We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
We describe a hybrid algorithm that is designed to reconstruct a piecewise smooth surface mesh from noisy input. While denoising, our method simultaneously regularizes triangle me...
Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual fo...
We consider formulas which, in addition to the symbols in the vocabulary, may use two designated symbols ≺ and + that must be interpreted as a linear order and its associated ad...
Link prediction is an important task in social networks and data mining for understanding the mechanisms by which the social networks form and evolve. In most link prediction rese...