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ICML
2008
IEEE
16 years 2 months ago
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
Ruslan Salakhutdinov, Andriy Mnih
ICASSP
2009
IEEE
15 years 8 months ago
A semi-supervised learning approach to online audio background detection
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
Selina Chu, Shrikanth S. Narayanan, C.-C. Jay Kuo
BMCBI
2010
127views more  BMCBI 2010»
15 years 2 months ago
Computational prediction of type III secreted proteins from gram-negative bacteria
Background: Type III secretion system (T3SS) is a specialized protein delivery system in gramnegative bacteria that injects proteins (called effectors) directly into the eukaryoti...
Yang Yang, Jiayuan Zhao, Robyn L. Morgan, Wenbo Ma...
NIPS
1996
15 years 3 months ago
Predicting Lifetimes in Dynamically Allocated Memory
Predictions oflifetimesofdynamicallyallocated objects can be used to improve time and space e ciency of dynamic memory management in computer programs. Barrett and Zorn 1993] used...
David A. Cohn, Satinder P. Singh
ICML
2007
IEEE
16 years 2 months ago
Learning to rank: from pairwise approach to listwise approach
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...