Category: Activities

This category contains small activities in discussed in BLOG like fashion.

Neural Network: implementing Lamstar

In this post i report a simple implementation of a Counter Propagation Neural Network.
As for the following examples i will post the goal is character recognition on a grid of pixels. 
Noise is introduce to evaluate robustness of the approach.

Here we will present both implementation and performance eval- 
uation of Lamstar neural network applied to characters recognition. 

 
This documentation provide full description of the approach and the results.
This is the source code for the neural network

Neural Network: implementing Counter Propagation

In this post i report a simple implementation of a Counter Propagation Neural Network.
As for the following examples i will post the goal is character recognition on a grid of pixels. 
Noise is introduce to evaluate robustness of the approach.

Here we will present both implementation and performance evalu- 
ation of an artificial neural network based on the Counter Propagation 
applied to characters recognition.

 
This documentation provide full description of the approach and the results.
This is the source code for the neural network

Neural Network: implementing Hopfield NN

In this post i report a simple implementation of a Hopfield Neural Network.
As for the following examples i will post the goal is character recognition on a grid of pixels. 
Noise is introduce to evaluate robustness of the approach.
  Here we will present both implementation and performance eval- 
uation of an artificial neural network, namely the Hopfield network 
applied to characters recognition.
 
This documentation provide full description of the approach and the results.
This is the source code for the neural network

Timeplot: an MIT tool to visualize series of events

Timeplot is a DHTML-based AJAXy widget for plotting time series and overlay time-based events over them (with the same data formats that Timeline supports). The original site is: http://simile.mit.edu/timeplot/ 

 I’ve installed it and make a couple of very simple tests, the installation is very simple and the XML-based language to feed the graphical interface very intuitive here is an example.

Here follows a simple example of XML input file:

<?xml version="1.0" encoding="UTF-8"?> 
<data>
<event start="Jan 01 1849 00:00:00 GMT" title="California Gold Rush" link="http://en.wikipedia.org/wiki/California_Gold_Rush"></event>
<event start="Apr 12 1861 00:00:00 GMT" end="Apr 09 1865 00:00:00 GMT" title="American Civil War" link="http://en.wikipedia.org/wiki/American_Civil_War"></event>
</data> 
 

Neural Network: implementing backpropagation

In this post i report a simple implementation of a Backpropagation Neural Network.
As for the following examples i will post the goal is character recognition on a grid of pixels. 
Noise is introduce to evaluate robustness of the approach.
  
Here we will present both implementation and performance eval- 
uation of a multilayer artificial neural network, exploiting backpropagation for characters recognition.
 
This documentation provide full description of the approach and the results.
This is the source code for the neural network

Neural Network: implementing Madaline

In this post i report a simple implementation of a Madaline Neural Network.
As for the following examples i will post the goal is character recognition on a grid of pixels. 
Noise is introduce to evaluate robustness of the approach.
  
Here we will present both implementation and performance eval- 
uation of a multilayer artificial neural network, based the Adaline 
neurons (Madaline) for characters recognition.
 
This documentation provide full description of the approach and the results.
This is the source code for the neural network

AI simple programs: MiniMax for game playing

Another interesting topic in AI is game playing, the MiniMax algorithm is been presented,
together with the optimized version known as Alpha-Beta pruning. Here i show an
implementation and result evaluation for both algorithm on a simplified version of the
well known Othello Game (also known as Reversi or Attaxx). 

 This documentation provide a complete description of the steps and  
here you can find the source code for the optimized version of the program. 

AI simple programs: heuristic search

Informed search algorithm are usefull when dealing with large state 
space, and when ”good” heuristics can be find for the problem. Here we 
present two simple an implementation of the well known algorithms: A*. 
To show this two simple game, the 8 puzzle game and the dating game has 
been used, in the previous we tested 4 different heuristics while the second 
has been used to compare simple depth first, A* and IDA*. 
 
 This documentation provide a complete description of the steps and  

here you can find the source code for the optimized version of the program. 

AI simple programs: searching

 
Searching algorithm are commonly exploited in the Artificial Intelligence field, 
here I present two simple implementations of the well known 
algorithms: depth first, breadth first and depth limited for tree search. To 
show this two simple game, the 8 puzzle game and a simple grid world 
has been used.
 
This documentation provide a complete description of the steps and  
here you can find the source code for the optimized version of the program. 
 

DrugSearch: Neural Network Information Retrieval

 

In this post is summarize the work i’ve done as Final Project for CS580 Neural Network in Chicago for Professor Graupe. This work has been later extended together with professor Clement Yu and published at CIKM 2005.  General purpose search engines have provided the users with simple way of querying massive sources of information efficiently, but for domain specific problems better solutions can be developed. We present an application of the Lamstar Neural Network for domain specific web searches. The problem itself is really general and is about relating different topics in a domain specific web search, we present here an instance of the problem relating drug names and side effects. The system, working on top of existing search engines, will filter the results to improve the quality of the search via a properly trained Lamstar neural network, providing a list of links to the suitable pages while directly showing the most relevant portion of each page to the user. 

 

Here is a presentation of the work: drugsearch.pdf