resources

AdSafe's strategy, methodology and technology are directly influenced by leading academicians, researchers and industry thought leaders. The business and academic literature relevant to the work of AdSafe is broad, from data science theory to brand strategy. The following articles, some written by AdSafe team members, offer a theoretical grounding in the concepts and ideas being employed by AdSafe.

Beyond the Gray Areas White Paper
April, 2010

Active Sampling for Class Probability
Maytal Saar-Tsechansky and Foster Provost
Sept. 18, 2002

An Expected Utility Approach - 2005
Foster Provost, Prem Melville, Maytal Saar-Tsechansky, Raymond Mooney
August, 2005

Audience Selection for Online Brand Advertising
Foster Provost, Brian Dalessandro, Rod Hook, Xiaohan Zhang, Alan Murray

Classification in Networked Data - 2007
Sofus A. Macskassy, Foster Provost
May, 2007

Enhanced hypertext categorization using hyperlinks
Souman Chakrabarti, Byron Don, Piotr Indyk

Get Another Label - 2008
Victor S. Sheng, Foster Provost, Panagiotis G. Ipeirotis
2005

Inductive Learning Algorithms
Susan Dumais, John Platt, David Heckerman, Mehran Sahami

Learning with Imbalanced Data
Foster Provost

Learning and Interference in Massive Social Networks - 2007
Shawndra Hill, Foster Provost, Chris Volinsky
2007

Modeling Complex Networks for Commerce - 2007
Foster Provost, Arun Sundararajan
June 12, 2007

Network-Based Marketing - 2006
Shawndra Hill, Foster Provost and Chris Volinsky
2006

Sextuple Indexing for Semantic Web Based Data Mang.
Cathrin Weiss, Panagiotis Karras, Abraham Bernstein