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JMLR
2006
169views more  JMLR 2006»
15 years 4 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
168
Voted
BIBE
2008
IEEE
142views Bioinformatics» more  BIBE 2008»
15 years 11 months ago
Optimizing performance, cost, and sensitivity in pairwise sequence search on a cluster of PlayStations
— The Smith-Waterman algorithm is a dynamic programming method for determining optimal local alignments between nucleotide or protein sequences. However, it suffers from quadrati...
Ashwin M. Aji, Wu-chun Feng
BMCBI
2006
137views more  BMCBI 2006»
15 years 4 months ago
A maximum likelihood framework for protein design
Background: The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, thi...
Claudia L. Kleinman, Nicolas Rodrigue, Céci...
115
Voted
CHI
2002
ACM
16 years 5 months ago
Quantitative analysis of scrolling techniques
We propose a formal experimental paradigm designed to help evaluate scrolling interaction techniques. Such a method is needed by interaction designers to quantify scrolling perfor...
Ken Hinckley, Edward Cutrell, Steve Bathiche, Tim ...
CIKM
2009
Springer
15 years 11 months ago
Generating comparative summaries of contradictory opinions in text
This paper presents a study of a novel summarization problem called contrastive opinion summarization (COS). Given two sets of positively and negatively opinionated sentences whic...
Hyun Duk Kim, ChengXiang Zhai