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New paper details field codes for empirical optimal transport

A new paper introduces a field-code compiler for empirical optimal transport, addressing communication tasks like distributed coupling sampling. The compiler allows for value-certified samplers with accuracy controlled by a public target-partition diameter, while field error influences residual communication. The research also establishes lower bounds for certified output, demonstrating its inherent difficulty. AI

IMPACT This research contributes to theoretical advancements in optimal transport, potentially impacting future AI systems that rely on efficient data distribution and sampling.

RANK_REASON The cluster contains an academic paper published on arXiv.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New paper details field codes for empirical optimal transport

COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Hung Mai, Hai Nguyen, Luong Doan, Ngoc Vu, Khanh Nguyen, Nhung Duong, Tuan Do ·

    Field Codes for Distributed Coupling Samplers and Certified Empirical Transport

    arXiv:2607.27078v1 Announce Type: cross Abstract: In this paper, we formulate three communication tasks for empirical optimal transport: distributed coupling sampling, cost-evaluable coupling output, and scalar value-certified sampling. Our main result is a field-code compiler: a…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Field Codes for Distributed Coupling Samplers and Certified Empirical Transport

    In this paper, we formulate three communication tasks for empirical optimal transport: distributed coupling sampling, cost-evaluable coupling output, and scalar value-certified sampling. Our main result is a field-code compiler: any communicated transport field approximating an o…