Bernhard Alois Moser

64 papers A* 6C 2Journal 41Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Exploiting Space Folding by Neural Networks. AAAI Michal Lewandowski, Raphael Pisoni, Bernhard Heinzl, Bernhard Alois Moser
2026	A*	`conf`	Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent (Abstract Reprint). AAAI Mohit Kumar, Alexander Valentinitsch, Magdalena Fuchs, Mathias Brucker, Juliana Bowles, Adnan Husakovic, Ali Abbas, Bernhard Alois Moser
2026	J	`jnl`	Linearized Bregman Iterations for Sparse Spiking Neural Networks. CoRR Daniel Windhager, Bernhard Alois Moser, Michael Lunglmayr
2025	C	`conf`	A Hardware Architecture for Efficient Adaptive Threshold-Based Sampling using Weyl's Discrepancy. ISCAS Anna Werzi, Simon Dorrer, Bernhard Alois Moser, Michael Lunglmayr
2025	J	`jnl`	Integrate-and-Fire from a Mathematical and Signal Processing Perspective. CoRR Bernhard Alois Moser, Anna Werzi, Michael Lunglmayr
2025	J	`jnl`	Lightweight LIF-only SNN accelerator using differential time encoding. CoRR Daniel Windhager, Lothar Ratschbacher, Bernhard Alois Moser, Michael Lunglmayr
2025	—	`conf`	Mineuron: Minimal Neuron Realization For Fast Fpga Snn Inference Using Logic Optimization. ICIPW Daniel Windhager, Lothar Ratschbacher, Bernhard Alois Moser, Michael Lunglmayr
2025	J	`jnl`	On Space Folds of ReLU Neural Networks. CoRR Michal Lewandowski, Hamid Eghbalzadeh, Bernhard Heinzl, Raphael Pisoni, Bernhard Alois Moser
2025	J	`jnl`	On Space Folds of ReLU Neural Networks. Trans. Mach. Learn. Res. Michal Lewandowski, Hamid Eghbalzadeh, Bernhard Heinzl, Raphael Pisoni, Bernhard Alois Moser
2025	C	`conf`	Spiking Neural Network Accelerator Architecture for Differential-Time Representation using Learned Encoding. ISCAS Daniel Windhager, Lothar Ratschbacher, Bernhard Alois Moser, Michael Lunglmayr
2025	J	`jnl`	The Resurrection of the ReLU. CoRR Cosku Can Horuz, Geoffrey Kasenbacher, Saya Higuchi, Sebastian Kairat, Jendrik Stoltz, Moritz Pesl, Bernhard Alois Moser, Christoph Linse, Thomas Martinetz, Sebastian Otte
2025	J	`jnl`	The Space Between: On Folding, Symmetries and Sampling. CoRR Michal Lewandowski, Bernhard Heinzl, Raphael Pisoni, Bernhard Alois Moser
2024	J	`jnl`	CantorNet: A Sandbox for Testing Geometrical and Topological Complexity Measures. CoRR Michal Lewandowski, Hamid Eghbalzadeh, Bernhard Alois Moser
2024	J	`jnl`	Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent. CoRR Mohit Kumar, Alexander Valentinitsch, Magdalena Fuchs, Mathias Brucker, Juliana Bowles, Adnan Husakovic, Ali Abbas, Bernhard Alois Moser
2024	—	`conf`	Integrate-and-Fire from a Mathematical and Signal Processing Perspective. IEEECONF Bernhard Alois Moser, Anna Werzi, Michael Lunglmayr
2024	J	`jnl`	Managing human-AI collaborations within Industry 5.0 scenarios via knowledge graphs: key challenges and lessons learned. Frontiers Artif. Intell. Franz Krause, Heiko Paulheim, Elmar Kiesling, Kabul Kurniawan, Maria Chiara Leva, Hector Diego Estrada-Lugo, Gernot Stübl, Nazim Kemal Üre, Javier Dominguez-Ledo, Maqbool Khan, Pedro Demolder, Hans Gaux, Bernhard Heinzl, Thomas Hoch, Jorge Martinez-Gil, Agastya Silvina, Bernhard Alois Moser
2024	J	`jnl`	On Leaky-Integrate-and Fire as Spike-Train-Quantization Operator on Dirac-Superimposed Continuous-Time Signals. CoRR Bernhard Alois Moser, Michael Lunglmayr
2024	A*	`conf`	On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint). IJCAI Mohit Kumar, Bernhard Alois Moser, Lukas Fischer
2024	J	`jnl`	On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach. J. Artif. Intell. Res. Mohit Kumar, Bernhard Alois Moser, Lukas Fischer
2024	J	`jnl`	On the Sampling Sparsity of Neuromorphic Analog-to-Spike Conversion based on Leaky Integrate-and-Fire. CoRR Bernhard Alois Moser, Michael Lunglmayr
