In this paper, we study the heterogeneous domain adaptation (HDA) problem, in which the
data from the source domain and the target domain are represented by heterogeneous …

Cross-domain learning methods have shown promising results by leveraging labeled patterns
from the auxiliary domain to learn a robust classifier for the target domain which has only …

We propose a visual event recognition framework for consumer videos by leveraging a large
amount of loosely labeled web videos (eg, from YouTube). Observing that consumer videos …

In this paper, we propose a new framework called domain adaptation machine (DAM) for
the multiple source domain adaption problem. Under this framework, we learn a robust …

Cucurbitacins are triterpenoids that confer a bitter taste in cucurbits such as cucumber, melon,
watermelon, squash, and pumpkin. These compounds discourage most pests on the plant …

We propose a new learning method for heterogeneous domain adaptation (HDA), in which
the data from the source domain and the target domain are represented by heterogeneous …

We propose a multiple source domain adaptation method, referred to as Domain Adaptation
Machine (DAM), to learn a robust decision function (referred to as target classifier) for label …

Cross-domain learning methods have shown promising results by leveraging labeled patterns
from auxiliary domains to learn a robust classifier for target domain, which has a limited …

Cross-domain object detection is challenging, because object detection model is often
vulnerable to data variance, especially to the considerable domain shift between two distinctive …

We first propose a new spatio-temporal context distribution feature of interest points for
human action recognition. Each action video is expressed as a set of relative XYT coordinates …