Computational analyses of protein structure-function relationships have traditionally been based on sequence homology, fold family analysis and 3D motifs/templates. Previous struct...
Reetal Pai, James C. Sacchettini, Thomas R. Ioerge...
Empirical evidence shows that in favorable situations semi-supervised learning (SSL) algorithms can capitalize on the abundance of unlabeled training data to improve the performan...
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
— The problem of concurrent thermal and vibration loading has not been thoroughly studied even though it is common in electronic packaging applications. Here we attempt to addres...
Cemal Basaran, Juan Gomez, Minghui Lin, Shidong Li