The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question: what are the most general conditions under...
Datacenter networks typically have many paths connecting each host pair to achieve high bisection bandwidth for arbitrary communication patterns. Fully utilizing the bisection ban...
—We present the boomerang protocol to efficiently retain information at a particular geographic location in a sparse network of highly mobile nodes without using infrastructure ...
Tingting Sun, Bin Zan, Yanyong Zhang, Marco Grutes...
When we look at a picture, our prior knowledge about the world allows us to resolve some of the ambiguities that are inherent to monocular vision, and thereby infer 3d information...
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...