Abstract. Robust probabilistic inference is an extension of prob- abilistic inference, where some of the observations are adversarially corrupted.
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Dec 22, 2014 · Robust probabilistic inference is an extension of probabilistic inference, where some of the observations are adversarially corrupted.
Mar 17, 2023 · The proposed approach finds applications in a wide variety of robust inference problems, where we intend to perform inference on the parameters ...
Proposal: use combinatorial reasoning/optimization techniques. (logic, verification, synthesis) for probabilistic reasoning tasks (machine learning).
Feb 2, 2024 · We propose a Bayesian approach-dubbed robust inverse graphics (RIG)-that relies on a strong scene prior and an uninformative uniform corruption prior.
We study the impact on the performance (accuracy) and execution cost of four factors: (1) Inference Algorithms, (2) Noise Models and. Noise Levels, (3) Model ...
Abstract. Probabilistic inference problems arise naturally in distributed systems such as sensor networks and teams of mobile robots.
Robust probabilistic inference is an extension of probabilistic inference, where some of the observations are adversarially corrupted.
Duration: 1:00:35
Posted: Aug 29, 2014
Posted: Aug 29, 2014
Robust probabilistic inference is an extension of probabilistic inference ... Robust Probabilistic Inference. @inproceedings{Mansour2014RobustPI, title ...