Late-breaking Abstracts

Organizer: Masaharu Munetomo (Hokkaido University)
Time: Monday, July 16, 14:00-17:40 (Session 1: 14:00-15:40, Session 2: 16:00-17:40)
Location: Training Room 2 (2F)

Instructions: Late-Breaking Abstract session will be organized in the poster format. The poster sizes are 90 cm (width) x 120 cm (height). The ISO paper size A0 (closely) fits this maximum size. Please print the poster by yourself and present it at the LBA session on Monday, July 16th. Poster boards and tape will be available. Please come about 15 minutes in advance of your assigned session (Session 1 or Session 2) to put up your poster. At the beginning of each session, you may introduce your paper in two minutes with slides. Please send your slides (PDF or PPT, max. 4 slides) by e-mail to LBA chair Masaharu Munetomo (munetomo@iic.hokudai.ac.jp) until July 14th. (You do not need to bring your PC for the presentation.)

Session 1 (14:00-15:40)

  1. Accelerating Genetic Programming using PyCuda
    Keiko Ono, Yoshiko Hanada
  2. Forecasting Soybean Futures Price Using Dynamic Model Averaging and Particle Swarm Optimization
    Tao Xiong
  3. A Self-Replication Basis For Designing Complex Agents
    Thommen Karimpanal George
  4. Genetically-Trained Deep Neural Networks
    Krzysztof Pawełczyk, Michal Kawulok, Jakub Nalepa
  5. The Human-based Evolutionary Computation System Enabling Us to Follow the Solution Evolution
    Kousuke Fujimoto, Kei Ohnishi, Tomohiro Yoshikawa
  6. Configuring the Parameters of Artificial Neural Networks using NeuroEvolution and Automatic Algorithm Configuration
    Evgenia Papavasileiou, Bart Jansen
  7. Optimization Based Adaptive Tagged Visual Cryptography
    Pei-Ling Chiu, Kai-Hui Lee
  8. A Geometric Evolutionary Search for Melody Composition
    Yong-Wook Nam, Yong-Hyuk Kim
  9. Distributed NSGA-II Sharing Extreme Non-dominated Solutions
    Yuji Sato, Mikiko Sato, Minami Miyakawa
  10. Parameter Space Analysis of Genetic Algorithm Using Support Vector Regression
    Hwi-Yeon Cho, Hye-Jin Kim, Yong-Hyuk Kim
  11. Evolutionary Algorithm Using Surrogate Assisted Model for Simultaneous Design Optimization Benchmark Problem of Multiple Car Structures
    Hiro Ohtsuka, Misaki Kaidan, Tomohiro Harada, Ruck Thawonmas
  12. On the Hardness of Parameter Optimization of Convolution Neural Networks Using Genetic Algorithm and Machine Learning
    Hyeon-Chang Lee, Dong-Pil Yu, Yong-Hyuk Kim

Session 2 (16:00-17:40)

  1. Infeasible Solution Repair and MOEA/D Sharing Weight Vectors for Solving Multi-objective Set Packing Problems
    Mariko Tanaka, Yuki Yamagishi, Hidetoshi Nagai, Hiroyuki Sato
  2. Is It Worth to Approximate Fitness by Machine Learning?: Investigation on the Extensibility According to Problem Size
    Dong-Pil Yu, Yong-Hyuk Kim
  3. Importance of Finding a Good Basis in Binary Representation
    Junghwan Lee, Yong-Hyuk Kim
  4. Hybrid Swarm of Particle Swarm with Firefly for Complex Function Optimization
    Heng Xiao, Toshiharu Hatanaka
  5. Deterministic and Stochastic Precipitation Downscaling using Multi-Objective Genetic Programming
    Tanja Zerenner, Victor Venema, Petra Friederichs, Clemens Simmer
  6. EBIC: a Next-Generation Evolutionary-Based Parallel Biclustering Method
    Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang, Jason H. Moore
  7. Digital Investigations on the Evolution of Prokaryote Photosynthesis Regulation
    Anselmo Pontes, Charles Ofria
  8. Syllabification by Phone Categorization
    Jacob Krantz, Maxwell Dulin, Paul De Palma, Mark VanDam
  9. Evolving Modular Neural Sequence Architectures with Genetic Programming
    David Dohan, David So, Quoc Le
  10. Investigation of Kernel Functions in EDA-GK
    Ryoichi Hasegawa, Hisashi Handa
  11. GA and Entropy Objective Function for Solving Sudoku Puzzle
    Katya Rodriguez-Vazquez
  12. A Surrogate-assisted Selection Scheme for Genetic Algorithms Employing Multi-layer Neural Networks
    Masaki Fujiwara, Masaharu Munetomo