Face Recognition has rapidly grown as a commercial requirement for a variety of
applications in recent years. There are certain situations in which all the face images may …

In graph embedding based methods, we usually need to manually choose the nearest
neighbors and then compute the edge weights using the nearest neighbors via L2 norm (eg …

Due to the serious information overload problem on the Internet, recommender systems
have emerged as an important tool for recommending more useful information to users by …

Many information processing problems can be transformed into some form of eigenvalue or
singular value problems. Eigenvalue decomposition (EVD) and singular value …

Bimodal biometrics has been found to outperform single biometrics and are usually
implemented using the matching score level or decision level fusion, though this fusion will …

In this paper, a novel incremental learning algorithm is presented for reinforcement learning
(RL) in dynamic environments, where the rewards of state-action pairs may change over …

We propose a pose-robust face recognition method to handle the challenging task of face
recognition in the presence of large pose difference between gallery and probe faces. The …

Principal component analysis (PCA) algorithm has been extensively employed in face
recognition. However, existing PCA algorithms have some limitations in face recognition. In …

As one of the most important forms of psychological behaviors, micro-expression can reveal
the real emotion. However, the existing labeled training samples are limited to train a high …

For handling data and training model, existing machine learning methods do not take
timeliness problem into consideration. Timeliness here means the data distribution or the …