Gradient-Based Adaptation of General Gaussian Kernels. - Tobias Glasmachers; Christian Igel (Neural Comput., 2005)

Degeneracy in model selection for SVMs with radial Gaussian kernel. - Tobias Glasmachers (ESANN, 2006)

Maximum-Gain Working Set Selection for SVMs. - Tobias Glasmachers; Christian Igel (J. Mach. Learn. Res., 2006)

Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts. - Britta Mersch; Tobias Glasmachers; Peter Meinicke; Christian Igel (Int. J. Neural Syst., 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)

On related violating pairs for working set selection in SMO algorithms. - Tobias Glasmachers (ESANN, 2008)

Uncertainty Handling in Model Selection for Support Vector Machines. - Tobias Glasmachers; Christian Igel (PPSN, 2008)

Shark. - Christian Igel; Verena Heidrich-Meisner; Tobias Glasmachers (J. Mach. Learn. Res., 2008)

Second-Order SMO Improves SVM Online and Active Learning. - Tobias Glasmachers; Christian Igel (Neural Comput., 2008)

Gradient based optimization of support vector machines. - Tobias Glasmachers (2008)

Exponential natural evolution strategies. - Tobias Glasmachers; Tom Schaul; Yi Sun 003; Daan Wierstra; Jürgen Schmidhuber (GECCO, 2010)

Universal Consistency of Multi-Class Support Vector Classification. - Tobias Glasmachers (NIPS, 2010)

A Natural Evolution Strategy for Multi-objective Optimization. - Tobias Glasmachers; Tom Schaul; Jürgen Schmidhuber (PPSN (1), 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)

Optimal Direct Policy Search. - Tobias Glasmachers; Jürgen Schmidhuber (AGI, 2011)

Coherence Progress: A Measure of Interestingness Based on Fixed Compressors. - Tom Schaul; Leo Pape; Tobias Glasmachers; Vincent Graziano; Jürgen Schmidhuber (AGI, 2011)

Novelty-based restarts for evolution strategies. - Giuseppe Cuccu; Faustino J. Gomez; Tobias Glasmachers (IEEE Congress on Evolutionary Computation, 2011)

High dimensions and heavy tails for natural evolution strategies. - Tom Schaul; Tobias Glasmachers; Jürgen Schmidhuber (GECCO, 2011)

Natural Evolution Strategies - Daan Wierstra; Tom Schaul; Tobias Glasmachers; Yi Sun 003; Jürgen Schmidhuber (CoRR, 2011)

A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes. - Ürün Dogan; Tobias Glasmachers; Christian Igel (ECML/PKDD (1), 2012)

Convergence of the IGO-Flow of Isotropic Gaussian Distributions on Convex Quadratic Problems. - Tobias Glasmachers (PPSN (1), 2012)

Kernel representations for evolving continuous functions. - Tobias Glasmachers; Jan Koutník; Jürgen Schmidhuber (Evol. Intell., 2012)

Accelerated Coordinate Descent with Adaptive Coordinate Frequencies. - Tobias Glasmachers; Ürün Dogan (ACML, 2013)

A natural evolution strategy with asynchronous strategy updates. - Tobias Glasmachers (GECCO, 2013)

Approximation properties of DBNs with binary hidden units and real-valued visible units. - Oswin Krause; Asja Fischer; Tobias Glasmachers; Christian Igel (ICML (1), 2013)

The Planning-ahead SMO Algorithm. - Tobias Glasmachers (CoRR, 2013)

Accelerated Linear SVM Training with Adaptive Variable Selection Frequencies - Tobias Glasmachers; Ürün Dogan (CoRR, 2013)

Testing Hypotheses by Regularized Maximum Mean Discrepancy - Somayeh Danafar; Paola M. V. Rancoita; Tobias Glasmachers; Kevin Whittingstall; Jürgen Schmidhuber (CoRR, 2013)

Handling sharp ridges with local supremum transformations. - Tobias Glasmachers (GECCO, 2014)

Information geometry in evolutionary computation. - Luigi Malagò; Tobias Glasmachers (GECCO (Companion), 2014)

Optimized Approximation Sets for Low-Dimensional Benchmark Pareto Fronts. - Tobias Glasmachers (PPSN, 2014)

Start Small, Grow Big? Saving Multi-objective Function Evaluations. - Tobias Glasmachers; Boris Naujoks; Günter Rudolph (PPSN, 2014)

Coordinate Descent with Online Adaptation of Coordinate Frequencies. - Tobias Glasmachers; Ürün Dogan (CoRR, 2014)

