89	Sparsely-connected associative memory models with displaced connectivity	claim
63	89	Immediate Reward Reinforcement Learning for Projective Kernel Methods	claim
64	86	Convex optimization for the design of learning machines	claim
65	85	Synchronization and acceleration: complementary mechanisms of temporal coding	claim
66	84	Human motion recognition using Nonlinear Transient Computation	claim
67	74	Spicules-based competitive neural network	claim
68	69	Spiral Recurrent Neural Network for Online Learning	claim

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