DenoGrad refines noisy tabular and time-series data by optimizing inputs via gradients from a fixed model, yielding better downstream predictions on ten real-world datasets while preserving data statistics.
Larsen-Ledet, Embracing data noise, in: microsoft, 2023, p
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
DenoGrad: A Gradient-Based Framework for Data Refinement in Tabular and Time-Series Learning
DenoGrad refines noisy tabular and time-series data by optimizing inputs via gradients from a fixed model, yielding better downstream predictions on ten real-world datasets while preserving data statistics.