Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Understanding goals and preferences behind a user's online activities can greatly help information providers, such as search engine and E-Commerce web sites, to personalize c...
Honghua (Kathy) Dai, Lingzhi Zhao, Zaiqing Nie, Ji...
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
This paper describes performance tuning experiences with a three-dimensional unstructured grid Euler flow code from NASA, which we have reimplemented in the PETSc framework and p...
William Gropp, Dinesh K. Kaushik, David E. Keyes, ...
We present a system that can match and reconstruct 3D
scenes from extremely large collections of photographs such
as those found by searching for a given city (e.g., Rome) on
In...
Sameer Agarwal, Noah Snavely, Ian Simon, Steven M....