ML: Sample efficiency

Machine-learning ideas tagged Sample efficiency in the ML taxonomy of the Math2NN corpus.

2 ideas found

ML: Sample efficiency Math: Statistics Clear all

✗ Failed on benchmark 2026

ZCA In-Context Output Transport

Train a neural surrogate to predict outputs in a source-domain ZCA-whitened space, then adapt to a shifted domain using only the shifted domain's output mean and covariance. At inference, transport the network prediction through the target covariance square root, yielding a weight-free correction that preserves output-coordinate semantics and can be applied to MLP, CNN, graph-NN, or transformer regressors.

Useful7/10

Difficulty4/10

Novelty5/10

Architecture Accuracy Sample efficiency Stability

Paper: Gradient-Free Topology Adaptation for Power Flow Surrogates via In-Context Whitening arXiv:2607.12241

△ Mechanism confirmed, baseline not beaten 2026

Resolution-aware operator data budget

Couple the number of operator training pairs to the output resolution instead of increasing the output grid independently. Refine the output discretization only while the oracle reconstruction improves, and increase the training set when the learned predictor remains substantially worse than the oracle decoder.

Useful6/10

Difficulty4/10

Novelty7/10

Training Scalability Sample efficiency Neural operator

Paper: Kernel-based Operator Learning: Error Analysis, Budget Allocation, and a Physics-Informed Extension arXiv:2607.06287