Incremental Semiparametric Inverse Dynamics Learning
January 18, 2016 ยท Declared Dead ยท ๐ IEEE International Conference on Robotics and Automation
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Raffaello Camoriano, Silvio Traversaro, Lorenzo Rosasco, Giorgio Metta, Francesco Nori
arXiv ID
1601.04549
Category
stat.ML: Machine Learning (Stat)
Cross-listed
cs.LG,
cs.RO
Citations
51
Venue
IEEE International Conference on Robotics and Automation
Last Checked
5 months ago
Abstract
This paper presents a novel approach for incremental semiparametric inverse dynamics learning. In particular, we consider the mixture of two approaches: Parametric modeling based on rigid body dynamics equations and nonparametric modeling based on incremental kernel methods, with no prior information on the mechanical properties of the system. This yields to an incremental semiparametric approach, leveraging the advantages of both the parametric and nonparametric models. We validate the proposed technique learning the dynamics of one arm of the iCub humanoid robot.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Machine Learning (Stat)
๐ฎ
๐ฎ
The Ethereal
๐ฎ
๐ฎ
The Ethereal
Layer Normalization
๐ฎ
๐ฎ
The Ethereal
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
R.I.P.
๐ป
Ghosted
Variational Inference with Normalizing Flows
๐
๐
The Cartographer
Towards A Rigorous Science of Interpretable Machine Learning
R.I.P.
๐ป
Ghosted
Optimization Methods for Large-Scale Machine Learning
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
๐ป
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
๐ป
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
๐ป
Ghosted