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Class Machine Unlearning for Complex Data via Concepts Inference and Data Poisoning
In this paper, to accurately defining the unlearning class of complex data, we apply the definition of Concept, rather than an image feature or a token of text data, to represent the semantic information of unlearning class.
GANDSE: Generative Adversarial Network based Design Space Exploration for Neural Network Accelerator Design
To improve the design quality while saving the cost, design automation for neural network accelerators was proposed, where design space exploration algorithms are used to automatically search the optimized accelerator design within a design space.
The non-tightness of the reconstruction threshold of a 4 states symmetric model with different in-block and out-block mutations
The tree reconstruction problem is to collect and analyze massive data at the $n$th level of the tree, to identify whether there is non-vanishing information of the root, as $n$ goes to infinity.
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