current reconstruction
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2021 ◽  
Vol 22 (1) ◽  
pp. 101-108
Author(s):  
Mustafa Aktaş ◽  
◽  
Barış Çavuş ◽  

Klio ◽  
2021 ◽  
Vol 103 (2) ◽  
pp. 409-435
Author(s):  
Salvatore Tufano

Summary This paper concentrates on the literary sources of the battle of Delion (424 BCE) and reopens the debate on the relevance of Euripides’ Supplices for the narrative of this event. Thucydides is read with a particular focus on the speech of Pagondas (4.92), which can be understood through the current reconstruction of the history of Boiotia in the latter half of the fifth century BCE. Finally, Diodorus (12.69–70) is considered as a useful source for a few pieces of information on the aftermath of the battle that have previously been disregarded.


Author(s):  
Baozhou Zhu ◽  
Peter Hofstee ◽  
Johan Peltenburg ◽  
Jinho Lee ◽  
Zaid Alars

Data-free compression raises a new challenge because the original training dataset for a pre-trained model to be compressed is not available due to privacy or transmission issues. Thus, a common approach is to compute a reconstructed training dataset before compression. The current reconstruction methods compute the reconstructed training dataset with a generator by exploiting information from the pre-trained model. However, current reconstruction methods focus on extracting more information from the pre-trained model but do not leverage network engineering. This work is the first to consider network engineering as an approach to design the reconstruction method. Specifically, we propose the AutoReCon method, which is a neural architecture search-based reconstruction method. In the proposed AutoReCon method, the generator architecture is designed automatically given the pre-trained model for reconstruction. Experimental results show that using generators discovered by the AutoRecon method always improve the performance of data-free compression.


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