AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is shown that this loop can sustain a lower-return policy even when representation fitting is globally optimal on data selected by the agent, which then uses the resulting returns to guide its next choices.
This work presents an exposition of the OSQ problem by summarizing its various formulations in the current literature and categorizing existing solutions into three different types, and summarizes the empirical methods proposed by existing works to verify the efficiency of OSQ mitigation approaches.
Language generation in the limit asks for valid unseen elements from every exhaustive positive presentation of an unknown infinite language. We characterize this task for arbitrary families over a countable universe. Generation is possible exactly when each target can be assigned a finite positive witness so that the t...
A spherical-cap construction proves the latter claim without assuming sparsity merely on the sampling support without assuming sparsity merely on the sampling support, and obtains agnostic minimax excess-risk bounds of order up to logarithms.
This survey reviews the geometry, learning, and computation of superposed representations, explaining how feature statistics and decoder choice affect the conclusions and compares practical methods for recovering and analyzing features.
We determine exactly what a kurtosis bound buys for one-sided tail control. For the class $\mathcal{C}(\kappa)$ of real random variables with mean $0$, variance $1$, and fourth moment at most $\kappa$, the skewness left free, we compute the worst-case tail probability $V_1(t,\kappa)=\sup_{X\in\mathcal{C}(\kappa)}\mathb...
Worst-case multiclass bounds do not become smaller when the best classifier is already nearly correct: what is missing is an optimistic rate, a guarantee whose fluctuation scales with the oracle risk itself. For a class of Natarajan dimension $d_N$ and Daniely-Shalev-Shwartz dimension $d_{DS}$, the optimal excess risk...
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