Feed-forward synthesis of textures and AWS AMI cloud deployment

  The long list of blogs I subscribe to seldom keeps me bored. This morning I didn't even remember well to have subscribed  ALGORITHMIA Blog, or whether I remembered their well qualified creators' skill set. But the Internet appears to be ever more intelligent, and with such a good timing of their  e-mail servers, that when … Continue reading Feed-forward synthesis of textures and AWS AMI cloud deployment

GRAM: Graph-based Attention Model. A better learning representation ?

The paper I review today will be a feature in next year  ICLR 2017: 5th International Conference on Learning Representations. It appears to be an important contribution to learning theory in the context of machine/deep learning systems and methods. The proper representation  of data is crucial to the successful implementation of deep learning systems, and increasingly … Continue reading GRAM: Graph-based Attention Model. A better learning representation ?

Image Classification with Sparse Neural Networks: a methodological new approach

  It is widely agreed in the deep neural networks community of researchers and the overall literature on the subject that sparse neural networks perform better than dense neural networks when it comes to image classification tasks. But this is a bit of s surprise, for me it was a recent revelation. Why is that … Continue reading Image Classification with Sparse Neural Networks: a methodological new approach

Long paper review of Attend, Infer, Repeat: Fast Scene Understanding with Generative Models

Upfront note:  this paper featured in the recent 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain. Today I will do a long paper review of one of those papers deserving it. The paper is about an algorithmic efficient inference in structured image models that explicitly reason about objects. The relatively long list of authors, … Continue reading Long paper review of Attend, Infer, Repeat: Fast Scene Understanding with Generative Models

Definition Series: Predictive Modeling

Continuing the definition series, today it is about an important topic: predictive modeling. Predictive modeling/analytics is a type of mathematical modeling used by a wide variety of organizations in order to predict outcomes of processes, events and pretty much everything that one cares about to know. It's based on a probabilistic and statistical kind of … Continue reading Definition Series: Predictive Modeling

Information Theory interpretation of Quantum probabilities

This blog is named The Information Age for a purpose. It is nothing to do with the common sense view of what is information. Instead it aims to provide insights about information in the way it is interpreted in scientific and technological contexts. In these contexts, information and information theory is normally associated with statistics, … Continue reading Information Theory interpretation of Quantum probabilities

Definition Series: Data center network topology with leaf-spine architecture

Today the information age is coming back to the definition series with tech target website WhatIs.com. This time with a post on the important and currently hot subject of data centers. Data centers had become a very important business topic, for obvious reasons. The current relevance of Big Data, Data engineering/management and related topics does … Continue reading Definition Series: Data center network topology with leaf-spine architecture

Short paper review: Towards Robot Self-consciousness (I): Brain-Inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-recognition

I will start a short paper review series here in The Information Age. I have got some difficulty in reviewing papers lately, something that needs further improvement regarding organizational issues. In my defense I would just say that I do not want to do this in a way that isn't proper and rigorous, with the … Continue reading Short paper review: Towards Robot Self-consciousness (I): Brain-Inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-recognition