This work focuses on several optimization problems involved in recovery of sparse solutions of linear inverse problems. Such problems appear in many fields including image and sig...
Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously. In this paper, we consider the problem of learning shared s...
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
Logistic Regression (LR) has been widely used in statistics for many years, and has received extensive study in machine learning community recently due to its close relations to S...
Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Ha...