We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
In this paper, we develop a new effective multiple kernel learning algorithm. First, we map the input data into m different feature spaces by m empirical kernels, where each genera...
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...
Multiple observation improves the performance of 3D object classification. However, since the distribution of feature vectors obtained from multiple view points have strong nonlin...
The existing Multi-View Learning (MVL) is to discuss how to learn from patterns with multiple information sources and has been proven its superior generalization to the usual Sing...