Papers

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Week 1

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1. Introduction and Overview
   (Arindam Banerjee)
   
   
2. Online Algorithms in Machine Learning
   Avrim Blum
   (Arindam Banerjee)
   
   

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   Week 2

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3. Game Theory, On-line Prediction and Boosting
   Yoav Freund and Rob Schapire
   (Arindam Banerjee)
   
   
4. Regret in Online Decision Problems
   Dean Foster and Rakesh Vohra
   (Arindam Banerjee)
   
   

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   Week 3

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5. Online Portfolio Selection using Multiplicative Updates
   David Helmbold, Rob Schapire, Yoram Singer and Manfred Warmuth
   
   
6. A Decision-Theoretic Generalization of Online Learning and an Application to Boosting
   Yoav Freund and Robert E. Schapire
   
   

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   Week 5

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7. Exponentiated Gradient versus Gradient Descent for Linear Predictors
   Jyrki Kivinen and Manfred Warmuth
   
   
8. Relative Loss Bounds for Multidimensional Regression Problems
   Jyrki Kivinen and Manfred Warmuth
   
   

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   Week 6

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9. Convex Optimization and Bregman Divergences
   (Arindam Banerjee)
   
   
10. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
    John Lafferty, Andrew McCallum, Fernando Pereira
    
    

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    Week 7

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11. Logistic Regression, AdaBoost and Bregman distances
    Michael Collins, Rob Schapire and Yoram Singer
    
    
12. The Information Bottleneck Method
    Naftali Tishby, Fernando Pereira, and William Bialek
    
    

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    Week 8

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13. Clustering with Bregman Divergences
    Arindam Banerjee, Srujana Merugu, Inderjit Dhillon and Joydeep Ghosh
    
    
14. Large Margin Methods
    (Arindam Banerjee)
    
    

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    Week 9

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15. Large margin classification using the perceptron algorithm
    Yoav Freund and Robert E. Schapire
    
    
16. Exponentiated gradient algorithms for large-margin structured classification
    Peter Bartlett, Michael Collins, Ben Taskar, and David McAllester
    
    

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    Week 10

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17. Learning Structured Prediction Models: A Large Margin Approach
    Ben Taskar, Vassil Chatalbashev, Daphne Koller and Carlos Guestrin
    
    
18. An Empirical Comparison of Supervised Learning Algorithms Using Different Performance Metrics
    Rich Caruana and Alexandru Niculescu-Mizil
    
    

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    Week 11

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19. A Simple Adaptive Procedure Leading to Correlated Equilibrium
    Sergiu Hart and Andreu Mas-Colell
    
    
20. Correlated Equilibria in Graphical Games
    Sham Kakade, Michael Kearns, John Langford and Luis Ortiz
    
    

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    Week 12

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21. From External to Internal Regret
    Avrim Blum and Yishay Mansour
    
    
22. Economic Properties of Social Networks
    Sham Kakade, Michael Kearns, Luis Ortiz, Robin Permantle and Siddharth Suri
    
    

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    Week 13

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23. The Link Prediction Problem for Social Networks
    David Liben-Nowell and Jon Kleinberg