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ICML 2014 Workshop on Deep Learning Models for Emerging Big Data Applications (DLBD'2014)

Overview

The DLBD'2014 workshop is about the advancement of Deep Learning inside the realm of emerging Big Data applications. Deep Learning is a rapidly emerging technology in the fields of Machine Learning and Data Science. The concept of Deep Learning has been borrowed from Artificial Intelligence area, in particular from Neural Network technology. It shows promising results with solving many large, complex, and high-dimensional machine learning problems, including dimensionality reduction, feature selection, feature extraction, classification and clustering. To date, the deep learning models have been used in many fields, including computer vision, medical imaging, social networks, Neuroscience, signal processing, speech recognition, natural language processing, and chemistry. The deep learning research has been carried out independently in these disciplines hence a common ground is needed to help the experts explore unique deep learning solutions for multiple disciplines that are prone to Big Data problems. The goal of this workshop is to give such a common ground for dissemination and discussions of deep learning and big data analytic. 

Motivation

The motivation behind DLBD'2014 workshop is to attract a wider research community who are working in multiple disciplines including statistics, artificial intelligence, signal processing, computer science, medical science, data science and chemistry, and facilitate discussions to advance the deep learning models for Big Data by adopting modern statistical signal processing techniques. The forum will impact many application including computer vision, speech recognition, computer networks, medical imaging and social networks, which in general suffer from the nonexistence of sophisticated techniques to solve large, complex, and high dimensional data. We expect this workshop will bring three advantages: establishment of a new direction research ground, formation of small research groups to work on deep learning technology using statistical signal processing techniques, and the development of unique/common solutions to enhance deep learning models for Big Data applications using statistical signal processing algorithms. 

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