Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- posterJuly 2024
Insightful Simplicity: Dissimilarity in Time Series Anomaly Detection
ACM-TURC '24: Proceedings of the ACM Turing Award Celebration Conference - China 2024Pages 242–243https://doi.org/10.1145/3674399.3674486Time series anomaly detection is a complex task, often hindered by the limitations of existing deep learning methods in capturing temporal contexts and accurately representing normal patterns, which impacts the effectiveness of anomaly detection. To ...
- research-articleJune 2024
Multivariate Time Series Forecasting: A Review
CVIPPR '24: Proceedings of the 2024 2nd Asia Conference on Computer Vision, Image Processing and Pattern RecognitionArticle No.: 58, Pages 1–9https://doi.org/10.1145/3663976.3664241Multivariate time series forecasting is a critical task with applications across various domains, including finance, energy demand, and climate modeling. This review paper, provides a comprehensive overview of methodologies and advancements in ...
- research-articleJanuary 2023
Indonesian Stock Prices Prediction using Bidirectional Long Short-Term Memory
SIET '22: Proceedings of the 7th International Conference on Sustainable Information Engineering and TechnologyPages 188–198https://doi.org/10.1145/3568231.3568249This paper aims to know how well Bidirectional Long Short-Term Memory (BiLSTM) is in predicting Indonesian stock prices. First, the best hyperparameter of BiLSTM is searched through hyperparameter tuning. After finding the best hyperparameter, we train ...
- research-articleApril 2022
The Pattern is in the Details: An Evaluation of Interaction Techniques for Locating, Searching, and Contextualizing Details in Multivariate Matrix Visualizations
CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing SystemsArticle No.: 84, Pages 1–15https://doi.org/10.1145/3491102.3517673Matrix visualizations are widely used to display large-scale network, tabular, set, or sequential data. They typically only encode a single value per cell, e.g., through color. However, this can greatly limit the visualizations’ utility when exploring ...
- research-articleDecember 2020
Evaluation of multivariate transductive neuro-fuzzy inference system for multivariate time-series analysis and modelling
SIET '20: Proceedings of the 5th International Conference on Sustainable Information Engineering and TechnologyPages 45–50https://doi.org/10.1145/3427423.3427428Multivariate Transductive Neuro-Fuzzy Inference System model, named the mTNFI is a previously proposed conceptual transductive approach designed for analysis and modelling of multivariate time-series data. In this study, we revisit, implement and ...
- surveyMay 2018
A Survey on Multidimensional Scaling
ACM Computing Surveys (CSUR), Volume 51, Issue 3Article No.: 47, Pages 1–25https://doi.org/10.1145/3178155This survey presents multidimensional scaling (MDS) methods and their applications in real world. MDS is an exploratory and multivariate data analysis technique becoming more and more popular. MDS is one of the multivariate data analysis techniques, ...
- research-articleMarch 2018
Novel meshes for multivariate interpolation and approximation
- Thomas C. H. Lux,
- Layne T. Watson,
- Tyler H. Chang,
- Jon Bernard,
- Bo Li,
- Xiaodong Yu,
- Li Xu,
- Godmar Back,
- Ali R. Butt,
- Kirk W. Cameron,
- Danfeng Yao,
- Yili Hong
ACMSE '18: Proceedings of the 2018 ACM Southeast ConferenceArticle No.: 13, Pages 1–7https://doi.org/10.1145/3190645.3190687A rapid increase in the quantity of data available is allowing all fields of science to generate more accurate models of multivariate phenomena. Regression and interpolation become challenging when the dimension of data is large, especially while ...
- research-articleOctober 2017
PCA-based multivariate anomaly detection in mobile healthcare applications
DS-RT '17: Proceedings of the 21st International Symposium on Distributed Simulation and Real Time ApplicationsPages 172–179Real time mobile Health applications highly depend on sensor readings to provide high-quality health services. However, real-time sensor readings may be inaccurate and cause abnormal physiological measurements due to internal and external factors. Thus, ...
- posterNovember 2010
An animated multivariate visualization for physiological and clinical data in the ICU
IHI '10: Proceedings of the 1st ACM International Health Informatics SymposiumPages 771–779https://doi.org/10.1145/1882992.1883109Current visualizations of electronic medical data in the Intensive Care Unit (ICU) consist of stacked univariate plots of variables over time and a tabular display of the current numeric values for the corresponding variables and occasionally an alarm ...
- ArticleNovember 1999
Dimensional anchors: a graphic primitive for multidimensional multivariate information visualizations
NPIVM '99: Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation conference on Information and knowledge managementPages 9–16https://doi.org/10.1145/331770.331775We introduce a graphic primitive, called a dimensional anchor (DA), which facilitates the creation of new visualizations and provides insight into the analysis of information visualizations. The DA represents an attempt to provide a unified framework or ...
- articleDecember 1994
Evaluation and approximate evaluation of the multivariate Bernstein-Bézier form on a regularly partitioned simplex
ACM Transactions on Mathematical Software (TOMS), Volume 20, Issue 4Pages 460–480https://doi.org/10.1145/198429.198434Polynomials of the total degree d in m variables have a geometrically intuitive representation in the Bernstein-Be´zier form defined over an m-dimensional simplex. The two algorithms given in this article evaluate the Bernstein-Be´zier form on a large ...