Statistical Relational Learning Reading Group
Friday 12:00 ~ 1:00 PM, at BY365

I will use "Introduction to Statistical Relational Learning" by Lise Getoor and Ben Taskar as the text book. Though, we will not exactly follow the book.

 

Tentative Schedule for Spring 08
(please feel free to ask for addition of any chapters not listed in this schedule. even the topics not included in the book are welcome)

We will meet on Fridays. 12:00 to 1:00 PM at BY365

 

Week Topic Related Materials Presenter Interests
1
01/18		 Introduction for Inductive Logic Programming and Overview of the Reading Group FOIL, Muggleton's papers Sungwook AI
2
01/25		 Introduction for Conditional Random Field Chapter 4, paper Bob Bio
3
02/01		 Graphical Models for Probabilistic Inference Chapter 2 Sukru &
Mike		  
4
02/08		 Probabilistic Relational Models Chapter 5, Learning PRM, SPOOK Yu-Ru DB,Bio
5
02/15		 PRM, continue Chapter 5 and some of the papers from Koller e.g., pclassic
or Learning Probabilistic Models for Relational Structures		 Raju DB
6
02/22		 Lifted First Order Probabilistic Inference

Poole
Braz Amir and Roth

 Kartik AI
7
02/29		 Features Features Features .. 1 Learning with Feature Description Language Ina DB,Bio
8
03/07		 Features Features Features .. 2 kFOIL: Learning Simple Relational Kernels Luis DB,Bio
9
03/21		 Bayesian Logic Programming Chapter 10 Mike DB,Bio
10
03/28		 Stochastic Logic Programs Chapter 11 Tuan DB,Bio
11
04/04		 Markov Logic Network Chapter 12 and MLN Garrett DB
12
04/11		 Markov Logic Network Continue Learning the Structure of Markov Logic Networks,
Efficient Weight Learning for Markov Logic Networks,
 Markov Logic in Infinite Domains		 Aravind DB
13
04/18		 Probabilistic Prolog Problog and PEBL   DB,Bio
14
04/25		 IBAL Chapter 14    
15
05/02		        

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