With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
Most Gene Regulatory Network (GRN) studies ignore the impact of the noisy nature of gene expression data despite its significant influence upon inferred results. This paper present...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
In this paper, we focus on the use of context-aware, collaborative filtering, machine-learning techniques that leverage automatically sensed and inferred contextual metadata toget...
Marc Davis, Michael Smith, John F. Canny, Nathan G...
Robustness analysis research has shown that conventional memory-based recommender systems are very susceptible to malicious profile-injection attacks. A number of attack models h...
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...