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Tushar Ganguli and Edwin K. P. Chong
We present a novel technique for pruning called activation-based pruning to effectively prune fully connected feedforward neural networks for multi-object classification. Our technique is based on the number of times each neuron is activated during model...
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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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Abdelghani Azri, Adil Haddi and Hakim Allali
Collaborative filtering (CF), a fundamental technique in personalized Recommender Systems, operates by leveraging user?item preference interactions. Matrix factorization remains one of the most prevalent CF-based methods. However, recent advancements in ...
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Weiming Fan, Jiahui Yu and Zhaojie Ju
Endoscopy, a pervasive instrument for the diagnosis and treatment of hollow anatomical structures, conventionally necessitates the arduous manual scrutiny of seasoned medical experts. Nevertheless, the recent strides in deep learning technologies proffer...
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Rongsheng Li, Jin Xu, Zhixiong Cao, Hai-Tao Zheng and Hong-Gee Kim
In the realm of large language models (LLMs), extending the context window for long text processing is crucial for enhancing performance. This paper introduces SBA-RoPE (Segmented Base Adjustment for Rotary Position Embeddings), a novel approach designed...
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