A Computational Theory for Efficient Mini Agent Evaluation with Causal Guarantees
Published in Arxiv, 2025
Problem: experimental evaluation cost is too high for infinite mini angents. Solution: Use computational model to do evaluation.
Publications
You can also find my articles on my Google Scholar profile.
Manuscripts
Conference Papers
A Measurable Framework for Run-time Data Sampling in Large-scale Datacenter
Published in 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP), 2019
Problem: Due to the huge size of data centers, limited computing resources and the requirement of low delay, it is very difficult and unrealistic to collect all the data in large-scale data centers. Solution: Propose a measurable framework for general run-time data sampling in large-scale data center by modeling underlying recovering hypothesis explicitly
Qualifying Examination of PhD
A Survey of Task-driven Heterogeneous Feature Embedding and Selection
Published in Accepted in QE, Computer Science Department, Hong Kong Baptist University, 2023
Problem: heterogeneous feature processing, including heterogeneous feature embedding and heterogeneous feature selection.
Learning Causal Effect for High-dimensional Observation Data with Unmeasured Confounding
Published in Rejected in QE, Computer Science Department, Hong Kong Baptist University, 2023
Problem: Learning causal effect for high-dimensional observation data with unmeasured confounding.
Rejected Papers
Evaluate Causal Models without Counterfactual on Real Data
Published in Rejected by 2023 AAAI, 2023
Problem: Evaluation of individual treatment effect prediction. Solution: Independently, identically, distributed error assumption.
Treatment Effect Identification as An Out-of-Distribution Generalization Method for Semi-Markovian Causal Model
Published in Rejected by 2022 UAI, 2022
Problem: Out-of-distribution generalization. Solution: Invariance of semi-Markovian causal model.