Machine Learning and Principles and Practice of Knowledge Discovery in Databases International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I
by
 
Koprinska, Irena. editor.

Title
Machine Learning and Principles and Practice of Knowledge Discovery in Databases International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I

Author
Koprinska, Irena. editor.

ISBN
9783031236181

Edition
1st ed. 2023.

Physical Description
XX, 633 p. 228 illus., 200 illus. in color. online resource.

Series
Communications in Computer and Information Science, 1752

Contents
Workshop on Data Science for Social Good (SoGood 2022) -- Preface from the workshop organisers -- Gender Stereotyping Impact on Facial Expression Recognition -- A Social Media Tool for Domain-Specific Information Retrieval - A Case Study in Human Trafficking -- A Unified Framework for Assessing Energy Efficiency of Machine Learning -- Fault Detection in Wastewater Treatment Plants: Application of Autoencoders Models with Streaming Data -- A Temporal Fusion Transformer for Long-term Explainable Prediction of Emergency Department Overcrowding -- Exploitation and Merge of Information Sources for Public Procurement Improvement -- Geovisualisation tools for reporting and monitoring Transthyretin-associated Familial Amyloid Polyneuropathy disease -- Evaluation of Group Fairness Measures in Student Performance Prediction Problems -- Combining Image Enhancement Techniques and Deep Learning for Shallow Water Benthic Marine Litter Detection -- Ethical and Technological AI Risks Classification: A Human vs Machine Approach -- A Reinforcement Learning Algorithm for Fair Electoral Redistricting in Parliamentary Systems -- Study on Correlation Between Vehicle Emissions and Air Quality in Porto -- Intelligently Detecting Information Online-weaponisation Trends (IDIOT) -- Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2022) -- Preface from the workshop organisers -- Multi-Modal Terminology Management: Corpora, Data Models and Implementations in TermSTAR -- Cluster algorithm for social choice -- Sentimental Analysis of COVID-19 Vaccine Tweets using BERT+NBSVM -- Rules, subgroups and redescriptions as features in classification tasks -- Bitpaths: compressing datasets without decreasing predictive performance -- Anomaly Detection for Physical Threat Intelligence -- Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2022) -- Preface fromthe workshop organisers -- Is Attention Interpretation? A Quantitative Assessment on Sets -- From Disentangled Representation to Concept Ranking: Interpreting Deep Representations in Image Classification tasks -- RangeGrad: Explaining Neural Networks by Measuring Uncertainty through Bound Propagation -- An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making -- Local Multi-Label Explanations for Random Forest -- Interpretable and Reliable Rule Classification based on Conformal Prediction -- Measuring the Burden of (Un)fairness Using Counterfactuals -- Are SHAP values biased towards high-entropy features? -- Simple explanations to summarise Subgroup Discovery outcomes: a case study concerning patient phenotyping -- Limits of XAI task performance evaluation: an e-sport prediction example -- Improving the quality of rule-based GNN explanations -- Exposing Racial Dialect Bias in Abusive Language Detection: Can Explainability Play a Role? -- On the Granularity of Explanations in Model Agnostic NLP Interpretability -- Workshop on Uplift Modeling (UMOD 2022) -- Preface from the workshop organisers -- Estimating the impact of coupon non-usage -- Shrinkage estimators for uplift regression -- Workshop on IoT, Edge and Mobile for Embedded Machine Learning (ITEM 2022) -- Preface from the workshop organisers -- Hierarchical Design Space Exploration for Distributed CNN Inference at the Edge -- Automated Search for Deep Neural Network Inference Partitioning on Embedded FPGA -- Framework to Evaluate Deep Learning Algorithms for Edge Inference and Training -- Hardware Execution Time Prediction for Neural Network Layers -- Enhancing Energy-efficiency by Solving the Throughput Bottleneck of LSTM Cells for Embedded FPGAs -- Accelerating RNN-based Speech Enhancement on a Multi-Core MCU with Mixed FP16-INT8 Post-Training Quantization -- LDRNet: Enabling Real-time Document Localization on Mobile Devices.

Added Author
Koprinska, Irena.
 
Mignone, Paolo.
 
Guidotti, Riccardo.
 
Jaroszewicz, Szymon.
 
Fröning, Holger.
 
Gullo, Francesco.
 
Ferreira, Pedro M.
 
Roqueiro, Damian.
 
Ceddia, Gaia.
 
Nowaczyk, Slawomir.
 
Gama, João.
 
Ribeiro, Rita.
 
Gavaldà, Ricard.
 
Masciari, Elio.
 
Ras, Zbigniew.
 
Ritacco, Ettore.
 
Naretto, Francesca.
 
Theissler, Andreas.
 
Biecek, Przemyslaw.
 
Verbeke, Wouter.
 
Schiele, Gregor.
 
Pernkopf, Franz.
 
Blott, Michaela.
 
Bordino, Ilaria.
 
Danesi, Ivan Luciano.
 
Ponti, Giovanni.
 
Severini, Lorenzo.
 
Appice, Annalisa.
 
Andresini, Giuseppina.
 
Medeiros, Ibéria.
 
Graça, Guilherme.
 
Cooper, Lee.
 
Ghazaleh, Naghmeh.
 
Richiardi, Jonas.
 
Saldana, Diego.
 
Sechidis, Konstantinos.
 
Canakoglu, Arif.
 
Pido, Sara.
 
Pinoli, Pietro.
 
Bifet, Albert.
 
Pashami, Sepideh.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
https://doi.org/10.1007/978-3-031-23618-1


LibraryMaterial TypeItem BarcodeShelf Number[[missing key: search.ChildField.HOLDING]]Status
Online LibraryE-Book520754-1001XX(520754.1)Elektronik Kütüphane