Vector Quantization is useful for data compression. Competitive Learning which minimizes reconstruction error is an appropriate algorithm for vector quantization of unlabelled dat...
This paper proposes a method for reconstructing non-rigid 3D shapes from noisy 2D shapes. The proposed method estimates the 3D shape bases and projection matrices, exploiting low-r...
Abstract. We study the decision theory of a maximally risk-averse investor — one whose objective, in the face of stochastic uncertainties, is to minimize the probability of ever ...
Noam Berger, Nevin Kapur, Leonard J. Schulman, Vij...
Abstract. Majority of the search algorithms in microdata anonymization restrict themselves to a single privacy property and a single criteria to optimize. The solutions obtained ar...
According to Shannon Sampling Theory, Fourier interpolation is the optimal way to reach subpixel accuracy from a properly-sampled digital image. However, for most images this inte...
Gwendoline Blanchet, Lionel Moisan, Bernard Roug&e...