We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Statistical approaches for building non-rigid deformable
models, such as the Active Appearance Model (AAM), have
enjoyed great popularity in recent years, but typically require
...
Akshay Asthana (Australian National University), R...
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...
Shuicheng Yan, Dong Xu, Lei Zhang, Benyu Zhang, Ho...