8:45-9:00 Welcome

9:00-09:50 Session 1

09:50-10:30 Coffee break

10:30-12:10 Session 2

12:10-13:30 Lunch break

13:30-14:30 Invited talk

14:30-15:30 Session 3

15:30-16:00 Coffee break

16:00-17:00 Session 4

17:00-17:40 Session 5

17:40-18:30 Drinks

Detailed program

Session 1: ML for solving optimization problems 1

9:00-9:20 Lucas Kletzander, Nysret Musliu and Kate Smith-Miles, Instance Space Analysis for a Personnel Scheduling Problem (download: paper, presentation)

9:20-9:40 Roland Yap, Optimization, Big Data and Scalability - A Position Paper

9:40-9:50 Lars Kotthoff, Vivek Jain, Alexander Tyrrell, Hud Wahab and Patrick Johnson, AI for Materials Science: Tuning Laser-Induced Graphene Production

Coffee break (09:50-10:30)

Session 2: Algorithm tuning, selection, and portfolios

10:30-10:50 André Biedenkapp, Hüseyin Furkan Bozkurt, Frank Hutter and Marius Lindauer, Towards White-box Benchmarks for Algorithm Control

10:50-11:10 Daniël Fokkinga, Anna Louise Latour, Marie Anastacio, Siegfried Nijssen and Holger Hoos, Programming a Stochastic Constraint Optimisation Algorithm, by Optimisation (download: paper, presentation)

11:10-11:30 Yair Nof and Ofer Strichman, Optimal algorithm portfolios for computationally hard real-time problems

11:30-11:50 Bishwamittra Ghosh, Dmitry Malioutov and Kuldeep S. Meel, Interpretable Classification Rules in Relaxed Logical Form (download: paper, presentation)

11:50-12:00 Marie Anastacio, Chuan Luo and Holger Hoos, Exploitation of Default Parameter Values in Automated Algorithm Configuration (download: paper, presentation)

12:00-12:10 Marius Lindauer, Matthias Feurer, Katharina Eggensperger, André Biedenkapp and Frank Hutter, Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters (download: paper, presentation)

Lunch break (12:10-13:30)

Invited talk (13:30-14:30) Prof. dr. Holger Hoos (Leiden University, NL), Cooperative competition: A new way of solving challenging problems in AI and beyond

Session 3: ML for solving optimization problems 2

14:30-14:50 Marijn van Knippenberg, Mike Holenderski and Vlado Menkovski, Complex Vehicle Routing with Memory Augmented Neural Networks

14:50-15:00 Chao Li, Pieter Smet and Patrick De Causmaecker, Polynomially solvable models for data-driven personnel scheduling

15:00-15:10 Emir Demirović, James Bailey, Jeffrey Chan, Tias Guns, Ramamohanarao Kotagiri, Christopher Leckie and Peter J. Stuckey, Learning Input Parameters to Combinatorial Optimisation Problems Based on Historical Data

15:10-15:20 Abhisek Mukhopadhyay, Sneha Singhania, Shubhashis Sengupta and Andrew Fano, Decision Support System for Playlist Management and Curation

coffee break (15:20-16:00)

Session 4: Methods from AI meeting optimization

16:00-16:20 Qing Chuan Ye, Jason Rhuggenaath, Yingqian Zhang, Sicco Verwer and Michiel Hilgeman, Data driven design for online industrial auctions (download: paper, presentation)

16:20-16:40 Laurens Bliek, Sicco Verwer and Mathijs de Weerdt, Black-box Combinatorial Optimization with Costly and Noisy Evaluations using Models with Integer-valued Minima

16:40-16:50 Ricardo Faia, Tiago Pinto, Tiago Sousa, Zita Vale and Juan Corchado, Case-based reasoning for dynamic application of optimization algorithms

16:50-17:00 Steven Prestwich, David Browne, Eugene Freuder and Barry O'Sullivan, Constraint Acquisition Via Classification

Session 5: Optimization techniques for ML

17:00-17:10 Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu and Jiacheng Zhuo, Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization

17:10-17:30 Marco Grassia, Juho Lauri, Sourav Dutta and Deepak Ajwani, Learning Multi-Stage Sparsification for Maximum Clique Enumeration

17:30-17:40 Jesus De Loera, Jamie Haddock, Anna Ma and Deanna Needell, Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing

17:40-17:50 Mikhail Krechetov, Jakub Marecek and Yury Maximov, Word Embedding as Entropy-Penalized Quadratic Semidefinite Programming

drinks (17:50-18:30)