Natural evolution strategies. - Daan Wierstra; Tom Schaul; Tobias Glasmachers; Yi Sun 003; Jan Peters 001; Jürgen Schmidhuber (J. Mach. Learn. Res., 2014)

A CMA-ES with Multiplicative Covariance Matrix Updates. - Oswin Krause; Tobias Glasmachers (GECCO, 2015)

Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite. - Oswin Krause; Tobias Glasmachers; Nikolaus Hansen; Christian Igel (GECCO (Companion), 2016)

Anytime Bi-Objective Optimization with a Hybrid Multi-Objective CMA-ES (HMO-CMA-ES). - Ilya Loshchilov; Tobias Glasmachers (GECCO (Companion), 2016)

Fast model selection by limiting SVM training times. - Aydin Demircioglu; Daniel Horn; Tobias Glasmachers; Bernd Bischl; Claus Weihs (CoRR, 2016)

A Fast Incremental Archive for Multi-objective Optimization. - Tobias Glasmachers (CoRR, 2016)

A Unified View on Multi-class Support Vector Classification. - Ürün Dogan; Tobias Glasmachers; Christian Igel (J. Mach. Learn. Res., 2016)

Limits of End-to-End Learning. - Tobias Glasmachers (ACML, 2017)

A Fast Incremental BSP Tree Archive for Non-dominated Points. - Tobias Glasmachers (EMO, 2017)

Qualitative and Quantitative Assessment of Step Size Adaptation Rules. - Oswin Krause; Tobias Glasmachers; Christian Igel (FOGA, 2017)

Texture Attribute Synthesis and Transfer Using Feed-Forward CNNs. - Thomas Irmer; Tobias Glasmachers; Subhransu Maji (WACV, 2017)

Global Convergence of the (1+1) Evolution Strategy. - Tobias Glasmachers (CoRR, 2017)

Limited-Memory Matrix Adaptation for Large Scale Black-box Optimization. - Ilya Loshchilov; Tobias Glasmachers; Hans-Georg Beyer (CoRR, 2017)

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 (GECCO, 2018)

User-Centered Development of a Pedestrian Assistance System Using End-to-End Learning. - Hasham Shahid Qureshi; Tobias Glasmachers; Rebecca Wiczorek (ICMLA, 2018)

Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search. - Tobias Glasmachers; Sahar Qaadan (LOD, 2018)

Challenges in High-Dimensional Reinforcement Learning with Evolution Strategies. - Nils Müller; Tobias Glasmachers (PPSN (2), 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)

Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training. - Sahar Qaadan; Tobias Glasmachers (CoRR, 2018)

Challenges of convex quadratic bi-objective benchmark problems. - Tobias Glasmachers (GECCO, 2019)

Boosting Reinforcement Learning with Unsupervised Feature Extraction. - Simon Hakenes; Tobias Glasmachers (ICANN (1), 2019)

Online Budgeted Stochastic Coordinate Ascent for Large-Scale Kernelized Dual Support Vector Machine Training. - Sahar Qaadan; Abhijeet Pendyala; Merlin Schüler; Tobias Glasmachers (ICPRAM (Revised Selected Papers), 2019)

Dual SVM Training on a Budget. - Sahar Qaadan; Merlin Schüler; Tobias Glasmachers (ICPRAM, 2019)

Moment Vector Encoding of Protein Sequences for Supervised Classification. - Haneen Altartouri; Tobias Glasmachers (PACBB, 2019)

Vehicle Shape and Color Classification Using Convolutional Neural Network. - Mohamed Nafzi; Michael Brauckmann; Tobias Glasmachers (CoRR, 2019)

Large Scale Black-Box Optimization by Limited-Memory Matrix Adaptation. - Ilya Loshchilov; Tobias Glasmachers; Hans-Georg Beyer (IEEE Trans. Evol. Comput., 2019)

Analyzing Reinforcement Learning Benchmarks with Random Weight Guessing. - Declan Oller; Tobias Glasmachers; Giuseppe Cuccu (AAMAS, 2020)

Methods of the Vehicle Re-identification. - Mohamed Nafzi; Michael Brauckmann; Tobias Glasmachers (IntelliSys (1), 2020)

The Hessian Estimation Evolution Strategy. - Tobias Glasmachers; Oswin Krause (PPSN (1), 2020)

Data Augmentation and Clustering for Vehicle Make/Model Classification. - Mohamed Nafzi; Michael Brauckmann; Tobias Glasmachers (SAI (1), 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 001 (CoRR, 2020)

