1 citations · 1 across the 8 of their papers we have counts for
8 papers
RainSeer: Fine-Grained Rainfall Reconstruction via Physics-Guided Modeling
Lin Chen, Jun Chen, Minghui Qiu +3
Reconstructing high-resolution rainfall fields is essential for flood forecasting, hydrological modeling, and climate analysis. However, existing spatial interpolation methods-whet…
Spark Transformer: Reactivating Sparsity in FFN and Attention
Chong You, Kan Wu, Zhipeng Jia +16
The discovery of the lazy neuron phenomenon in trained Transformers, where the vast majority of neurons in their feed-forward networks (FFN) are inactive for each token, has spurre…
A Survey of Quantum Transformers: Architectures, Challenges and Outlooks
Hui Zhang, Qinglin Zhao, Mengchu Zhou +4
Quantum Transformers integrate the representational power of classical Transformers with the computational advantages of quantum computing. Since 2022, research in this area has ra…
Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption
Zhizheng Lai, Yufei Zhou, Peijia Zheng +1
The recently proposed Kolmogorov-Arnold Networks (KANs) offer enhanced interpretability and greater model expressiveness. However, KANs also present challenges related to privacy l…
Optimistic Rates for Learning from Label Proportions
Gene Li, Lin Chen, Adel Javanmard +1
We consider a weakly supervised learning problem called Learning from Label Proportions (LLP), where examples are grouped into ``bags'' and only the average label within each bag i…
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions
Adel Javanmard, Lin Chen, Vahab Mirrokni +2
Due to the rise of privacy concerns, in many practical applications the training data is aggregated before being shared with the learner, in order to protect privacy of users' sens…
Federated Learning with Extremely Noisy Clients via Negative Distillation
Yang Lu, Lin Chen, Yonggang Zhang +4
Federated learning (FL) has shown remarkable success in cooperatively training deep models, while typically struggling with noisy labels. Advanced works propose to tackle label noi…
Greedy PIG: Adaptive Integrated Gradients
Kyriakos Axiotis, Sami Abu-al-haija, Lin Chen +2
Deep learning has become the standard approach for most machine learning tasks. While its impact is undeniable, interpreting the predictions of deep learning models from a human pe…