Vroom optimizes in unpredictable conditions without derivatives.
arXiv research
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New methods improve estimation accuracy in noisy settings.
While recent continual learning methods largely alleviate the catastrophic problem on toy-sized datasets, some issues remain to be tackled to apply them to real-world problem domains. First, a continual learning model should effectively handle catastrophic forgetting and be efficient to train even with a large number o…
Unified framework improves PCA for outliers and distributed data.
C-kNN-LSH identifies similar patient histories for causal inference in longitudinal data.
SOR-Mamba improves Mamba for robust time series forecasting by minimizing channel order bias.