Tootfinder

From Tea Leaves to System Maps: Context-awareness in Monitoring Operational Machine Learning Models
Joran Leest, Claudia Raibulet, Patricia Lago, Ilias Gerostathopoulos
https://arxiv.org/abs/2506.10770

From Tea Leaves to System Maps: Context-awareness in Monitoring Operational Machine Learning Models
Machine learning (ML) models in production do not fail due to statistical anomalies in their input data; they fail due to contextual misalignment -- when their environment deviates from training assumptions, leading to unreliable predictions. Effective ML monitoring requires rich contextual information to move beyond detecting statistical shifts toward meaningful alerts and systematic root-cause analysis. Yet, surprisingly, despite extensive research in ML monitoring and related disciplines (dr…

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https://kinggizzard.bandcamp.com/track/lonely-cosmos
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On novel Hamiltonian description of the nonholonomic Suslov problem
A. V. Tsiganov
https://arxiv.org/abs/2505.19594 https://arxiv.org…

On novel Hamiltonian description of the nonholonomic Suslov problem
We present some new Poisson bivectors that are invariants by the flow of the nonholonomic Suslov problem. Two rank four invariant Poisson bivectors have globally defined Casimir functions and, therefore, define cubic Poisson brackets on the five dimensional state space with standard symplectic leaves. For the Suslov gyrostat in the potential field we found rank two Poisson bivectors having only two globally defined Casimir functions and, therefore, we say about formal Hamiltonian description in…