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» Randomized Optimum Models for Structured Prediction
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PAKDD
2005
ACM
180views Data Mining» more  PAKDD 2005»
13 years 11 months ago
Conditional Random Fields for Transmembrane Helix Prediction
Abstract. It is estimated that 20% of genes in the human genome encode for integral membrane proteins (IMPs) and some estimates are much higher. IMPs control a broad range of event...
Lior Lukov, Sanjay Chawla, W. Bret Church
NIPS
2004
13 years 7 months ago
Using Random Forests in the Structured Language Model
In this paper, we explore the use of Random Forests (RFs) in the structured language model (SLM), which uses rich syntactic information in predicting the next word based on words ...
Peng Xu, Frederick Jelinek
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 9 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICML
2005
IEEE
14 years 6 months ago
Predicting protein folds with structural repeats using a chain graph model
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
Yan Liu, Eric P. Xing, Jaime G. Carbonell
CP
2006
Springer
13 years 9 months ago
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...