Knowledge Discovery from Data (TKDD)


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ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 8 Issue 3, June 2014

Robust Manifold Nonnegative Matrix Factorization
Jin Huang, Feiping Nie, Heng Huang, Chris Ding
Article No.: 11
DOI: 10.1145/2601434

Nonnegative Matrix Factorization (NMF) has been one of the most widely used clustering techniques for exploratory data analysis. However, since each data point enters the objective function with squared residue error, a few outliers with large...

A Regularization Approach to Learning Task Relationships in Multitask Learning
Yu Zhang, Dit-Yan Yeung
Article No.: 12
DOI: 10.1145/2538028

Multitask learning is a learning paradigm that seeks to improve the generalization performance of a learning task with the help of some other related tasks. In this article, we propose a regularization approach to learning the relationships...

On the Sample Complexity of Random Fourier Features for Online Learning: How Many Random Fourier Features Do We Need?
Ming Lin, Shifeng Weng, Changshui Zhang
Article No.: 13
DOI: 10.1145/2611378

We study the sample complexity of random Fourier features for online kernel learning—that is, the number of random Fourier features required to achieve good generalization performance. We show that when the loss function is strongly convex...

Predicting and Identifying Missing Node Information in Social Networks
Ron Eyal, Avi Rosenfeld, Sigal Sina, Sarit Kraus
Article No.: 14
DOI: 10.1145/2536775

In recent years, social networks have surged in popularity. One key aspect of social network research is identifying important missing information that is not explicitly represented in the network, or is not visible to all. To date, this line of...

Efficient Discovery of the Most Interesting Associations
Geoffrey I. Webb, Jilles Vreeken
Article No.: 15
DOI: 10.1145/2601433

Self-sufficient itemsets have been proposed as an effective approach to summarizing the key associations in data. However, their computation appears highly demanding, as assessing whether an itemset is self-sufficient requires consideration of all...

Optimizing Data Misuse Detection
Asaf Shabtai, Maya Bercovitch, Lior Rokach, Yuval Elovici
Article No.: 16
DOI: 10.1145/2611520

Data misuse may be performed by entities such as an organization's employees and business partners who are granted access to sensitive information and misuse their privileges. We assume that users can be either trusted or untrusted. The access of...