#distribution-estimation News & Analysis

3 articles tagged with #distribution-estimation. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · Jun 85/10

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A Temporal Spatial Minimax Rate for Smoothly-Varying Distributions in Wasserstein Space

A new mathematical framework establishes minimax rates for predicting future probability distributions in Wasserstein space based on noisy observations of smoothly-varying curves. The research provides both lower bounds and conditional upper bounds for distribution estimation, revealing how prediction accuracy degrades with dimensionality and unobserved future time horizons.

AINeutralarXiv – CS AI · Jun 16/10

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Improved Distribution Estimation in $\ell_\infty$

Researchers present improved theoretical bounds for estimating discrete probability distributions under the ℓ∞ norm, resolving open questions from prior work by Kontorovich and Painsky. The work provides both minimax bounds in expectation and high-probability tail bounds, with a fully empirical version of the tightest risk bound and identification of worst-case extremal distributions.

AINeutralarXiv – CS AI · May 276/10

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How to Square Tensor Networks and Circuits Without Squaring Them

Researchers have developed new parameterization methods for squared tensor networks and circuits that eliminate computational overhead in marginalization and partition function calculations. By leveraging unitary matrix parameterizations inspired by orthogonality and determinism principles, the approach maintains expressiveness while enabling more efficient machine learning applications without the traditional squaring operation complexity.