Training ideas

Curricula, sampling schedules, pseudo-labeling and multi-task mixing, with the standard training recipe as the control.

2 ideas found

Status: Beats tuned baseline Category: Training Math: Linear algebra Clear all

✓✓ Beats tuned baseline 2026

Constructive Two-View Gauge Initialization

Initialize latent coordinate-frame parameters analytically from two temporally separated neural predictions instead of starting joint optimization from arbitrary translation and orientation. This removes the continuous gauge before backpropagation and should prevent EKF-like or gradient-based failures caused by large yaw and position initialization errors.

Useful7/10

Difficulty4/10

Novelty8/10

Training Stability Speed Accuracy

Paper: Trajectory-Induced Self-Calibration for Hidden-Target Localization Through an Unknown-Pose Range-Bearing Relay arXiv:2608.09464

✓✓ Beats tuned baseline 2026

Laplacian-Coherence Graph Minibatches

Replace uniform node minibatches in a GNN with a coreset selected from a small random candidate set using local Laplacian-column coherence. Select nodes whose connectivity signatures are least redundant with already selected nodes, while retaining inverse-probability weights for unbiased loss estimates. This should improve coverage of weakly connected graph clusters and preserve smooth graph signals at the same batch size.

Useful7/10

Difficulty5/10

Novelty7/10

Training Sample efficiency Scalability Accuracy

Paper: Scalable Graph Coreset Selection via Greedy Sampling arXiv:2607.27602