Tobias Glasmachers

According to our database, Tobias Glasmachers authored at least 90 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Volume Determination Challenges in Waste Sorting Facilities: Observations and Strategies.

Tom Maus, Nico Zengeler, Dorothee Sänger, Tobias Glasmachers

Sensors, April, 2024

ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data.

Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes

Comput. Biol. Medicine, January, 2024

Understanding activation patterns in artificial neural networks by exploring stochastic processes: Discriminating generalization from memorization.

Stephan Johann Lehmler, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis

Neurocomputing, 2024

tachAId - An interactive tool supporting the design of human-centered AI solutions.

Max Bauroth, Pavlos Rath-Manakidis, Valentin Langholf, Laurenz Wiskott, Tobias Glasmachers

Frontiers Artif. Intell., 2024

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 24271).

Anne Auger, Tobias Glasmachers, Martin S. Krejca, Johannes Lengler, Alexander Jungeilges

Dagstuhl Reports, 2024

ProtoP-OD: Explainable Object Detection with Prototypical Parts.

Pavlos Rath-Manakidis, Frederik Strothmann, Tobias Glasmachers, Laurenz Wiskott

CoRR, 2024

A Potential Function for a Variable-Metric Evolution Strategy.

Stephan Frank, Tobias Glasmachers

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering.

Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

Weighted Initialisation of Evolutionary Instrument and Pitch Detection in Polyphonic Music.

Justin Dettmer, Igor Vatolkin, Tobias Glasmachers

Proceedings of the Artificial Intelligence in Music, Sound, Art and Design, 2024

2023

Leveraging Topological Maps in Deep Reinforcement Learning for Multi-Object Navigation.

Simon Hakenes, Tobias Glasmachers

CoRR, 2023

Understanding Activation Patterns in Artificial Neural Networks by Exploring Stochastic Processes.

Stephan Johann Lehmler, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis

CoRR, 2023

ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation.

Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers, Asma Atamna

Proceedings of the Machine Learning, Optimization, and Data Science, 2023

2022

Global Linear Convergence of Evolution Strategies on More than Smooth Strongly Convex Functions.

Youhei Akimoto, Anne Auger, Tobias Glasmachers, Daiki Morinaga

SIAM J. Optim., 2022

Latent Representation Prediction Networks.

Hlynur Davíð Hlynsson, Merlin Schüler, Robin Schiewer, Tobias Glasmachers, Laurenz Wiskott

Int. J. Pattern Recognit. Artif. Intell., 2022

Convergence Analysis of the Hessian Estimation Evolution Strategy.

Tobias Glasmachers, Oswin Krause

Evol. Comput., 2022

Invariance to Quantile Selection in Distributional Continuous Control.

Felix Grün, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis

CoRR, 2022

ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces.

Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes

CoRR, 2022

From Motion to Muscle.

Marie Dominique Schmidt, Tobias Glasmachers, Ioannis Iossifidis

CoRR, 2022

The (1+1)-ES Reliably Overcomes Saddle Points.

Tobias Glasmachers

Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Transfer Meta Learning.

Nico Zengeler, Tobias Glasmachers, Uwe Handmann

Proceedings of the 26th International Conference on Pattern Recognition, 2022

DiBB: distributing black-box optimization.

Giuseppe Cuccu, Luca Rolshoven, Fabien Vorpe, Philippe Cudré-Mauroux, Tobias Glasmachers

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Recipe for Fast Large-Scale SVM Training: Polishing, Parallelism, and More RAM!

Tobias Glasmachers

Proceedings of the Artificial Intelligence and Machine Learning, 2022

AFRNN: Stable RNN with Top Down Feedback and Antisymmetry.

Tim Schwabe, Tobias Glasmachers, Maribel Acosta

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Deep Transfer-Learning for patient specific model re-calibration: Application to sEMG-Classification.

Stephan Johann Lehmler, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis

CoRR, 2021

Non-local optimization: imposing structure on optimization problems by relaxation.

Nils Müller, Tobias Glasmachers

Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

2020

Global Convergence of the (1 + 1) Evolution Strategy to a Critical Point.

Tobias Glasmachers

Evol. Comput., 2020

Improving the performance of EEG decoding using anchored-STFT in conjunction with gradient norm adversarial augmentation.

Omair Ali, Muhammad Saif-ur-Rehman, Susanne Dyck, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes

CoRR, 2020

Data Augmentation and Clustering for Vehicle Make/Model Classification.

Mohamed Nafzi, Michael Brauckmann, Tobias Glasmachers

Proceedings of the Intelligent Computing, 2020

The Hessian Estimation Evolution Strategy.

