Feature selection for classification applications in neural network pruning by Gong, Rui

“…The feature selection problem, which is a traditional machine learning problem, share many similarities with neural network pruning problem. …”
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Unsupervised generative variational continual learning by Liu, Guimeng

“…Recent research in continual learning generally incorporates two of these methods to obtain better performance. …”
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Refining learning models in grammatical inference by Wang, Xiangrui

“…We introduce the use of recurrent neural networks (RNNs) and present a pruning learning method to avoid the exponential space costs. …”
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Towards ILP-based LTLf passive learning by Ielo, A, Law, M, Fionda, V, Ricca, F, De Giacomo, G, De Giacomo, G, Russo, A

“…Inferring a LTL_f formula from a set of example traces, also known as passive learning, is a challenging task for model-based techniques. …”

Learning class-specific edges for object detection and segmentation by Prasad, M, Zisserman, A, Fitzgibbon, A, Kumar, MP, Torr, PHS

“…This classifier may then be used to prune edges which are not relevant to the object class, and thereby improve the performance of subsequent processing. …”

Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-level Backdoor Attacks by Zhang, Zhengyan, Xiao, Guangxuan, Li, Yongwei, Lv, Tian, Qi, Fanchao, Liu, Zhiyuan, Wang, Yasheng, Jiang, Xin, Sun, Maosong

“…Finally, we apply several defense methods to NeuBA and find that model pruning is a promising technique to resist NeuBA by omitting backdoored neurons.…”
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Efficient algorithms for subgraph counting and enumeration on large graphs by Wang, Kaixin

“…It determines the weights of edges in a data-driven fashion, using a novel method based on reinforcement learning. We conduct extensive experi- ments to verify that our technique can produce estimates with smaller errors while often running faster compared with existing algorithms. …”
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