Pascal Kerschke | DeepAI

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∙ 02/16/2023

Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games

The term Procedural Content Generation (PCG) refers to the (semi-)automa...

2 Vanessa Volz, et al. ∙

∙ 11/26/2022

Mixture of Decision Trees for Interpretable Machine Learning

This work introduces a novel interpretable machine learning method calle...

0 Simeon Brüggenjürgen, et al. ∙

∙ 07/30/2022

HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis

Hyperparameter optimization (HPO) is a key component of machine learning...

1 Lennart Schneider, et al. ∙

∙ 04/22/2022

MOLE: Digging Tunnels Through Multimodal Multi-Objective Landscapes

Recent advances in the visualization of continuous multimodal multi-obje...

2 Lennart Schäpermeier, et al. ∙

∙ 04/12/2022

A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes

Exploratory Landscape Analysis is a powerful technique for numerically c...

8 Moritz Vinzent Seiler, et al. ∙

∙ 11/29/2020

To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes

Simultaneously visualizing the decision and objective space of continuou...

16 Lennart Schäpermeier, et al. ∙

∙ 10/02/2020

Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent

Multimodality is one of the biggest difficulties for optimization as loc...

10 Vera Steinhoff, et al. ∙

∙ 07/07/2020

Benchmarking in Optimization: Best Practice and Open Issues

This survey compiles ideas and recommendations from more than a dozen re...

11 Thomas Bartz-Beielstein, et al. ∙

∙ 06/29/2020

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem

In this work we focus on the well-known Euclidean Traveling Salesperson ...

9 Moritz Seiler, et al. ∙

∙ 06/25/2020

Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems

When dealing with continuous single-objective problems, multimodality po...

4 Vera Steinhoff, et al. ∙

∙ 06/20/2020

One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes

Visualization techniques for the decision space of continuous multi-obje...

15 Lennart Schäpermeier, et al. ∙

∙ 05/27/2020

Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries

Artificial neural networks in general and deep learning networks in part...

46 Moritz Seiler, et al. ∙

∙ 05/27/2020

Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection

The Traveling-Salesperson-Problem (TSP) is arguably one of the best-know...

5 Jakob Bossek, et al. ∙

∙ 03/30/2020

Initial Design Strategies and their Effects on Sequential Model-Based Optimization

Sequential model-based optimization (SMBO) approaches are algorithms for...

3 Jakob Bossek, et al. ∙

∙ 02/04/2020

The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics

Several important optimization problems in the area of vehicle routing c...

2 Jakob Bossek, et al. ∙

∙ 12/19/2019

One-Shot Decision-Making with and without Surrogates

One-shot decision making is required in situations in which we can evalu...

20 Jakob Bossek, et al. ∙

∙ 11/28/2018

Automated Algorithm Selection: Survey and Perspectives

It has long been observed that for practically any computational problem...

2 Pascal Kerschke, et al. ∙

∙ 06/20/2018

Estimation of component reliability in repairable series systems with masked cause of failure by means of latent variables

In this work, we propose two methods, a Bayesian and a maximum likelihoo...

0 Agatha Rodrigues, et al. ∙

∙ 11/24/2017

Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning

In this paper, we build upon previous work on designing informative and ...

0 Pascal Kerschke, et al. ∙

∙ 08/17/2017

Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package flacco

Choosing the best-performing optimizer(s) out of a portfolio of optimiza...

0 Pascal Kerschke, et al. ∙

∙ 01/05/2017

OpenML: An R Package to Connect to the Machine Learning Platform OpenML

OpenML is an online machine learning platform where researchers can easi...

0 Giuseppe Casalicchio, et al. ∙

∙ 06/08/2015

ASlib: A Benchmark Library for Algorithm Selection

The task of algorithm selection involves choosing an algorithm from a se...

0 Bernd Bischl, et al. ∙

∙ 03/26/2015

Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms

In the a posteriori approach of multiobjective optimization the Pareto f...

0 Luis Marti, et al. ∙

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