Dynamics of Stochastic Momentum with Sparse Updates in High Dimensions

2026-05-29T07:23:58Ze3e2c76f13d0979aadf75e57bef60715a6754f538d171f2126e7ebd72ef7f261
Anytime-FC-RAGFPLDLLM-swarmsbandwidth-optimizationconformal-predictionconjugate-kerneldiffusion-modelsfederated-RAGfederated-learningmomentum-dynamicsmulti-task-inferenceoptimization-theoryprediction-powered-inferenceprivacyprobe-logit-distillationquantized-communicationrandom-matrix-theoryrobust-sparsificationsample-complexitysparse-updates

What happened

Collection of recent ML/stat arXiv papers (May 29, 2026) covering: (1) dynamics of stochastic momentum under sparse updates in high dimensions; (2) an anytime-valid extension of Federated Conformal RAG (Anytime-FC-RAG) for LLM swarms with sequential guarantees and bandwidth savings; (3) multi-task prediction-powered inference for improved statistical power with scarce labels; (4) deep individualized treatment-rule learning for bivariate survival outcomes; (5) tight rates and optimal per-node bandwidth allocation for federated probe-logit distillation (FPLD) under heterogeneous budgets; (6) RMT

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_stat_ml
Record identifier
e3e2c76f13d0979aadf75e57bef60715a6754f538d171f2126e7ebd72ef7f261
Enrichment time
2026-05-29T07:23:58Z
AI-assisted enrichment
Yes

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