In this paper, we study the problem of recovering a low-rank matrix (the principal components) from a highdimensional data matrix despite both small entry-wise noise and gross spar...
Zihan Zhou, Xiaodong Li, John Wright, Emmanuel J. ...
In cross-modal inference, we estimate complete fields from noisy and missing observations of one sensory modality using structure found in another sensory modality. This inference...
S. Ravela, Antonio B. Torralba, William T. Freeman
This paper deals with generalized procrustes analysis. This is the problem of registering a set of shape data by estimating a reference shape and a set of rigid transformations gi...
We propose the use of random projections with a sparse matrix to maintain a sketch of a collection of high-dimensional data-streams that are updated asynchronously. This sketch al...
Aditya Krishna Menon, Gia Vinh Anh Pham, Sanjay Ch...
"Learning with side-information" is attracting more and more attention in machine learning problems. In this paper, we propose a general iterative framework for relevant...