In this paper, we present a novel algorithm for partial
intrinsic symmetry detection in 3D geometry. Unlike previous
work, our algorithm is based on a conceptually simple
and st...
Ruxandra Lasowski, Art Tevs, Hans-Peter Seidel, Mi...
This paper studies the inference of 3D shape from a set of ? noisy photos. We derive a probabilistic framework to specify what one can infer about 3D shape for arbitrarily-shaped, ...
Rahul Bhotika, David J. Fleet, Kiriakos N. Kutulak...
Scientific and intelligence applications have special data handling needs. In these settings, data does not fit the standard model of short coded records that had dominated the dat...
Recent work on distributed, in-network aggregation assumes a benign population of participants. Unfortunately, modern distributed systems are plagued by malicious participants. In...
Minos N. Garofalakis, Joseph M. Hellerstein, Petro...
We investigate the problem of learning to predict moves in the board game of Go from game records of expert players. In particular, we obtain a probability distribution over legal...