COSEAL Workshop 2021

The first virtual COSEAL workshop with roughly half of the attendees


The eighth COSEAL Workshop is a forum for discussing the most recent advances in the automated configuration and selection of algorithms. It will take place on September 17th and is organized by Bernd Bischl and Marius Lindauer .

The workshop will consist of posters and talks about late-breaking research and useful tools, discussions regarding intra- and international cooperation, and many opportunities to interact with other attendees. 


Administrative questions :

Scope of the Workshop

The scope of COSEAL includes, but is not limited to:

  • Algorithm selection
  • Algorithm configuration 
  • Algorithm portfolios
  • Performance predictions and empirical performance models
  • Bayesian optimization
  • Hyperparameter optimization
  • Automated machine learning (AutoML)
  • Neural architecture search
  • Meta-learning
  • Algorithm and parameter control
  • Explorative landscape analysis
  • Programming by optimization
  • Hyper-heuristics

Important dates

  • Registration deadline : Sept. 1st
  • Talk/poster abstract deadline : Sept 1st
  • Poster submission deadline: Sept 13th
  • Workshop : September 17th 2021


COSEAL 2021 workshop will be an virtual workshop with talks in Zoom, and poster sessions and social event in gather town.

Registration Fees

None! For free!

Registration and Applications


Tentative Schedule

Time slots according to CEST:

08:45 – 09:00: Joining the Zoom call, small-talk and enjoy a tee or coffee together
09:00 – 09:15: Opening
09:15 – 09:45: Contributed Talk I (20+10)
09:45 – 10:15: Contributed Talk II (20+10)
10:15 – 10:45: Coffee Break with Speed Dating in break out-rooms (15min with a small set of random attendees)
10:45 – 12:00: Poster Session I (in Gather Town)
12:00 – 14:00: Lunch break
14:00 – 14:30: Contributed Talk III (20+10)
14:30 – 15:00: Contributed Talk IV (20+10)
15:00 – 15:30: Coffee Break with Speed Dating in break-out rooms
15:30 – 17:00: Poster Session II (in Gather Town)
17:00 – 18:00: Panel Discussion
18:00 – open end: Social event

Contributed Talks

Contributed Talk I: Jacopo Mauro and Roberto Amadini: Algorithm Selection with SUNNY: past, present and future

Contributed Talk II: Laurens Bliek: EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions

Contributed Talk III: Marie Anastacio: Statistical Comparison of Algorithm Performance Through Instance Selection

Contributed Talk IV: Dimitri Weiß: Gray Box Realtime Algorithm Configuration

Poster Session I

Eftimov, Tome: Personalized Machine Learning Models for Performance Prediction for Black-Box Optimization Problems

Deng, Difan: Auto-PyTorch for Time Series Prediction

Benjamins, Carolin: Dynamic Algorithm Configuration with Bayesian Optimization (DAC-BO): Learning Dynamic Hyperparameters through Reinforcement Learning.

König, Matthias: Speeding Up Neural Network Robustness Verification via Algorithm Configuration
and an Optimised Mixed Integer Linear Programming Solver Portfolio

Biedenkapp, André and Adriaensen, Steven: Dynamic Algorithm Configuration: The Journey so Far

Eggensperger, Katharina: HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO

Tornede, Alexander: Multi-Armed Bandits for Online Algorithm Selection under Censored Feedback

Dang, Nguyen: Dynamic Algorithm Configuration for the 1+(lambda,lambda) Genetic Algorithm

Hanselle, Jonas: Algorithm Selection via Hybrid Ranking and Regression

Sass, Rene: DeepCAVE: A Versatile Tool for Explaining AutoML

Poster Session II

Vermetten, Diederick: IOHprofiler: A Benchmarking platform for the Performance of Iterative Optimization Heuristics with Improved Logging and Visualization

Woźnica, Katarzyna: metaMIMIC: analysis of hyperparameter transferability for tabular data using MIMIC-IV database

Tornede, Tanja: Green AutoML: Towards more Sustainable Automated Machine Learning

Meyer, Anne and Bessai, Jan: Decision Pipeline Synthesis

Feurer, Matthias: Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning

Rajan, Raghu: Population Based Bandits with Backtracking (PB2-BT)

Paleta, Leonard: On perfect Roman domination under some binary operations of graphs

Eimer, Theresa: DACBench: A Benchmark library for Dynamic Algorithm Configuration

Pérez Cáceres, Leslie, de Souza, Marcelo, Lopez-Ibanez, Manuel and Ritt, Marcus: Evaluation of Random Forest importance measures for Algorithm configuration

Kostovska, Ana: OPTION: An OPTImization algorithm benchmarking ONtology

Dreo, Johann: Using Irace, Paradiseo and IOHprofiler for Large-Scale Algorithm Configuration

Panel Discussion

Topic: Validation and Explaining Meta-Algorithmics

Moderator: Janek Thomas

Panel members:

  • Thomas Bartz-Beielstein
  • Johann Dreo
  • Leslie Pérez Cáceres
  • Bernd Bischl
  • Marius Lindauer
  • Frank Hutter


Supported by

  • Florian Karl (Ludwig-Maximilian University Munich)
  • Daniel Ritter (Leibniz University Hannover)