Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2018; 27th International C Věra K?rková,Yannis Manolopoulos,Ilias Maglogianni Confe

STANT

critique

,Relationale und differentielle Serialit?t,he proposed method is compared with reservoir computing methods with normal neurons and leaky integrator neurons by solving four kinds of regression and classification problems with time-series data. As a result, the proposed method shows superior results in all of problems.

古老

https://doi.org/10.1007/978-3-642-47931-1t we can learn compact encoders that, despite the relatively small number of parameters, reach high-level performances in downstream tasks, comparing them with related state-of-the-art approaches or with fully supervised methods.

Kaleidoscope

Practical Fractional-Order Neuron Dynamics for Reservoir Computinghe proposed method is compared with reservoir computing methods with normal neurons and leaky integrator neurons by solving four kinds of regression and classification problems with time-series data. As a result, the proposed method shows superior results in all of problems.

畏縮

An Unsupervised Character-Aware Neural Approach to Word and Context Representation Learningt we can learn compact encoders that, despite the relatively small number of parameters, reach high-level performances in downstream tasks, comparing them with related state-of-the-art approaches or with fully supervised methods.

Torrid

Verfassungsrechtliche Problemstellungn in that time step. Finally, the values of the survival function are linearly combined to compute the unique risk score. Thanks to the model structure and the training designed to exploit two loss functions, our model gets better concordance index (C-index) than the state of the art approaches.