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pro vyhledávání: '"Marzouk, Reda"'
Autor:
Marzouk, Reda, de La Higuera, Colin
Thanks to its solid theoretical foundation, the SHAP framework is arguably one the most widely utilized frameworks for local explainability of ML models. Despite its popularity, its exact computation is known to be very challenging, proven to be NP-H
Externí odkaz:
http://arxiv.org/abs/2405.02936
Autor:
Marzouk, Reda, de La Higuera, Colin
The primary use of any probabilistic model involving a set of random variables is to run inference and sampling queries on it. Inference queries in classical probabilistic models is concerned by the computation of marginal or conditional probabilitie
Externí odkaz:
http://arxiv.org/abs/2206.12862
Autor:
Marzouk, Reda
This work aims at shedding some light on connections between finite state machines (FSMs), and recurrent neural networks (RNNs). Examined connections in this master's thesis is threefold: the extractability of finite state machines from recurrent neu
Externí odkaz:
http://arxiv.org/abs/2009.06398
Autor:
Marzouk, Reda, de la Higuera, Colin
The need of interpreting Deep Learning (DL) models has led, during the past years, to a proliferation of works concerned by this issue. Among strategies which aim at shedding some light on how information is represented internally in DL models, one c
Externí odkaz:
http://arxiv.org/abs/2004.00478