Workshops

Advancements in Neural Architecture Search: Techniques and Application

Traditionally, NAS algorithms are grouped into three main categories based on their search methodologies:

1. 1. Reinforcement Learning
   2. Gradient-based Techniques
   3. Evolutionary Computation

Yet, the landscape of NAS is continually evolving. Modern NAS innovations often defy these clear-cut classifications. Some algorithms exhibit characteristics spanning multiple categories, while others introduce groundbreaking architectural encodings that challenge conventional search methods.

The dynamism of this field is undeniable. Contemporary NAS techniques are pushing boundaries by enabling the design of complex Deep Neural Networks within stringent time constraints. This progress is driven by:

• • Streamlined Search Spaces: Efficiently defined to focus on optimal solutions.
  • GPU Optimisation: Leveraging the power of GPUs for accelerated computations.
  • Approximation Techniques: Using intelligent approximating functions to enhance performance.

Notably, while some NAS approaches excel in specific domains, others produce adaptable architectures, empowering users to effortlessly transition between diverse applications.

This workshop aims to delve into the contemporary trends of NAS, explore its successes and challenges, and contemplate its future directions and broader impact within the AI community, industry, and society.

Date: 25 June, 2025
Time: 10:30 am – 12:30 pm
Venue: Lotus Junior 4D

Website: ANASTA

Organisers
Zexuan Zhu (Shenzhen University, China)
Liang Feng (Chongqing University, China)
Yaqing Hou (Dalian University of Technology, China)
Ran Cheng (Southern University of Science and Technology, China)
Zhihui Zhan (South China University of Technology, China)

Advances in Computational Intelligence and Machine Learning: Applications and Innovations

Overview
Computational Intelligence and Machine Learning have emerged as the driving forces behind advancements in the field of information technology. Rapid progress in related domains not only offers fresh perspectives for scientific enquiry but also exerts profound impacts across a myriad of practical applications. This workshop “Advances in Computational Intelligence and Machine Learning: Applications and Innovations” aims to explore the latest developments in Computational Intelligence and Machine Learning, showcasing their practical applications and innovations across various domains.
This workshop will encompass the following aspects:

• • Theory and Methods: We will delve into the latest theories and methods within the realms of Computational Intelligence and Machine Learning. This includes, but is not limited to, Deep Learning, Reinforcement Learning, Evolutionary Algorithms, Fuzzy Logic, Genetic Algorithms, and more. Discussions will revolve around the principles, advantages, and applications of these methodologies across diverse problem domains.
  • Practical Applications: Emphasis will be placed on the application of Computational Intelligence and Machine Learning in real-world scenarios. This encompasses Natural Language Processing, Computer Vision, Medical Diagnostics, and Financial Forecasting, among other fields. We will explore how these applications are reshaping our lives and work processes, as well as discuss their potential impacts and challenges.
  • Innovation and Future Trends: Discussions will center around the innovations and future trends in Computational Intelligence and Machine Learning. This includes emerging algorithms, novel application domains, and new research directions. We will explore how these innovations drive technological advancements and societal developments, while also deliberating on potential future directions and challenges.

Through this workshop, we aim to provide a platform for participants to exchange ideas and learn from one another, fostering collaboration and innovation within the realms of Computational Intelligence and Machine Learning. By facilitating dialogue and knowledge-sharing, we seek to propel advancements in these fields, addressing the increasingly complex and diverse technological and societal challenges of our time.

Date: 27 June, 2025
Time: 3:30 pm – 6:00 pm
Venue: Melati Ballroom 4101AB-4102

Website: ACIML

Organisers
Huanhuan Chen (School of Computer Science and Technology, University of Science and Technology of China, China)
Shan He (School of Computer Science, University of Birmingham, UK)
Bing Xue (School of Engineering and Computer Science, Victoria University of Wellington, New Zealand)