Advanced Analytics and Learning on Temporal Data: 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers: Lecture Notes in Computer Science, cartea 14343
Editat de Georgiana Ifrim, Romain Tavenard, Anthony Bagnall, Patrick Schaefer, Simon Malinowski, Thomas Guyet, Vincent Lemaireen Limba Engleză Paperback – 20 dec 2023
The 20 full papers were carefully reviewed and selected from 28 submissions. They are organized in the following topical section as follows: Machine Learning; Data Mining; Pattern Analysis; Statistics to Share their Challenges and Advances in Temporal Data Analysis.
Din seria Lecture Notes in Computer Science
- 20% Preț: 1061.55 lei
- 20% Preț: 307.71 lei
- 20% Preț: 438.69 lei
- 20% Preț: 645.28 lei
- Preț: 410.88 lei
- 15% Preț: 580.46 lei
- 17% Preț: 427.22 lei
- 20% Preț: 596.46 lei
- Preț: 381.21 lei
- 20% Preț: 353.50 lei
- 20% Preț: 1414.79 lei
- 20% Preț: 309.90 lei
- 20% Preț: 583.40 lei
- 20% Preț: 1075.26 lei
- 20% Preț: 310.26 lei
- 20% Preț: 655.02 lei
- 20% Preț: 580.93 lei
- 20% Preț: 340.32 lei
- 15% Preț: 438.59 lei
- 20% Preț: 591.51 lei
- 20% Preț: 649.49 lei
- 20% Preț: 337.00 lei
- Preț: 449.57 lei
- 20% Preț: 607.39 lei
- 20% Preț: 1024.44 lei
- 20% Preț: 579.30 lei
- 20% Preț: 763.23 lei
- 20% Preț: 453.32 lei
- 20% Preț: 575.48 lei
- 20% Preț: 585.88 lei
- 20% Preț: 825.93 lei
- 20% Preț: 763.23 lei
- 17% Preț: 360.19 lei
- 20% Preț: 1183.14 lei
- 20% Preț: 340.32 lei
- 20% Preț: 504.57 lei
- 20% Preț: 369.12 lei
- 20% Preț: 583.40 lei
- 20% Preț: 343.62 lei
- 20% Preț: 350.21 lei
- 20% Preț: 764.89 lei
- 20% Preț: 583.40 lei
- Preț: 389.48 lei
- 20% Preț: 341.95 lei
- 20% Preț: 238.01 lei
- 20% Preț: 538.29 lei
Preț: 447.57 lei
Preț vechi: 559.46 lei
-20% Nou
Puncte Express: 671
Preț estimativ în valută:
85.65€ • 88.48$ • 71.29£
85.65€ • 88.48$ • 71.29£
Carte tipărită la comandă
Livrare economică 26 martie-09 aprilie
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9783031498954
ISBN-10: 303149895X
Pagini: 308
Ilustrații: XIII, 308 p. 113 illus., 90 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.45 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 303149895X
Pagini: 308
Ilustrații: XIII, 308 p. 113 illus., 90 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.45 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
Cuprins
Human Activity Segmentation Challenge.- Human Activity Segmentation Challenge@ECML/PKDD’23.- Change points detection in multivariate signal applied to human activity segmentation.- Change Point Detection via Synthetic Signals.- Oral Presentation.- Clustering time series with k-medoids based algorithms.- Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting.- RED CoMETS: an ensemble classifier for symbolically represented multivariate time series.- Deep Long Term Prediction for Semantic Segmentation in Autonomous Driving.- Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression.- ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averaging.- Poster Presentation.- Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks.- Evaluating Explanation Methods for Multivariate Time Series
Classification.- tGLAD: A sparse graph recovery based approach for multivariate time series segmentation.- Designing a New Search Space for Multivariate Time-Series Neural Architecture Search.- Back to Basics: A Sanity Check on Modern Time Series Classification Algorithms.- Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Behaviours and Detect Health Issues.- Exploiting Context and Attention with Recurrent Neural Network for Sensor Time Series Prediction.- Rail Crack Propagation Forecasting Using Multi-horizons RNNs.- Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies.- Time-aware Predictions of Moments of Change in Longitudinal User Posts on Social Media.