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Found 8 papers, 1 papers with code
Learnability is a Compact Property
Furthermore, the learnability of such problems can fail to be a property of finite character: informally, it cannot be detected by examining finite projections of the problem.
Stability and Multigroup Fairness in Ranking with Uncertain Predictions
However, when predictors trained for classification tasks have intrinsic uncertainty, it is not obvious how this uncertainty should be represented in the derived rankings.
Regularization and Optimal Multiclass Learning
We demonstrate that an agnostic version of the Hall complexity again characterizes error rates exactly, and exhibit an optimal learner using maximum entropy programs.
Fairness in Matching under Uncertainty
The prevalence and importance of algorithmic two-sided marketplaces has drawn attention to the issue of fairness in such settings.
Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions
Many reinforcement learning (RL) environments in practice feature enormous state spaces that may be described compactly by a "factored" structure, that may be modeled by Factored Markov Decision Processes (FMDPs).
ResiliNet: Failure-Resilient Inference in Distributed Neural Networks
Nevertheless, when a neural network is partitioned and distributed among physical nodes, failure of physical nodes causes the failure of the neural units that are placed on those nodes, which results in a significant performance drop.
Guardians of the Deep Fog: Failure-Resilient DNN Inference from Edge to Cloud
To articulate deepFogGuard, we introduce the elements and a model for the resiliency of distributed DNN inference.
DeepPR: Incremental Recovery for Interdependent VNFs with Deep Reinforcement Learning
The increasing reliance upon cloud services entails more flexible networks that are realized by virtualized network equipment and functions.
Networking and Internet Architecture
