Tensor Decompositions for Modeling Inverse Dynamics
نویسندگان
چکیده
منابع مشابه
Tensor Decompositions for Modeling Inverse Dynamics
Modeling inverse dynamics is crucial for accurate feedforward robot control. The model computes the necessary joint torques, to perform a desired movement. The highly non-linear inverse function of the dynamical system can be approximated using regression techniques. We propose as regression method a tensor decomposition model that exploits the inherent threeway interaction of positions × veloc...
متن کاملTensor Decompositions for Probabilistic Classification
Tensor decompositions are introduced as a novel approach to probabilistic classification and can be interpreted as a particular kind of mixture model. Since many problems in medicine and biology can be described as a classification problem, the approach is seen as a useful tool for biomedical data analysis. The approach is validated by means of a clinical database consisting of data about 1002 ...
متن کاملComputational optimization for tensor decompositions
Further advances depend critically on algorithms that are robust, accurate, numerically stable, and fast. Despite widespread interest, the computational tools available to practitioners have not changed dramatically for nearly four decades. State-of-the-art methods are based on simple alternating least squares (ALS); this approach is often slow to converge and there are few guarantees that it w...
متن کاملCanonical Tensor Decompositions
The Singular Value Decomposition (SVD) may be extended to tensors at least in two very different ways. One is the High-Order SVD (HOSVD), and the other is the Canonical Decomposition (CanD). Only the latter is closely related to the tensor rank. Important basic questions are raised in this short paper, such as the maximal achievable rank of a tensor of given dimensions, or the computation of a ...
متن کاملOrthogonal Tensor Decompositions
We explore the orthogonal decomposition of tensors (also known as multidimensional arrays or n-way arrays) using two different definitions of orthogonality. We present numerous examples to illustrate the difficulties in understanding such decompositions. We conclude with a counterexample to a tensor extension of the Eckart-Young SVD approximation theorem by Leibovici and Sabatier [Linear Algebr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2017
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2017.08.1110