Song Liu

Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective

2015 · arXiv (Cornell University)

Transfer learning assumes classifiers of similar tasks share certain parameter structures. Unfortunately, modern classifiers uses sophisticated feature representations with huge parameter spaces which lead to costly transfer. Under the impression that changes from one classifier …

Suppressing Coherent Two-Qubit Errors via Dynamical Decoupling

2021 · Physical Review Applied

Scalable quantum information processing requires the ability to tune multiqubit interactions. This makes the precise manipulation of quantum states particularly difficult for multiqubit interactions because tunability unavoidably introduces sensitivity to fluctuations in the tuning parameters, …

Document-Level Joint Biomedical Event Extraction Model Using Hypergraph Convolutional Networks

2022 · 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Biomedical event extraction is a fundamental information extraction task, which aims to identify biomedical event triggers and parameters in the text. Although various deep learning and Graph Convolutional Network (GCN) models have been proposed for …

BiLSTM-based Federated Learning Computation Offloading and Resource Allocation Algorithm in MEC

2023 · ACM Transactions on Sensor Networks

Mobile edge computing (MEC) driven by 5G cellular systems has recently emerged as a promising paradigm, enabling mobile devices (MDs) with limited computing resources to offload various computation-intensive tasks (such as autopilot, online game) to …

Neural network based time-resolved state tomography of superconducting qubits

2023 · arXiv (Cornell University)

Superconducting qubits have emerged as a premier platform for large-scale quantum computation, yet the fidelity of state readout is often hindered by random noise and crosstalk, especially in multi-qubit systems. While neural networks trained on …

Clustering and Anomaly Detection of Users Based on Seasonal Load Characteristics

2024

Accurate implementation of load clustering analysis can improve the accuracy of forecasting future load demand, which is more helpful for power system planners to better adjust the balance of power supply and demand, and reasonably …

Code Comment Inconsistency Detection and Rectification Using a Large Language Model

2025

Comments are widely used in source code. If a comment is consistent with the code snippet it intends to annotate, it would aid code comprehension. Otherwise, Code Comment Inconsistency (CCI) is not only detrimental to …

Modeling Relation Paths for Representation Learning of Knowledge Bases

2015

Representation learning of knowledge bases aims to embed both entities and relations into a low-dimensional space. Most existing methods only consider direct relations in representation learning. We argue that multiple-step relation paths also contain rich …

Personalized Dialogue Generation with Diversified Traits

2019 · arXiv (Cornell University)

Endowing a dialogue system with particular personality traits is essential to deliver more human-like conversations. However, due to the challenge of embodying personality via language expression and the lack of large-scale persona-labeled dialogue data, this …