All regular talks are 10 minutes + 5 Min Q&A. 

4 August (09.00-17.30)

09:00 - 09:05: Opening

09:05 - 09:50 Keynote 1:  AI models for solving combinatorial optimization problems, by Jinkyoo Park (Department of Industrial and Systems Engineering, KAIST, South Korea) 

09:50-10:35 Session 1 

• Neural Decision Diagrams for Job Shop Scheduling, by Eghonghon-aye Eigbe, Christoph Schmidl, Bart De Schutter, Nils Jansen, Mitra Nasri, Neil Yorke-Smith

• On the performance of Grad-Avg algorithm on Foundation NLP models, by Saugata Purkayastha, Sukannya Purkayastha

• Combining Local Symmetry Exploitation and Reinforcement Learning for Optimised Probabilistic Inference, by Sagad Hamid, Tanya Braun

10:35-11:05 Coffee Break

11:05-12:20 Session 2: 

• Energy Disaggregation Via Bayesian Non-negative Matrix Factorization with Sum-to-k Constraint, by Oumayma Dalhoumi, Manar Amayri, Nizar Bouguila

• SOSAE: Self-Organizing Sparse Autoencoders, by Sarthak Ketanbhai Modi, Zi Pong Lim, Yushi Cao, Yupeng Cheng, Teo Yon Shin, Shang-Wei Lin

• PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting, by Zeying Gong, Yujin Tang, Junwei Liang

• Flat Posterior For Bayesian Model Averaging, by SungJun Lim, Jeyoon Yeom, Sooyon Kim, Hoyoon Byun, Jinho Kang, Jiyoung Jung, Kyungwoo Song

• Sufficient Invariant Learning for Distribution Shift, by Taero Kim, SungJun Lim, Kyungwoo Song

12:30 - 14:00 Lunch

14:00 - 14:45 Keynote 2:  Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization, by Zhenkun Wang (Southern University of Science and Technology, China) 

14:45 - 15:30 Session 3: 

• Algorithm Selection for Robust Automated Machine Learning, by Yinuo Guo, Mustafa Misir

• On Size and Hardness Generalization in Unsupervised Learning for the Travelling Salesman Problem, by Yimeng Min, Carla P Gomes

• Foamy: a fast algorithm for a probabilistic crack growth model, by Alkis Papanastassiou, Piergiulio Lenzi, Valentina Gori

15:30 - 16:00 Coffee Break

16:00 - 16:45 Keynote 3:  Machine Learning-Based Hybrid Approaches for Combinatorial Optimization, by Yan Jin (Huazhong University of Science and Technology, China) 

16:45 - 17:15 Panel Discussions: Future of AI in the role of optimization