Kernel machines (e.g. SVM, KLDA) have shown state-ofthe-art performance in several visual classification tasks. The classification performance of kernel machines greatly depends o...
Recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. The individual predictors (weak learners) can be very simple, ...
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Leakage power is becoming a dominant contributor to the total power consumption and dual-Vth assignment is an efficient technique to decrease leakage power, for which effective de...
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...