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Publication search results
found 2,703 matches
- 2023
- Mohit Kumar, Bernhard Moser, Lukas Fischer:
Secure Federated Learning with Kernel Affine Hull Machines. ESANN 2023 - Oliver Kramer:
Enhancing Evolution Strategies with Evolution Path Bias. ESANN 2023 - Oliver Kramer, Jill Baumann:
Wind Power Prediction with ETSformer. ESANN 2023 - Denis Martins, Christian Lülf, Fabian Gieseke:
End-to-End Neural Network Training for Hyperbox-Based Classification. ESANN 2023 - Sophie Adama, Martin Bogdan:
Sleep analysis in a CLIS patient using soft-clustering: a case study. ESANN 2023 - Tameem Adel:
Probabilistic Adaptation for Meta-Learning. ESANN 2023 - Alexandra-Ioana Albu:
Temporal Ensembling-based Deep k-Nearest Neighbours for Learning with Noisy Labels. ESANN 2023 - Mohammed Aldosari, John A. Miller:
On Transformer Autoregressive Decoding for Multivariate Time Series Forecasting. ESANN 2023 - Leonardo Amato, Marta Maschietto, Alessandro Leparulo, Mattia Tambaro, Stefano Vassanelli, Alessandro Sperduti:
Real-time Detection of Evoked Potentials by Deep Learning: a Case Study. ESANN 2023 - Kodjo Mawuena Amekoe, Mohamed Djallel Dilmi, Hanene Azzag, Zaineb Chelly Dagdia, Mustapha Lebbah, Gregoire Jaffre:
TabSRA: An Attention based Self-Explainable Model for Tabular Learning. ESANN 2023 - Otmane Amel, Sédrick Stassin, Sidi Ahmed Mahmoudi, Xavier Siebert:
Multimodal Approach for Harmonized System Code Prediction. ESANN 2023 - Daniel Nowak Assis:
Learning with Boosting Decision Stumps for Feature Selection in Evolving Data Streams. ESANN 2023 - Davide Bacciu, Federico Errica, Alessio Micheli, Nicolò Navarin, Luca Pasa, Marco Podda, Daniele Zambon:
Graph Representation Learning. ESANN 2023 - Nermeen Abou Baker, Uwe Handmann:
Don't waste SAM. ESANN 2023 - Mehrdad Mohannazadeh Bakhtiari, Daniel Staps, Thomas Villmann:
Learning Vector Quantization in Context of Information Bottleneck Theory. ESANN 2023 - Ana Maria Barragán-Montero, Robin Tilman, Margerie Huet-Dastarac, John A. Lee:
Single-pass uncertainty estimation with layer ensembling for regression: application to proton therapy dose prediction for head and neck cancer. ESANN 2023 - Alessandro Berti:
Logarithmic Quantum Forking. ESANN 2023 - Karan Bhanot, Dennis Wei, Ioana Baldini, Kristin P. Bennett:
Adversarial Auditing of Machine Learning Models under Compound Shift. ESANN 2023 - Michael Biehl, Sofie Lövdal:
Improved Interpretation of Feature Relevances: Iterated Relevance Matrix Analysis (IRMA). ESANN 2023 - Jérémie Bogaert, Emmanuel Jean, Cyril de Bodt, François-Xavier Standaert:
Fine-tuning is not (always) overfitting artifacts. ESANN 2023 - Martin Bogdan:
Is Boredom an Indicator on the way to Singularity of Artificial Intelligence? Hypotheses as Thought-Provoking Impulse. ESANN 2023 - Verónica Bolón-Canedo, Laura Morán-Fernández, Brais Cancela, Amparo Alonso-Betanzos:
Green Machine Learning. ESANN 2023 - Tanguy Bosser, Souhaib Ben Taieb:
Revisiting the Mark Conditional Independence Assumption in Neural Marked Temporal Point Processes. ESANN 2023 - Henda Boudegga, Yaroub Elloumi, Asma Ben Abdallah, Rostom Kachouri, Mouhamed Hédi Bedoui:
Retinal blood vessel segmentation from high resolution fundus image using deep learning architecture. ESANN 2023 - Alvaro Leandro Cavalcante Carneiro, Denis Henrique Pinheiro Salvadeo, Lucas de Brito Silva:
Large-scale dataset and benchmarking for hand and face detection focused on sign language. ESANN 2023 - Valerio De Caro, Antonio Di Mauro, Davide Bacciu, Claudio Gallicchio:
Communication-Efficient Ridge Regression in Federated Echo State Networks. ESANN 2023 - Andrea Ceni, Davide Bacciu, Valerio De Caro, Claudio Gallicchio, Luca Oneto:
Improving Fairness via Intrinsic Plasticity in Echo State Networks. ESANN 2023 - Xi Chen, Giacomo Anerdi, Daniel Stanley Tan, Stefano Bromuri:
Language Modeling in Logistics: Customer Calling Prediction. ESANN 2023 - Gianluca Coda, Massimo De Gregorio, Antonio Sorgente, Paolo Vanacore:
Improving the DRASiW performance by exploiting its own "Mental Images". ESANN 2023 - Louis Le Coeur, Nick Riedman, Saarthak Sarup, Kwabena Boahen:
Energy-efficient detection of a spike sequence. ESANN 2023
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