mlsp 2020

Parameter estimation in non-linear state-space models by automatic differentiation of non-linear Kalman filters

PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation

Block-wise Minimization-Majorization algorithm for Huber''s criterion: sparse learning and applications

Approximate Gaussian Process Regression and Performance Analysis Using Composite Likelihood

PERFORMANCE-COMPLEXITY TRADE-OFF IN LARGE DIMENSIONAL STATISTICS

Robust Semiparametric Joint Estimators of Location and Scatter in Elliptical Distributions

DIFFUSION FIELD ESTIMATION USING DECENTRALIZED KERNEL KALMAN FILTER WITH PARAMETER LEARNING OVER HIERARCHICAL SENSOR NETWORKS

AERIAL SPECTRUM SURVEYING: RADIO MAP ESTIMATION WITH AUTONOMOUS UAVS

Fast Variational Learning in State-Space Gaussian Process Models

Online Supervised Acoustic System Identification exploiting Prelearned Local Affine Subspace Models

Non-linearities in Gaussian processes with integral observations