4 papers · 1 filter
When Does Retrieval Help Time-Series Forecasting?
Mert Onur Cakiroglu, Elham Buxton, Mehmet Dalkilic +1
Retrieval plug-ins supply a deep forecaster with information its lookback window cannot carry. Published evaluations report consistent gains, and each credits its own mechanism. We…
The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting
Mert Onur Cakiroglu, Mehmet Dalkilic, Hasan Kurban
A growing family of indices scores how predictable a series is from its spectrum. Practitioners increasingly read these scores as answering a different question: whether \emph{addi…
Geometric-k-means: A Bound Free Approach to Fast and Eco-Friendly k-means
Parichit Sharma, Marcin Stanislaw, Hasan Kurban +2
This paper introduces Geometric-k-means (or Gk-means for short), a novel approach that significantly enhances the efficiency and energy economy of the widely utilized k-means algor…
Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting
Mert Onur Cakiroglu, Idil Bilge Altun, Mehmet Dalkilic +2
Time series forecasting remains a challenging task for foundation models due to temporal heterogeneity, high dimensionality, and the lack of inherent symbolic structure. In this wo…