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Found 5 papers, 1 papers with code
Deep Symbolic Representation Learning for Heterogeneous Time-series Classification
In this paper, we consider the problem of event classification with multi-variate time series data consisting of heterogeneous (continuous and categorical) variables.
Comparative Study of Deep Learning Software Frameworks
The study is performed on several types of deep learning architectures and we evaluate the performance of the above frameworks when employed on a single machine for both (multi-threaded) CPU and GPU (Nvidia Titan X) settings.
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification
In this paper, we propose a supervised dictionary learning algorithm in the kernel domain for hyperspectral image classification.
Multimodal Task-Driven Dictionary Learning for Image Classification
Dictionary learning algorithms have been successfully used for both reconstructive and discriminative tasks, where an input signal is represented with a sparse linear combination of dictionary atoms.
Quality-based Multimodal Classification Using Tree-Structured Sparsity
An accelerated proximal algorithm is proposed to solve the optimization problem, which is an efficient tool for feature-level fusion among either homogeneous or heterogeneous sources of information.
