21 citations · 70 across the 11 of their papers we have counts for
14 papers
Comparing Heuristics, Constraint Optimization, and Reinforcement Learning for an Industrial 2D Packing Problem
Stefan Böhm, Martin Neumayer, Oliver Kramer +2
Cutting and Packing problems are occurring in different industries with a direct impact on the revenue of businesses. Generally, the goal in Cutting and Packing is to assign a set…
Earnings Prediction with Deep Learning
Lars Elend, Sebastian A. Tideman, Kerstin Lopatta +1
In the financial sector, a reliable forecast the future financial performance of a company is of great importance for investors' investment decisions. In this paper we compare long…
Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates
Tim Cofala, Lars Elend, Philip Mirbach +3
Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SA…
Learned Weight Sharing for Deep Multi-Task Learning by Natural Evolution Strategy and Stochastic Gradient Descent
Jonas Prellberg, Oliver Kramer
In deep multi-task learning, weights of task-specific networks are shared between tasks to improve performance on each single one. Since the question, which weights to share betwee…
Acute Lymphoblastic Leukemia Classification from Microscopic Images using Convolutional Neural Networks
Jonas Prellberg, Oliver Kramer
Examining blood microscopic images for leukemia is necessary when expensive equipment for flow cytometry is unavailable. Automated systems can ease the burden on medical experts fo…
Limited Evaluation Evolutionary Optimization of Large Neural Networks
Jonas Prellberg, Oliver Kramer
Stochastic gradient descent is the most prevalent algorithm to train neural networks. However, other approaches such as evolutionary algorithms are also applicable to this task. Ev…