Machine learning and principles and ...
ECML PKDD (Conference) ((2022 :)

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  • 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 /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Machine learning and principles and practice of knowledge discovery in databases/ edited by Irena Koprinska ... [et al.].
    其他題名: International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022 : proceedings.
    其他題名: ECML PKDD 2022
    其他作者: Koprinska, Irena.
    團體作者: ECML PKDD (Conference)
    出版者: Cham :Springer Nature Switzerland : : 2023.,
    面頁冊數: xx, 633 p. :ill. (chiefly color), digital ;24 cm.
    內容註: 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 from the 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.
    Contained By: Springer Nature eBook
    標題: Machine learning - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-23618-1
    ISBN: 9783031236181
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