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检索条件"机构=MIIT Key Laboratory of Pattern Analysis and Machine Intelligence"
231 条 记 录,以下是91-100 订阅
排序:
Filter, Obstruct and Dilute: Defending Against Backdoor Attacks on Semi-Supervised Learning
arXiv
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arXiv 2025年
作者: Wang, Xinrui Geng, Chuanxing Wan, Wenhai Li, Shao-Yuan Chen, Songcan College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China School of Computer Science and Technology Huazhong University of Science and Technology China
Recent studies have verified that semi-supervised learning (SSL) is vulnerable to data poisoning backdoor attacks. Even a tiny fraction of contaminated training data is sufficient for adversaries to manipulate up to 9... 详细信息
来源: 评论
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
arXiv
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arXiv 2023年
作者: Huang, Feihu College of Computer Science and Technology Nanjing University of Aeronautics and Astro-nautics Nanjing China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing China
In the paper, we study a class of nonconvex nonconcave minimax optimization problems (i.e., minx maxy f (x, y)), where f (x, y) is possible nonconvex in x, and it is nonconcave and satisfies the Polyak-Lojasiewicz (PL... 详细信息
来源: 评论
Characteristic AI Agents via Large Language Models
arXiv
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arXiv 2024年
作者: Wang, Xi Dai, Hongliang Gao, Shen Li, Piji College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing China School of Computer Science and Technology Shandong University China
The advancement of Large Language Models (LLMs) has led to significant enhancements in the performance of chatbot systems. Many researchers have dedicated their efforts to the development of bringing characteristics t... 详细信息
来源: 评论
Guidance Not Obstruction: A Conjugate Consistent Enhanced Strategy for Domain Generalization
arXiv
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arXiv 2024年
作者: Cao, Meng Chen, Songcan The MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing University of Aeronautics and Astronautics Nanjing210016 China The College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China
Domain generalization addresses domain shift in real-world applications. Most approaches adopt a domain angle, seeking invariant representation across domains by aligning their marginal distributions, irrespective of ...
来源: 评论
PIE: Physics-inspired Low-light Enhancement
arXiv
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arXiv 2024年
作者: Liang, Dong Xu, Zhengyan Li, Ling Wei, Mingqiang Chen, Songcan MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Nanjing Universily of Aeronautics Astronautics Shenzhen Research Institute China
In this paper, we propose a physics-inspired contrastive learning paradigm for low-light enhancement, called PIE. PIE primarily addresses three issues: (i) To resolve the problem of existing learning-based methods oft... 详细信息
来源: 评论
Recovering from out-of-sample states via inverse dynamics in offline reinforcement learning  23
Recovering from out-of-sample states via inverse dynamics in...
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Proceedings of the 37th International Conference on Neural Information Processing Systems
作者: Ke Jiang Jia-yu Yao Xiaoyang Tan College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics and MIIT Key Laboratory of Pattern Analysis and Machine Intelligence School of Electronic and Computer Engineering Peking University
We deal with the state distributional shift problem commonly encountered in offline reinforcement learning during test, where the agent tends to take unreliable actions at out-of-sample (unseen) states. Our idea is to...
来源: 评论
Relative Difficulty Distillation for Semantic Segmentation
arXiv
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arXiv 2024年
作者: Liang, Dong Sun, Yue Du, Yun Chen, Songcan Huang, Sheng-Jun MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China Nanjing University of Aeronautics Astronautics Shenzhen Research Institute China
Current knowledge distillation (KD) methods primarily focus on transferring various structured knowledge and designing corresponding optimization goals to encourage the student network to imitate the output of the tea... 详细信息
来源: 评论
Forgetting, Ignorance or Myopia: Revisiting key Challenges in Online Continual Learning
arXiv
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arXiv 2024年
作者: Wang, Xinrui Geng, Chuanxing Wan, Wenhai Li, Shao-Yuan Chen, Songcan College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China School of Computer Science and Technology Huazhong University of Science and Technology China
Online continual learning (OCL) requires the models to learn from constant, endless streams of data. While significant efforts have been made in this field, most were focused on mitigating the catastrophic forgetting ... 详细信息
来源: 评论
XL2Bench: A Benchmark for Extremely Long Context Understanding with Long-range Dependencies
arXiv
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arXiv 2024年
作者: Ni, Xuanfan Cai, Hengyi Wei, Xiaochi Wang, Shuaiqiang Yin, Dawei Li, Piji Nanjing University of Aeronautics and Astronautics Nanjing China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing China Institute of Computing Technology CAS Beijing China Baidu Inc. Beijing China
Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks but are constrained by their small context window sizes. Various efforts have been proposed to expand the context window to ac... 详细信息
来源: 评论
StructSR: Refuse Spurious Details in Real-World Image Super-Resolution
arXiv
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arXiv 2025年
作者: Li, Yachao Liang, Dong Ding, Tianyu Huang, Sheng-Jun College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing211106 China Microsoft Washington United States
Diffusion-based models have shown great promise in real-world image super-resolution (Real-ISR), but often generate content with structural errors and spurious texture details due to the empirical priors and illusions... 详细信息
来源: 评论