We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
This paper presents a two-stage compression method for accelerating GPU-based volume rendering of time-varying scalar data. Our method aims at reducing transfer time by compressin...
We develop techniques that make authenticated directories efficient and scalable toward the goal of managing tens of billions of objects in a single directory. Internet storage s...
Paul T. Stanton, Benjamin McKeown, Randal C. Burns...