Search Results - "Deep Learning"

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    Advances in Intelligent Data Analysis XVIII 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27-29, 2020, Proceedings /

    Published 2020
    Table of Contents: “…Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder -- Dual Sequential Variational Autoencoders for Fraud Detection -- A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks -- Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams -- GraphMDL: Graph Pattern Selection Based on Minimum Description Length -- Towards Content Sensitivity Analysis -- Gibbs Sampling Subjectively Interesting Tiles -- Even Faster Exact k-Means Clustering -- Ising-Based Consensus Clustering on Special Purpose Hardware -- Transfer Learning by Learning Projections from Target to Source -- Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs -- Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces -- Vouw: Geometric Pattern Mining Using the MDL Principle -- A Consensus Approach to Improve NMF Document Clustering -- Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams -- Widening for MDL-Based Retail Signature Discovery -- Addressing the Resolution Limit and the Field of View Limit in Community Mining -- Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics -- Adversarial Attacks Hidden in Plain Sight -- Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code -- Overlapping Hierarchical Clustering (OHC) -- Digital Footprints of International Migration on Twitter -- Percolation-Based Detection of Anomalous Subgraphs in Complex Networks -- A Late-Fusion Approach to Community Detection in Attributed Networks -- Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction -- A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization -- Actionable Subgroup Discovery and Urban Farm Optimization -- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model -- Detection ofDerivative Discontinuities in Observational Data -- Improving Prediction with Causal Probabilistic Variables -- DO-U-Net for Segmentation and Counting -- Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media -- Event Recognition Based on Classification of Generated Image Captions -- Human-to-AI Coach: Improving Human Inputs to AI Systems -- Aleatoric and Epistemic Uncertainty with Random Forests -- Master your Metrics with Calibration -- Supervised Phrase-Boundary Embeddings -- Predicting Remaining Useful Life with Similarity-Based Priors -- Orometric Methods in Bounded Metric Data -- Interpretable Neuron Structuring with Graph Spectral Regularization -- Comparing the Preservation of Network Properties by Graph Embeddings -- Making Learners (More) Monotone -- Combining Machine Learning and Simulation to a Hybrid Modelling Approach -- LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification -- Angle-Based Crowding Degree Estimation for Many-Objective Optimization.…”
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    Foundations of Robotics A Multidisciplinary Approach with Python and ROS /

    Published 2022
    Table of Contents: “…Multi-robot systems: bio-inspired concepts and deployment challenges (Vivek Shankar Varadharajan and Giovanni Beltrame) -- Chapter 12 - The Embedded design process: CAD/CAM and prototyping (Eddi Pianca) -- PART III: Interaction Design -- Chapter 13 - Social robots: Principles of interaction design and user studies (Janie Busby Grant & Damith Herath) -- Chapter 14 - Safety first: On the safe deployment of robotic systems (Bruno Belzile and David St-Onge) -- Chapter 15 - Managing the world complexity: from linear regression to deep learning (Yann Bouteiller) -- Chapter 16 - Robot ethics: Ethical design considerations (Dylan Cawthorne) -- Chapter 17 - Robot Hexapod Build Labs (David Hinwood and Damith Herath) -- Chapter 18 - ROS Mobile Manipulator labs (David St-Onge, Corentin Boucher and Bruno Belzile).…”
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    Stochastic Transport in Upper Ocean Dynamics STUOD 2021 Workshop, London, UK, September 20-23 /

    Published 2023
    Table of Contents: “…Lang) -- Stochastic parameterization withdynamic mode decomposition (L. Li) -- Deep Learning for the Benes Filter (A. Lobbe). End-to-End Kalman Filter in a High Dimensional Linear Embedding of the Observations (S. …”
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