Shu Yang

8

Papers

21

Total Citations

Papers (8)

Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks

Enhancing Statistical Validity and Power in Hybrid Controlled Trials: A Randomization Inference Approach with Conformal Selective Borrowing

Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment

Efficient Causal Decision Making with One-sided Feedback

Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model

Efficient ANN-Guided Distillation: Aligning Rate-based Features of Spiking Neural Networks through Hybrid Block-wise Replacement

Evaluating and Learning Optimal Dynamic Treatment Regimes under Truncation by Death

ABQ-LLM: Arbitrary-Bit Quantized Inference Acceleration for Large Language Models