SMiLer: A Semi-Lazy Time Series Prediction System for Sensors
Summary: SMiLer builds query-dependent GPs on small data per prediction for real-time sensor time series, with no training phase. GPU-based two-level inverted index accelerates DTW-kNN for just-in-time GP construction; adaptive auto-tuning personalizes per-series parameters, improving accuracy and uncertainty estimates. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,971 | LazyLSH: Approximate Nearest Neighbor Search for Multiple Distance Functions with a Single Index | 2016 | SIGMOD | 9.893198e-05 |
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