2024	—	`conf`	On the Solvability of the XOR Problem by Spiking Neural Networks. DEXA Workshops Bernhard Alois Moser, Michael Lunglmayr
2024	J	`jnl`	On the Solvability of the {XOR} Problem by Spiking Neural Networks. CoRR Bernhard Alois Moser, Michael Lunglmayr
2024	J	`jnl`	Rethinking data augmentation for adversarial robustness. Inf. Sci. Hamid Eghbal-zadeh, Werner Zellinger, Maura Pintor, Kathrin Grosse, Khaled Koutini, Bernhard Alois Moser, Battista Biggio, Gerhard Widmer
2024	—	`conf`	Risk Assessment in AI System Engineering: Experiences and Lessons Learned from a Practitioner's Perspective. DEXA Workshops Magdalena Fuchs, Lukas Fischer, Alessio Montuoro, Mohit Kumar, Bernhard Alois Moser
2024	—	`conf`	SNN Architecture for Differential Time Encoding Using Decoupled Processing Time. AICAS Daniel Windhager, Bernhard Alois Moser, Michael Lunglmayr
2024	J	`jnl`	Spiking neural networks in the Alexiewicz topology: A new perspective on analysis and error bounds. Neurocomputing Bernhard Alois Moser, Michael Lunglmayr
2023	A*	`conf`	Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. ICLR Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger
2023	J	`jnl`	Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. CoRR Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger
2023	J	`jnl`	An Information Theoretic Approach to Privacy-Preserving Interpretable and Transferable Learning. Algorithms Mohit Kumar, Bernhard Alois Moser, Lukas Fischer, Bernhard Freudenthaler
2023	J	`jnl`	Kernel Affine Hull Machines for Differentially Private Learning. CoRR Mohit Kumar, Bernhard Alois Moser, Lukas Fischer
2023	—	`conf`	Measuring Overhead Costs of Federated Learning Systems by Eavesdropping. DEXA Workshops Rainer Meindl, Bernhard Alois Moser
2023	J	`jnl`	Quantization in Spiking Neural Networks. CoRR Bernhard Alois Moser, Michael Lunglmayr
2023	J	`jnl`	Spiking Neural Networks in the Alexiewicz Topology: A New Perspective on Analysis and Error Bounds. CoRR Bernhard Alois Moser, Michael Lunglmayr
2023	J	`jnl`	Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. ACM Comput. Surv. Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli
2022	J	`jnl`	A Systematic Mapping Study of Predictive Maintenance in SMEs. IEEE Access Maqbool Khan, Arshad Ahmad, Florian Sobieczky, Mario Pichler, Bernhard Alois Moser, Ivo Bukovsky
2022	A*	`conf`	Tessellation-Filtering ReLU Neural Networks. IJCAI Bernhard Alois Moser, Michal Lewandowski, Somayeh Kargaran, Werner Zellinger, Battista Biggio, Christoph Koutschan
2022	J	`jnl`	Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. CoRR Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli
2021	J	`jnl`	An optimal (∊, δ)-differentially private learning of distributed deep fuzzy models. Inf. Sci. Mohit Kumar, Michael Rossbory, Bernhard Alois Moser, Bernhard Freudenthaler
2021	J	`jnl`	Information Theoretic Evaluation of Privacy-Leakage, Interpretability, and Transferability for a Novel Trustworthy AI Framework. CoRR Mohit Kumar, Bernhard Alois Moser, Lukas Fischer, Bernhard Freudenthaler
2021	J	`jnl`	Membership-Mappings for Data Representation Learning. CoRR Mohit Kumar, Bernhard Alois Moser, Lukas Fischer, Bernhard Freudenthaler
2021	J	`jnl`	On generalization in moment-based domain adaptation. Ann. Math. Artif. Intell. Werner Zellinger, Bernhard Alois Moser, Susanne Saminger-Platz
2021	J	`jnl`	On the truncated Hausdorff moment problem under Sobolev regularity conditions. Appl. Math. Comput. Werner Zellinger, Bernhard Alois Moser
2021	A*	`conf`	The balancing principle for parameter choice in distance-regularized domain adaptation. NeurIPS Werner Zellinger, Natalia Shepeleva, Marius-Constantin Dinu, Hamid Eghbal-zadeh, Hoan Duc Nguyen, Bernhard Nessler, Sergei V. Pereverzyev, Bernhard Alois Moser
