Cerca risorse accademiche

Las redes neuronales convolucionales (CNN) tienen gran potencial en resolver problemas de clasificación con imágenes. La presente investigación tiene como objetivo presentar modelos reducidos que permita identificar c...

Materie / parole chiave: Refrigeration and refrigerating machinery; Automatic control; Energy conservation; Mathematical models; Artificial intelligence; Industrial applications; Food industry; Technological innovations

Materie / parole chiave: Machine learning; Artificial intelligence; Electronic books

Materie / parole chiave: Neural networks (Computer science); Artificial intelligence; Information networks; Machine learning

Materie / parole chiave: Artificial intelligence; Machine learning; Bioinformatics; Biotechnology; Pharmacology

Materie / parole chiave: Computer science; Technological innovations; Machine learning; Artificial intelligence

Materie / parole chiave: TensorFlow; Machine learning; Artificial intelligence

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing n...

Materie / parole chiave: Black box; Harm; Computer science; Key (lock); Criminal justice; Artificial intelligence; Economic Justice; Machine learning; Data science; Criminology; Psychology; Computer security

Defeasible Logic Programming (DeLP) is a knowledge representation and reasoning formalism that by combining Logic Programming with Defeasible Argumentation is able to represent incomplete and potentially contradictory in...

Parallel machine scheduling, involves the allocation of jobs to the system resources (a bank of machines in parallel). A basic model consisting of m machines and n jobs is the foundation of more complex models. Here, job...

The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML applications have been developed, such as da...

Tardiness related objectives are of utmost importance in production systems when client satisfaction is a main goal of a company. These objectives measure the system response to the client requirements and rate manager´...

This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-worl...

As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on o...

An attentional mechanism has lately been used to improve neural machine translation (NMT) by selectively focusing on parts of the source sentence during translation. However, there has been little work exploring useful a...

Due to the simplicity of their implementations, least square support vector machine (LS-SVM) and proximal support vector machine (PSVM) have been widely used in binary classification applications. The conventional LS-SVM...

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.

Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks.The neural machine translation models often consist of an encoder and a decoder.The encoder extra...

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing mach...

My first exposure to Support Vector Machines came this spring when heard Sue Dumais present impressive results on text categorization using this analysis technique. This issue's collection of essays should help familiari...

TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. Tensor-Flow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. ...

Materie / parole chiave: Computer science; Overfitting; Ensemble learning; Boosting (machine learning); AdaBoost; Artificial intelligence; Machine learning; Classifier (UML); Bayesian probability; Pattern recognition (psychology); Artificial neu...

Materie / parole chiave: Extreme learning machine; Computer science; Bottleneck; Generalization; Feedforward neural network; Artificial neural network; Benchmark (surveying); Feed forward; Artificial intelligence; Key (lock); Machine learning; A...