IJCNN 2017 Special Session: Probabilistic Models and Kernel Methods
Organized by Shiliang Sun, Shifei Ding, Huawen Liu, Wenjian Wang,
Xiaowei Yang, Li Zhang, and Jing Zhao
Probabilistic models and kernel methods are two of the core techniques in pattern recognition and machine learning. During the past two decades, many successful applications based on them have been developed. Probabilistic models are known as a solid framework to model uncertainty and dependency, while kernel methods provide a powerful approach to modeling nonlinear relationship through the use of linear methods and the kernel trick. These two types of techniques are closely related and some methods can be understood from both sides. Building good and scalable models and giving effective and efficient inference methods are important concerns for research on probabilistic models; creatively applying kernel methods to solve problems such as those in multi-view learning, transfer learning, and semi-supervised learning is also an active research field.
This special session, following the success in the last year, intends to provide a platform for researchers to discuss and report related progresses.
Scope and Topics
The special session covers theory, models, algorithms and applications for probabilistic models and kernel methods. Typical call-for-paper topics include the following (but not limited to):
- Gaussian processes
- Hidden Markov models
- Conditional random fields
- Topic models
- Maximum entropy discrimination
- Support vector machines and twin support vector machines
- Statistical learning theory
- Multi-view learning
- Multi-task learning and transfer learning
- Semi-supervised learning and active learning
- Large-scale machine learning and optimization
- Papers submitted for special sessions are to be peer-reviewed with the same criteria used for the regular sessions.
- Authors should make sure that papers submitted to the special session clearly indicate the name of the special session the papers belong to.
Special Session Chairs (Organizers)
Shiliang Sun, Professor, East China Normal University
Shifei Ding, Professor, China University of Mining and Technology
Huawen Liu, Associate Professor, Zhejiang Normal University
Wenjian Wang, Professor, Shanxi University
Xiaowei Yang, Professor, South China University of Technology
Li Zhang, Professor, Soochow University
Jing Zhao, Assistant Professor, East China Normal University
Last Update: October 5, 2016