Tobias Glasmachers, Oswin Krause

Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

Methods of the Vehicle Re-identification.

Mohamed Nafzi, Michael Brauckmann, Tobias Glasmachers

Proceedings of the Intelligent Systems and Applications, 2020

Analyzing Reinforcement Learning Benchmarks with Random Weight Guessing.

Declan Oller, Tobias Glasmachers, Giuseppe Cuccu

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Large Scale Black-Box Optimization by Limited-Memory Matrix Adaptation.

Ilya Loshchilov, Tobias Glasmachers, Hans-Georg Beyer

IEEE Trans. Evol. Comput., 2019

Vehicle Shape and Color Classification Using Convolutional Neural Network.

Mohamed Nafzi, Michael Brauckmann, Tobias Glasmachers

CoRR, 2019

Moment Vector Encoding of Protein Sequences for Supervised Classification.

Haneen Altartouri, Tobias Glasmachers

Proceedings of the Practical Applications of Computational Biology and Bioinformatics, 2019

Dual SVM Training on a Budget.

Sahar Qaadan, Merlin Schüler, Tobias Glasmachers

Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods, 2019

Online Budgeted Stochastic Coordinate Ascent for Large-Scale Kernelized Dual Support Vector Machine Training.

Sahar Qaadan, Abhijeet Pendyala, Merlin Schüler, Tobias Glasmachers

Proceedings of the Pattern Recognition Applications and Methods, 2019

Boosting Reinforcement Learning with Unsupervised Feature Extraction.

Simon Hakenes, Tobias Glasmachers

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

Challenges of convex quadratic bi-objective benchmark problems.

Tobias Glasmachers

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

2018

Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training.

Sahar Qaadan, Tobias Glasmachers

CoRR, 2018

A comparative study on large scale kernelized support vector machines.

Daniel Horn, Aydin Demircioglu, Bernd Bischl, Tobias Glasmachers, Claus Weihs

Adv. Data Anal. Classif., 2018

Challenges in High-Dimensional Reinforcement Learning with Evolution Strategies.

Nils Müller, Tobias Glasmachers

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search.

Tobias Glasmachers, Sahar Qaadan

Proceedings of the Machine Learning, Optimization, and Data Science, 2018

User-Centered Development of a Pedestrian Assistance System Using End-to-End Learning.

Hasham Shahid Qureshi, Tobias Glasmachers, Rebecca Wiczorek

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Drift theory in continuous search spaces: expected hitting time of the (1 + 1)-ES with 1/5 success rule.

Youhei Akimoto, Anne Auger, Tobias Glasmachers

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

2017

Limited-Memory Matrix Adaptation for Large Scale Black-box Optimization.

Ilya Loshchilov, Tobias Glasmachers, Hans-Georg Beyer

CoRR, 2017

Global Convergence of the (1+1) Evolution Strategy.

Tobias Glasmachers

CoRR, 2017

Texture Attribute Synthesis and Transfer Using Feed-Forward CNNs.

Thomas Irmer, Tobias Glasmachers, Subhransu Maji

Proceedings of the 2017 IEEE Winter Conference on Applications of Computer Vision, 2017

Qualitative and Quantitative Assessment of Step Size Adaptation Rules.

Oswin Krause, Tobias Glasmachers, Christian Igel

Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2017

A Fast Incremental BSP Tree Archive for Non-dominated Points.

Tobias Glasmachers

Proceedings of the Evolutionary Multi-Criterion Optimization, 2017

Limits of End-to-End Learning.

Tobias Glasmachers

Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016

A Unified View on Multi-class Support Vector Classification.

Ürün Dogan, Tobias Glasmachers, Christian Igel

J. Mach. Learn. Res., 2016

A Fast Incremental Archive for Multi-objective Optimization.

Tobias Glasmachers

CoRR, 2016

Fast model selection by limiting SVM training times.

Aydin Demircioglu, Daniel Horn, Tobias Glasmachers, Bernd Bischl, Claus Weihs

CoRR, 2016

Anytime Bi-Objective Optimization with a Hybrid Multi-Objective CMA-ES (HMO-CMA-ES).

Ilya Loshchilov, Tobias Glasmachers

Proceedings of the Genetic and Evolutionary Computation Conference, 2016

Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite.

Oswin Krause, Tobias Glasmachers, Nikolaus Hansen, Christian Igel

Proceedings of the Genetic and Evolutionary Computation Conference, 2016

2015

A CMA-ES with Multiplicative Covariance Matrix Updates.

Oswin Krause, Tobias Glasmachers

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2014

Natural evolution strategies.

Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, Jürgen Schmidhuber

J. Mach. Learn. Res., 2014

Coordinate Descent with Online Adaptation of Coordinate Frequencies.

Tobias Glasmachers, Ürün Dogan

CoRR, 2014

Start Small, Grow Big? Saving Multi-objective Function Evaluations.

Tobias Glasmachers, Boris Naujoks, Günter Rudolph

Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

Optimized Approximation Sets for Low-Dimensional Benchmark Pareto Fronts.

Tobias Glasmachers

Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

Information geometry in evolutionary computation.

Luigi Malagò, Tobias Glasmachers

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Handling sharp ridges with local supremum transformations.

Tobias Glasmachers

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

2013

Testing Hypotheses by Regularized Maximum Mean Discrepancy

Somayeh Danafar, Paola M. V. Rancoita, Tobias Glasmachers, Kevin Whittingstall, Jürgen Schmidhuber

CoRR, 2013

Accelerated Linear SVM Training with Adaptive Variable Selection Frequencies

Tobias Glasmachers, Ürün Dogan

CoRR, 2013

The Planning-ahead SMO Algorithm.

Tobias Glasmachers

CoRR, 2013

Approximation properties of DBNs with binary hidden units and real-valued visible units.

Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel

Proceedings of the 30th International Conference on Machine Learning, 2013

A natural evolution strategy with asynchronous strategy updates.

Tobias Glasmachers

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Accelerated Coordinate Descent with Adaptive Coordinate Frequencies.

Tobias Glasmachers, Ürün Dogan

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Kernel representations for evolving continuous functions.

Tobias Glasmachers, Jan Koutník, Jürgen Schmidhuber

Evol. Intell., 2012

Convergence of the IGO-Flow of Isotropic Gaussian Distributions on Convex Quadratic Problems.

Tobias Glasmachers

Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012

A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes.

Ürün Dogan, Tobias Glasmachers, Christian Igel

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

2011

Natural Evolution Strategies

Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jürgen Schmidhuber

CoRR, 2011

High dimensions and heavy tails for natural evolution strategies.

Tom Schaul, Tobias Glasmachers, Jürgen Schmidhuber

Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Novelty-based restarts for evolution strategies.

Giuseppe Cuccu, Faustino J. Gomez, Tobias Glasmachers

Proceedings of the IEEE Congress on Evolutionary Computation, 2011

Coherence Progress: A Measure of Interestingness Based on Fixed Compressors.

Tom Schaul, Leo Pape, Tobias Glasmachers, Vincent Graziano, Jürgen Schmidhuber

Proceedings of the Artificial General Intelligence - 4th International Conference, 2011

Optimal Direct Policy Search.

Tobias Glasmachers, Jürgen Schmidhuber

Proceedings of the Artificial General Intelligence - 4th International Conference, 2011

2010

Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters.

Tobias Glasmachers, Christian Igel

IEEE Trans. Pattern Anal. Mach. Intell., 2010

A Natural Evolution Strategy for Multi-objective Optimization.

Tobias Glasmachers, Tom Schaul, Jürgen Schmidhuber

Proceedings of the Parallel Problem Solving from Nature, 2010

Universal Consistency of Multi-Class Support Vector Classification.

Tobias Glasmachers

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Exponential natural evolution strategies.

Tobias Glasmachers, Tom Schaul, Yi Sun, Daan Wierstra, Jürgen Schmidhuber

Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2008

Gradient based optimization of support vector machines.

Tobias Glasmachers

PhD thesis, 2008

Second-Order SMO Improves SVM Online and Active Learning.

Tobias Glasmachers, Christian Igel

Neural Comput., 2008

Shark.

Christian Igel, Verena Heidrich-Meisner, Tobias Glasmachers

J. Mach. Learn. Res., 2008

Uncertainty Handling in Model Selection for Support Vector Machines.

Tobias Glasmachers, Christian Igel

Proceedings of the Parallel Problem Solving from Nature, 2008

On related violating pairs for working set selection in SMO algorithms.

Tobias Glasmachers

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007

Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection.

Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, Peter Meinicke

IEEE ACM Trans. Comput. Biol. Bioinform., 2007

Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts.

Britta Mersch, Tobias Glasmachers, Peter Meinicke, Christian Igel

Int. J. Neural Syst., 2007

2006

Maximum-Gain Working Set Selection for SVMs.

Tobias Glasmachers, Christian Igel

J. Mach. Learn. Res., 2006

Degeneracy in model selection for SVMs with radial Gaussian kernel.

Tobias Glasmachers

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

2005

Gradient-Based Adaptation of General Gaussian Kernels.

Tobias Glasmachers, Christian Igel

Neural Comput., 2005