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Research map / Learning theory and algorithms / Matrix and tensor methods

Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition

ICML 2020 · Learning theory and algorithms › Matrix and tensor methods · approach: Randomized tensor decomposition algorithms · 6 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
adaptive sketching rate selection via multiplicative weights (CPD-MWU) instead of static sketching rateproximally/Tikhonov regularized sketched CPD-ALS · Noisy synthetic tensorruntime (s): 214.51 -> 185.67 sHelped
adaptive sketching rate selection (CPD-MWU) vs static sketchingsketched CPD-ALS · Noisy synthetic tensorresidual error ε: 0.3808 vs 0.3808No clear effect
adaptive sketching rate selection (CPD-MWU) vs static sketchingsketched CPD-ALS with proximal regularization · Ill-conditioned synthetic tensor, 10-minute budgetresidual error ε: 0.0149 -> 0.0030Helped
adaptive sketching rate selection (CPD-MWU) vs static sketchingsketched CPD-ALS · Park bench video, rank 250runtime (s): 527.98 -> 465.83 sHelped
adaptive sketching rate selection (CPD-MWU) vs static sketchingsketched CPD-ALS · NELL knowledge base, 30-minute limitresidual error ε: CPRAND-MIX 0.072 and SPALS 0.104 vs CPD-MWU+MIX 0.058Helped
static sketching rates (CPRAND-MIX, SPALS) run for two hours instead of 30 minutes (ablation)static sketched CPD-ALS baselines · NELL knowledge baseresidual error ε: CPRAND-MIX 0.072 -> 0.066; SPALS 0.104 -> 0.098; neither reaches target 0.060No clear effect
adaptive sketching rate selection (CPD-MWU + MIX) vs CPD-ALS + MIXCPD-ALS with pre-mixed tensor · NELL knowledge base, target error 0.060runtime (s): 1044.75 -> 354.55 sHelped
number of candidate sketching rates N increased from 5/10 to 50-1000 (ablation)CPD-MWU · Ill-conditioned synthetic tensorresidual error ε over time: N=5 and 10 perform similarly and significantly outperform larger NHurt
proximal regularization (λ) vs Tikhonov in sketched CPD-ALSsketched CPD-ALS · Synthetic tensorsconvergenceNo clear effect

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