Polynomial Stein discrepancies (PSD) provide a scalable alternative to kernel Stein methods for measuring sample quality and goodness-of-fit testing, but their statistical properties remain poorly understood. We show that increasing polynomial degree primarily amplifies signal without adequately controlling variance, rather than directly optimising the signal-to-noise ratio (SNR). Under suitable assumptions, this might lead to a failure mode in which the $\text{SNR}^2$ can provably decay exponentially with polynomial degree. Motivated by this observation, we reformulate Stein discrepancy construction as an explicit $\text{SNR}^2$ maximisation problem, yielding a Rayleigh quotient over Stein features. This perspective motivates $λ$-PSD, an approximate scalable covariance-aware reweighting scheme defined in a low-dimensional subspace. Under Gaussian settings, we show that $λ$-PSD avoids the exponential $\text{SNR}^2$ collapse and achieves a stable $\text{SNR}^2$. Empirically, $λ$-PSD substantially improves test power while retaining linear-time complexity in the number of samples, highlighting the importance of SNR-aware design for scalable Stein discrepancies.

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Rep. Pat Harrigan is leading a bill to phase out Chinese-manufactured drones from U.S. law enforcement, citing national security concerns tied to the Chinese Communist Party.

Is the war entering a new phase? At least five people have been killed in a Ukrainian attack on Russia and the Crimean peninsula as Kyiv steps up strikes, according to the Russian-appointed governor in the annexed region. Crimea Governor Sergey Aksyonov said two people, including a child, were killed and two others wounded following "overnight enemy attacks" into Thursday. Russia's defence ministry said 269 Ukrainian drones were downed over Russia and Crimea overnight. The head of the Krasnoarmeysk district in Krasnodar Krai said debris from a drone strike triggered an oil depot fire.

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Missouri State University trained over 1,500 Chinese executives tied to China's military-industrial complex through an MBA program, a new watchdog report claims.

U.S. defense firm Anduril in talks for Nissan plant to build drones in Japan, sources say U.S. defense firm Anduril Industries is in talks to acquire the plant to build military drones in Japan, sources say. U.S. defense firm Anduril Industries is in talks to acquire Nissan Motor's Oppama assembly plant near Tokyo as the maker of autonomous weapons looks to build military drones in Japan, according to three sources familiar with the matter. While they say no decision has been made, any deal could transform one of Japan's first large-scale postwar car factories, long a symbol of its industrial revival, into an arms-making hub. The talks over Oppama, which are being reported for the first time, come as Prime Minister Sanae Takaichi's government seeks to expand defense manufacturing amid growing concern that a Taiwan Strait crisis could draw in Japan and run down weapons stocks. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.