2020	—	`conf`	Differentially Private Learning of Distributed Deep Models. UMAP (Adjunct Publication) Mohit Kumar, Michael Rossbory, Bernhard Alois Moser, Bernhard Freudenthaler
2020	J	`jnl`	Domain adaptation for regression under Beer-Lambert's law. Knowl. Based Syst. Ramin Nikzad-Langerodi, Werner Zellinger, Susanne Saminger-Platz, Bernhard Alois Moser
2020	J	`jnl`	Learning Bounds for Moment-Based Domain Adaptation. CoRR Werner Zellinger, Bernhard Alois Moser, Susanne Saminger-Platz
2020	J	`jnl`	On Data Augmentation and Adversarial Risk: An Empirical Analysis. CoRR Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus, Verena Haunschmid, Michal Lewandowski, Werner Zellinger, Bernhard Alois Moser, Gerhard Widmer
2020	—	`conf`	Variational Optimization of Informational Privacy. DEXA Workshops Mohit Kumar, David Brunner, Bernhard Alois Moser, Bernhard Freudenthaler
2019	—	`conf`	An Event-Driven Approach for Time-Domain Recognition of Spoken English Letters. EBCCSP Saeed Mian Qaisar, S. Laskar, Michael Lunglmayr, Bernhard Alois Moser, R. Abdulbaqi, R. Banafia
2019	J	`jnl`	DeepSNP: An End-to-End Deep Neural Network with Attention-Based Localization for Breakpoint Detection in Single-Nucleotide Polymorphism Array Genomic Data. J. Comput. Biol. Hamid Eghbal-zadeh, Lukas Fischer, Niko Popitsch, Florian Kromp, Sabine Taschner-Mandl, Teresa Gerber, Eva Bozsaky, Peter F. Ambros, Inge M. Ambros, Gerhard Widmer, Bernhard Alois Moser
2019	—	`conf`	Deriving an Optimal Noise Adding Mechanism for Privacy-Preserving Machine Learning. DEXA Workshops Mohit Kumar, Michael Rossbory, Bernhard Alois Moser, Bernhard Freudenthaler
2019	J	`jnl`	On Quasi-Isometry of Threshold-Based Sampling. IEEE Trans. Signal Process. Bernhard Alois Moser, Michael Lunglmayr
2019	J	`jnl`	Robust unsupervised domain adaptation for neural networks via moment alignment. Inf. Sci. Werner Zellinger, Bernhard Alois Moser, Thomas Grubinger, Edwin Lughofer, Thomas Natschläger, Susanne Saminger-Platz
2019	—	`conf`	Tradeoff Analysis of Discrepancy-Based Adaptive Thresholding Approach. EBCCSP Michael Lunglmayr, Saeed Mian Qaisar, Bernhard Alois Moser
2018	J	`jnl`	Deep SNP: An End-to-end Deep Neural Network with Attention-based Localization for Break-point Detection in SNP Array Genomic data. CoRR Hamid Eghbal-zadeh, Lukas Fischer, Niko Popitsch, Florian Kromp, Sabine Taschner-Mandl, Khaled Koutini, Teresa Gerber, Eva Bozsaky, Peter F. Ambros, Inge M. Ambros, Gerhard Widmer, Bernhard Alois Moser
2017	—	`conf`	Estimating the signal reconstruction error from threshold-based sampling without knowing the original signal. EBCCSP Bernhard Alois Moser
2017	J	`jnl`	Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment. CoRR Werner Zellinger, Bernhard Alois Moser, Thomas Grubinger, Edwin Lughofer, Thomas Natschläger, Susanne Saminger-Platz
2017	J	`jnl`	Similarity Recovery From Threshold-Based Sampling Under General Conditions. IEEE Trans. Signal Process. Bernhard Alois Moser
2016	—	`conf`	On preserving metric properties of integrate-and-fire sampling. EBCCSP Bernhard Alois Moser
2015	—	`conf`	Matching event sequences approach based on Weyl's discrepancy norm. EBCCSP Bernhard Alois Moser
2015	—	`conf`	Stability of threshold-based sampling as metric problem. EBCCSP Bernhard Alois Moser
2014	J	`jnl`	On Stability of Distance Measures for Event Sequences Induced by Level-Crossing Sampling. IEEE Trans. Signal Process. Bernhard Alois Moser, Thomas Natschläger
2014	J	`jnl`	The Range of a Simple Random Walk on Z: An Elementary Combinatorial Approach. Electron. J. Comb. Bernhard Alois Moser
2012	J	`jnl`	Geometric Characterization of Weyl's Discrepancy Norm in Terms of Its n-Dimensional Unit Balls. Discret. Comput. Geom. Bernhard Alois Moser