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...
In this paper, we survey the current state-ofart models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron...
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
In this paper, we present a novel semisupervised regression algorithm working on multiclass data that may lie on multiple manifolds. Unlike conventional manifold regression algori...
Huan Wang, Shuicheng Yan, Thomas S. Huang, Jianzhu...