Global Convergence of the (1 + 1) Evolution Strategy to a Critical Point. - Tobias Glasmachers (Evol. Comput., 2020)

Non-local optimization: imposing structure on optimization problems by relaxation. - Nils Müller; Tobias Glasmachers (FOGA, 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)

AFRNN: Stable RNN with Top Down Feedback and Antisymmetry. - Tim Schwabe; Tobias Glasmachers; Maribel Acosta (ACML, 2022)

Recipe for Fast Large-Scale SVM Training: Polishing, Parallelism, and More RAM! - Tobias Glasmachers (BNAIC/BENELEARN, 2022)

DiBB: distributing black-box optimization. - Giuseppe Cuccu; Luca Rolshoven; Fabien Vorpe; Philippe Cudré-Mauroux; Tobias Glasmachers (GECCO, 2022)

Transfer Meta Learning. - Nico Zengeler; Tobias Glasmachers; Uwe Handmann (ICPR, 2022)

The (1+1)-ES Reliably Overcomes Saddle Points. - Tobias Glasmachers (PPSN (2), 2022)

From Motion to Muscle. - Marie Dominique Schmidt; 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 001 (CoRR, 2022)

Invariance to Quantile Selection in Distributional Continuous Control. - Felix Grün; Muhammad Saif-ur-Rehman; Tobias Glasmachers; Ioannis Iossifidis (CoRR, 2022)

Convergence Analysis of the Hessian Estimation Evolution Strategy. - Tobias Glasmachers; Oswin Krause (Evol. Comput., 2022)

Latent Representation Prediction Networks. - Hlynur Davíð Hlynsson; Merlin Schüler; Robin Schiewer; Tobias Glasmachers; Laurenz Wiskott (Int. J. Pattern Recognit. Artif. Intell., 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)

ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation. - Abhijeet Pendyala; Justin Dettmer; Tobias Glasmachers; Asma Atamna (LOD (1), 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)

Leveraging Topological Maps in Deep Reinforcement Learning for Multi-Object Navigation. - Simon Hakenes; Tobias Glasmachers (CoRR, 2023)

Weighted Initialisation of Evolutionary Instrument and Pitch Detection in Polyphonic Music. - Justin Dettmer; Igor Vatolkin; Tobias Glasmachers (EvoMUSART, 2024)

Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering. - Abhijeet Pendyala; Asma Atamna; Tobias Glasmachers (ECML/PKDD (10), 2024)

A Potential Function for a Variable-Metric Evolution Strategy. - Stephan Frank; Tobias Glasmachers (PPSN (2), 2024)

ProtoP-OD: Explainable Object Detection with Prototypical Parts. - Pavlos Rath-Manakidis; Frederik Strothmann; Tobias Glasmachers; Laurenz Wiskott (CoRR, 2024)

Deep-learning-based identification of individual motion characteristics from upper-limb trajectories towards disorder stage evaluation. - Tim Sziburis; Susanne Blex; Tobias Glasmachers; Ioannis Iossifidis (CoRR, 2024)

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 24271). - Anne Auger; Tobias Glasmachers; Martin S. Krejca; Johannes Lengler; Alexander Jungeilges (Dagstuhl Reports, 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)

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)

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 001 (Comput. Biol. Medicine, 2024)

Volume Determination Challenges in Waste Sorting Facilities: Observations and Strategies. - Tom Maus; Nico Zengeler; Dorothee Sänger; Tobias Glasmachers (Sensors, 2024)

Exploring Parameter Influence on Empirical Drift Behavior for Variable-Metric Evolution Strategies. - Stephan Frank; Tobias Glasmachers (CEC, 2025)

Variable Metric Evolution Strategies for High-dimensional Multi-Objective Optimization. - Tobias Glasmachers (GECCO, 2025)

SortingEnv: An Extendable RL-Environment for an Industrial Sorting Process. - Tom Maus; Nico Zengeler; Tobias Glasmachers (CoRR, 2025)

Curriculum RL meets Monte Carlo Planning: Optimization of a Real World Container Management Problem. - Abhijeet Pendyala; Tobias Glasmachers (CoRR, 2025)

Deep Reinforcement Learning Based Navigation with Macro Actions and Topological Maps. - Simon Hakenes; Tobias Glasmachers (CoRR, 2025)

A Superlinearly Convergent Evolution Strategy. - Tobias Glasmachers (CoRR, 2025)

Leveraging Genetic Algorithms for Efficient Demonstration Generation in Real-World Reinforcement Learning Environments. - Tom Maus; Asma Atamna; Tobias Glasmachers (CoRR, 2025)