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David Picard
- ESANN 2021 - Unsupervised Word Representations Learning with Bilinear Convolutional Network on Characters [Details]
- ESANN 2012 - Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm [Details]
- ESANN 2013 - Machine Learning and Content-Based Multimedia Retrieval [Details]
- ESANN 2014 - Dimensionality reduction in decentralized networks by Gossip aggregation of principal components analyzers [Details]
- ESANN 2015 - Asynchronous decentralized convex optimization through short-term gradient averaging [Details]
- ESANN 2021 - Toxicity Detection in Online Comments with Limited Data: A Comparative Analysis [Details]
- ESANN 1996 - A fast Bayesian algorithm for Boolean functions synthesis by means of perceptron networks [Details]
- ESANN 2014 - Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis [Details]
- ESANN 2014 - Machine learning techniques to assess the performance of a gait analysis system [Details]
- ESANN 2016 - On the improvement of static force capacity of humanoid robots based on plants behavior [Details]
- ESANN 2023 - Knowledge Distillation for Anomaly Detection [Details]
- ESANN 2003 - Classification of handwritten digits using supervised locally linear embedding algorithm and support vector machine [Details]
- ESANN 2009 - Kernelizing Vector Quantization Algorithms [Details]
- ESANN 2010 - Online speaker diarization with a size-monitored growing neural gas algorithm [Details]
- ESANN 2011 - Single-trial P300 detection with Kalman filtering and SVMs [Details]
- ESANN 2018 - Latent representations of transient candidates from an astronomical image difference pipeline using Variational Autoencoders [Details]
- ESANN 2021 - Orientation Adaptive Minimal Learning Machine for Directions of Atomic Forces [Details]
- ESANN 2006 - Classification of Boar Sperm Head Images using Learning Vector Quantization [Details]
- ESANN 2015 - Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs [Details]
- ESANN 1994 - Variable binding in a neural network using a distributed representation [Details]
- ESANN 1999 - Mean-field equations reveal synchronization in a 2-populations neural network model [Details]
- ESANN 2023 - Large-scale dataset and benchmarking for hand and face detection focused on sign language [Details]
- ESANN 2023 - A model-based approach to meta-Reinforcement Learning: Transformers and tree search [Details]
- ESANN 2015 - An affinity matrix approach for structure selection of extreme learning machines [Details]
- ESANN 2021 - Slope: A First-order Approach for Measuring Gradient Obfuscation [Details]
- ESANN 2023 - Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization [Details]
- ESANN 2023 - Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness [Details]
- ESANN 2006 - The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks [Details]
- ESANN 2015 - Designing semantic feature spaces for brain-reading [Details]
- ESANN 1996 - Neural versus neurofuzzy systems for credit approval [Details]
- ESANN 2023 - Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization [Details]
- ESANN 2020 - Variational MIxture of Normalizing Flows [Details]
- ESANN 2016 - Multi-task learning for speech recognition: an overview [Details]
- ESANN 2000 - A statistical model selection strategy applied to neural networks [Details]
- ESANN 2002 - A resampling and multiple testing-based procedure for determining the size of a neural network [Details]
- ESANN 2002 - Noise derived information criterion for model selection [Details]
- ESANN 2003 - A new Meta Machine Learning (MML) method based on combining non-significant different neural networks [Details]
- ESANN 2010 - Combining back-propagation and genetic algorithms to train neural networks for start-up time modeling in combined cycle power plants [Details]
- ESANN 2016 - Bag-of-Steps: predicting lower-limb fracture rehabilitation length [Details]
- ESANN 2017 - ELM Preference Learning for Physiological Data [Details]