The proceedings contain 89 papers. The topics discussed include: mahalanobis-based one-class classification;improving the robustness of surface enhanced Raman spectroscopy based sensors by Bayesian non-negative matrix...
ISBN:
(纸本)9781479936946
The proceedings contain 89 papers. The topics discussed include: mahalanobis-based one-class classification;improving the robustness of surface enhanced Raman spectroscopy based sensors by Bayesian non-negative matrix factorization;data mining by nonnegative tensor approximation;non-negative tensor factorization with missing data for the modeling of gene expressions in the human brain;multiple speaker tracking with the factorial von mises-fisher filter;a probabilistic approach to hearing loss compensation;coherent time modeling of semi-Markov models with application to real-time audio-to-score alignment;ultra-low-power voice-activity-detector through context and resource-cost-aware feature selection in decision trees;and a probabilistic approach for phase estimation in single-channel speech enhancement using von mises phase priors.
The proceedings contain 102 papers. The topics discussed include: non-negative matrix completion for bandwidth extension: a convex optimization approach;diffusion map for clustering FMRI spatial maps extracted by inde...
ISBN:
(纸本)9781479911806
The proceedings contain 102 papers. The topics discussed include: non-negative matrix completion for bandwidth extension: a convex optimization approach;diffusion map for clustering FMRI spatial maps extracted by independent component analysis;segmentation of medical images based on hierarchical evolutionary and bee algorithms;the linear process mixture model;video-informed approach for enhancing audio source separation through noise source suppression;introducing a simple fusion framework for audio source separation;orthogonal segmented model for underdetermined blind identification and separation of sources with sparse events;a constrained approach for extraction of pre-ICTAL discharges from scalp EEG;complex support vector machines for quaternary classification;MOGT: oversampling with a parsimonious mixture of Gaussian trees model for imbalanced time-series classification;and non-linear noise adaptive Kalman filtering via variational Bayes.
The proceedings contain 65 papers. The topics discussed include: local linear ICA for mutual information estimation in feature selection;a proposal for blind FIR equalization of time-varying channels;overcomplete blin...
详细信息
ISBN:
(纸本)0780395174
The proceedings contain 65 papers. The topics discussed include: local linear ICA for mutual information estimation in feature selection;a proposal for blind FIR equalization of time-varying channels;overcomplete blind source separation by combining ICA and binary time-frequency masking;ICA by maximization of nongaussianity using complex functions;blind source separation and sparse bump modelling of time frequency representation of EEG signals: New tools for early detection of Alzheimer's disease;implementing nonlinear algorithm in multimicrophone signalprocessing;multi-scale kernel methods for classification;a robust linear programming based boosting algorithm;automatic determination of the number of clusters using spectral algorithms;an extension of iterative scaling for joint decision-level and feature-level fusion in ensemble classification;and supervised neural network training using the minimum error entropy criterion with variable-size and finite-support kernel estimates.
The proceedings contain 75 papers. The topics discussed include: model-order selection in statistical shape models;monaural speech separation using a phase-aware deep denoising auto encoder;variational Bayesian partia...
ISBN:
(纸本)9781538654774
The proceedings contain 75 papers. The topics discussed include: model-order selection in statistical shape models;monaural speech separation using a phase-aware deep denoising auto encoder;variational Bayesian partially observed non-negative tensor factorization;nonlinear probabilistic latent variable models for groupwise correspondence analysis in brain structures;uncertainty bounds for kernel-based regression: a Bayesian SPS approach;frame-level proximity and touch recognition using capacitive sensing and semi-supervised sequential modeling;a variance modeling framework based on variational autoencoders for speech enhancement;correcting boundary over-exploration deficiencies in Bayesian optimization with virtual derivative sign observations;single-channel EEG classification by multi-channel tensor subspace learning and regression;learning sparse structured ensembles with stochastic gradient MCMC sampling and network pruning;convolutional neural networks for noise signal recognition;deep learning based speed estimation for constraining strapdown inertial navigation on smartphones;a multi-layer perceptron applied to number of target indication for direction-of-arrival estimation in automotive radar sensors;APE: archetypal-prototypal embeddings for audio classification;a characterization of the edge of criticality in binary echo state networks;and controlling blood glucose levels in patients with type 1 diabetes using fitted q-iterations and functional features.
Scattering Transforms (or ScatterNets) introduced by Mallat in [1] are a promising start into creating a well-defined feature extractor to use for pattern recognition and image classification tasks. They are of partic...
详细信息
暂无评论