Generalizing from Limited Resources in the Open World: Third International Workshop, Glow 2025, Held in Conjunction with Ijcai 2025, Montreal, Canada,
暫譯: 從有限資源中進行一般化於開放世界:第三屆國際研討會 Glow 2025,與 Ijcai 2025 共同舉辦,蒙特利爾,加拿大
Ma, Yuqing, Guo, Jinyang, Zhao, Xiaowei
- 出版商: Springer
- 出版日期: 2025-08-15
- 售價: $2,810
- 貴賓價: 9.5 折 $2,670
- 語言: 英文
- 頁數: 196
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9819509874
- ISBN-13: 9789819509874
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相關分類:
Machine Learning
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商品描述
This book presents the proceedings from the Third International Workshop on Generalizing from Limited Resources in the Open World (GLOW) 2025 held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI 2025, in Montreal, Canada, during August 16-22, 2025.
The 12 full papers in this book were carefully reviewed and selected from 27 submissions. These papers focus on the academic exploration of efficient methodologies within the realm of artificial intelligence models. We concentrated on both data-efficient strategies, such as zero/few-shot learning and domain adaptation, as well as model-efficient approaches like model sparsification and compact model design.
商品描述(中文翻譯)
本書呈現了2025年第三屆開放世界有限資源推廣國際研討會(GLOW)會議的論文集,該會議與2025年國際人工智慧聯合會議(IJCAI)於2025年8月16日至22日在加拿大蒙特利爾舉行。
本書中的12篇完整論文是從27篇投稿中經過仔細審核和選拔而來。這些論文專注於人工智慧模型領域內高效方法的學術探索。我們集中於數據高效策略,如零樣本/少樣本學習和領域適應,以及模型高效方法,如模型稀疏化和緊湊模型設計。