In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from th...
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
Relational data appear frequently in many machine learning applications. Relational data consist of the pairwise relations (similarities or dissimilarities) between each pair of i...
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip...