Database Paper Browser

Back to papers

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)

Paper ID
5046
Venue
SIGMOD
Year
2015
Pagerank
4.1945683e-05
Overall Rank
11,921 | 17.07%
DOI
10.1145/2723372.2749429

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

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
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers