| 1 |
MLEM: Generative and Contrastive Learning as Distinct Modalities for Event Sequences |
提出MLEM模型以解决事件序列自监督学习的挑战 |
contrastive learning multimodal |
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| 2 |
Context-Former: Stitching via Latent Conditioned Sequence Modeling |
提出ContextFormer以解决决策变换器的拼接能力不足问题 |
reinforcement learning offline RL offline reinforcement learning |
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| 3 |
Effective Communication with Dynamic Feature Compression |
提出动态特征压缩以解决工业系统远程通信问题 |
reinforcement learning deep reinforcement learning DRL |
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| 4 |
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF |
提出迭代数据平滑方法以解决RLHF中的奖励过拟合问题 |
reinforcement learning RLHF |
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| 5 |
GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling |
提出GPS方法以解决图对比学习中的增强视图生成问题 |
representation learning contrastive learning |
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| 6 |
PICL: Physics Informed Contrastive Learning for Partial Differential Equations |
提出物理信息对比学习以提升偏微分方程求解的泛化能力 |
contrastive learning |
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| 7 |
Spectral Co-Distillation for Personalized Federated Learning |
提出谱共蒸馏方法以解决个性化联邦学习中的数据异质性问题 |
distillation |
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| 8 |
Supervised Contrastive Learning based Dual-Mixer Model for Remaining Useful Life Prediction |
提出双混合模型以解决剩余使用寿命预测问题 |
contrastive learning |
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| 9 |
Simple Policy Optimization |
提出简单策略优化算法以解决现有强化学习效率问题 |
reinforcement learning PPO |
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