99 citations · 522 across the 74 of their papers we have counts for
16 papers · 1 filter
MS-Index: Fast Top-k Subsequence Search for Multivariate Time Series under Euclidean Distance
Jens E. d'Hondt, Teun Kortekaas, Odysseas Papapetrou +1
Modern applications frequently collect and analyze temporal data in the form of multivariate time series (MTS) -- time series that contain multiple channels. A common task in this…
MSAD: A Deep Dive into Model Selection for Time series Anomaly Detection
Emmanouil Sylligardos, John Paparrizos, Themis Palpanas +2
Anomaly detection is a fundamental task for time series analytics with important implications for the downstream performance of many applications. Despite increasing academic inter…
Toward Efficient and Scalable Design of In-Memory Graph-Based Vector Search
Ilias Azizi, Karima Echihab, Themis Palpanas +1
Vector data is prevalent across business and scientific applications, and its popularity is growing with the proliferation of learned embeddings. Vector data collections often reac…
CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data
Shifeng Xie, Vasilii Feofanov, Ambroise Odonnat +7
Time series foundation models (TSFMs) have recently gained significant attention due to their strong zero-shot capabilities and widespread real-world applications. Such models typi…
TiVy: Time Series Visual Summary for Scalable Visualization
Gromit Yeuk-Yin Chan, Luis Gustavo Nonato, Themis Palpanas +2
Visualizing multiple time series presents fundamental tradeoffs between scalability and visual clarity. Time series capture the behavior of many large-scale real-world processes, f…
DeviceScope: An Interactive App to Detect and Localize Appliance Patterns in Electricity Consumption Time Series
Adrien Petralia, Paul Boniol, Philippe Charpentier +1
In recent years, electricity suppliers have installed millions of smart meters worldwide to improve the management of the smart grid system. These meters collect a large amount of…
Few Labels are all you need: A Weakly Supervised Framework for Appliance Localization in Smart-Meter Series
Adrien Petralia, Paul Boniol, Philippe Charpentier +1
Improving smart grid system management is crucial in the fight against climate change, and enabling consumers to play an active role in this effort is a significant challenge for e…
NILMFormer: Non-Intrusive Load Monitoring that Accounts for Non-Stationarity
Adrien Petralia, Philippe Charpentier, Youssef Kadhi +1
Millions of smart meters have been deployed worldwide, collecting the total power consumed by individual households. Based on these data, electricity suppliers offer their clients…
LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning
Xiaotian Lin, Yanlin Qi, Yizhang Zhu +4
Instruction tuning has emerged as a critical paradigm for improving the capabilities and alignment of large language models (LLMs). However, existing iterative model-aware data sel…
DARTH: Declarative Recall Through Early Termination for Approximate Nearest Neighbor Search
Manos Chatzakis, Yannis Papakonstantinou, Themis Palpanas
Approximate Nearest Neighbor Search (ANNS) presents an inherent tradeoff between performance and recall (i.e., result quality). Each ANNS algorithm provides its own algorithm-depen…
Graphint: Graph-based Time Series Clustering Visualisation Tool
Paul Boniol, Donato Tiano, Angela Bonifati +1
With the exponential growth of time series data across diverse domains, there is a pressing need for effective analysis tools. Time series clustering is important for identifying p…
VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection
Paul Boniol, Ashwin K. Krishna, Marine Bruel +7
Anomaly detection (AD) is a fundamental task for time-series analytics with important implications for the downstream performance of many applications. In contrast to other domains…
-Graph: A Graph Embedding for Interpretable Time Series Clustering
Paul Boniol, Donato Tiano, Angela Bonifati +1
Time series clustering poses a significant challenge with diverse applications across domains. A prominent drawback of existing solutions lies in their limited interpretability, of…
Automated Data Quality Validation in an End-to-End GNN Framework
Sijie Dong, Soror Sahri, Themis Palpanas +1
Ensuring data quality is crucial in modern data ecosystems, especially for training or testing datasets in machine learning. Existing validation approaches rely on computing data q…
LeaFi: Data Series Indexes on Steroids with Learned Filters
Qitong Wang, Ioana Ileana, Themis Palpanas
The ever-growing collections of data series create a pressing need for efficient similarity search, which serves as the backbone for various analytics pipelines. Recent studies hav…
Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art
Ilias Azizi, Karima Echihabi, Themis Palpanas
Vector data is prevalent across business and scientific applications, and its popularity is growing with the proliferation of learned embeddings. Vector data collections often reac…