C. Richard

Latest

• Online change-point detection with kernels
• Deep Deconvolution for Traffic Analysis with Distributed Acoustic Sensing Data
• A Self-Supervised Deep Learning Approach for Blind Denoising and Waveform Coherence Enhancement in Distributed Acoustic Sensing data
• Self-Supervised Velocity Field Learning for High-Resolution Traffic Monitoring with Distributed Acoustic Sensing
• Deep Deconvolution Applied to Distributed Acoustic Sensing for Traffic Analysis
• Online Graph-Based Change Point Detection in Multiband Image Sequences
• Non-parametric community change-points detection in streaming graph signals
• Distributed change detection in streaming graph signals
• Kernel based online change point detection
• Non-parametric community change-points detection in streaming graph signals
• Non-Parametric Online Change-Point Detection with Kernel LMS By Relative Density Ratio Estimation
• ADA-PT: An Adaptive Parameter Tuning Strategy Based on the Weighted Stein Unbiased Risk Estimator
• Diffusion LMS for Multitask Problems With Local Linear Equality Constraints
• Unmixing of multispectral photoacoustic images
• Distributed approach for deblurring large images with shift-variant blur
• A Telemetry Monitoring System Using the One-Class SVM Method
• Nonlinear Unmixing of Hyperspectral Data With Vector-Valued Kernel Functions
• Proximal Multitask Learning Over Networks With Sparsity-Inducing Coregularization
• Diffusion LMS over multitask networks with noisy links
• Multitask Diffusion Adaptation Over Asynchronous Networks
• Spatial regularization for nonlinear unmixing of hyperspectral data with vector-valued kernel functions
• Improving Spacecraft Health Monitoring with Automatic Anomaly Detection Techniques
• Diffusion LMS over multitask networks with noisy links
• Unsupervised neighbor dependent nonlinear unmixing
• Estimation distribuée sur les réseaux multitâches en présence d'échanges d'informations bruitées
• Modèle non-linéaire et semi-paramétrique pour le démélange non-supervisé d'images hyperspectrales
• Hyperspectral data unmixing with graph-based regularization
• A graph Laplacian regularization for hyperspectral data unmixing
• Multitask diffusion LMS with sparsity-based regularization
• Blind and Fully Constrained Unmixing of Hyperspectral Images
• Performance analysis of multitask diffusion adaptation over asynchronous networks
• Distributed image reconstruction for very large arrays in radio astronomy
• GLUP: yet another algorithm for blind unmixing of hyperspectral data
• Group Lasso avec contraintes de positivité et de somme unité pour le dé mé lange non-supervisé des images hyperspectrales
• Nonlinear unmixing of hyperspectral data with partially linear least-squares support vector regression
• Adaptive inverse control using kernel identification
• Transitional surrogates
• Distributed learning with kernels in wireless sensor networks for physical phenomena modeling and tracking
• Transductive kernel matrix learning with hierarchic Bayesian model, application to hyperspectral images