As a promising area in machine learning, multi-task learning (MTL) aims to improve the
performance of multiple related learning tasks by leveraging useful information among them …

Abstract Multi-task learning (MTL), which optimizes multiple related learning tasks at the
same time, has been widely used in various applications, including natural language …

Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to
leverage useful information contained in multiple related tasks to help improve the …

Multi-task learning in Convolutional Networks has displayed remarkable success in the field
of recognition. This success can be largely attributed to learning shared representations …

Lifelong Machine Learning, Second Edition is an introduction to an advanced machine
learning paradigm that continuously learns by accumulating past knowledge that it then …

Accurate classification of Alzheimer's disease (AD) and mild cognitive impairment (MCI),
especially distinguishing the progressive MCI (pMCI) from stable MCI (sMCI), will be helpful …

This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint
human action grou** and recognition. Specifically, we formulate the objective function into …

In this paper, we study the challenging problem of categorizing videos according to high-
level semantics such as the existence of a particular human action or a complex event …

We provide novel theoretical results regarding local optima of regularized M-estimators,
allowing for nonconvexity in both loss and penalty functions. Under restricted strong …

In the paradigm of multi-task learning, mul-tiple related prediction tasks are learned jointly,
sharing information across the tasks. We propose a framework for multi-task learn-ing that …