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KDD
2004
ACM
154views Data Mining» more  KDD 2004»
14 years 8 months ago
Diagnosing extrapolation: tree-based density estimation
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Giles Hooker
BMCBI
2005
150views more  BMCBI 2005»
13 years 7 months ago
Discover protein sequence signatures from protein-protein interaction data
Background: The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-prot...
Jianwen Fang, Ryan J. Haasl, Yinghua Dong, Gerald ...
BMCBI
2007
207views more  BMCBI 2007»
13 years 7 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
ICFP
2001
ACM
14 years 7 months ago
Macros as Multi-Stage Computations: Type-Safe, Generative, Binding Macros in MacroML
With few exceptions, macros have traditionally been viewed as operations on syntax trees or even on plain strings. This view makes macros seem ad hoc, and is at odds with two desi...
Steven E. Ganz, Amr Sabry, Walid Taha
UAI
2004
13 years 8 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani