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» Improved bounds on the sample complexity of learning
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AIRS
2009
Springer
14 years 13 hour ago
A Latent Dirichlet Framework for Relevance Modeling
Relevance-based language models operate by estimating the probabilities of observing words in documents relevant (or pseudo relevant) to a topic. However, these models assume that ...
Viet Ha-Thuc, Padmini Srinivasan
BMCBI
2010
122views more  BMCBI 2010»
13 years 5 months ago
Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data
Background: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduc...
Kai-Lin Tang, Tong-Hua Li, Wen-Wei Xiong, Kai Chen
SIAMMAX
2010
189views more  SIAMMAX 2010»
13 years 4 days ago
Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
Lei-Hong Zhang, Li-Zhi Liao, Michael K. Ng
STOC
2004
ACM
158views Algorithms» more  STOC 2004»
14 years 5 months ago
Collective asynchronous reading with polylogarithmic worst-case overhead
The Collect problem for an asynchronous shared-memory system has the objective for the processors to learn all values of a collection of shared registers, while minimizing the tot...
Bogdan S. Chlebus, Dariusz R. Kowalski, Alexander ...
PEPM
2009
ACM
14 years 2 months ago
Self-adjusting computation: (an overview)
Many applications need to respond to incremental modifications to data. Being incremental, such modification often require incremental modifications to the output, making it po...
Umut A. Acar