Wei Guo

Quantum controlled teleportation when only the sender knows the partially entangled state

2018 · Fourth Seminar on Novel Optoelectronic Detection Technology and Application

In this paper, a new proposal was presented to probabilistically transmit an unknown quantum state from a sender to a remote receiver with the aid of a controller when the non-maximally entangled state is only …

The Practice and Research of Orff's Music Teaching Method in Contemporary Chinese Music Teaching

2018 · Proceedings of the 2018 3rd International Conference on Humanities Science, Management and Education Technology (HSMET 2018)

As the greatest music research method in the world, Orff's music teaching method is praised by many countries in their own music education. But in the process of advocating and developing, it is more important …

Design of the Landslide Multi-factor Monitoring System Based on the GNSS Technology

2020 · MATEC Web of Conferences

Based on the multi-element monitoring of landslide, this paper adopts the GNSS technology to build the three-dimensional space monitoring system to research the landslide multi-element three- dimensional space monitoring technology. Through collecting the rainfall, soil …

A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks

2020

Personalized recommender systems are playing an increasingly important role for online consumption platforms. Because of the multitude of relationships existing in recommender systems, Graph Neural Networks (GNNs) based approaches have been proposed to better characterize …

Speech error recognition based on broad learning

2021 · Journal of Physics Conference Series

Abstract In recent years, with the increasing popularity of Chinese in the world, more foreigners have begun to learn Chinese. In this regard, this paper studies the phonetic errors in a single sentence, and designs …

Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models

2021

Effectively modeling feature interactions is crucial for CTR prediction in industrial recommender systems. The state-of-the-art deep CTR models with parallel structure (e.g., DCN) learn explicit and implicit feature interactions through independent parallel networks. However, these …

An Distributed CA System : Identity authentication system in transnational railway transportation based on blockchain

2021 · 2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI)

With the introduction of "One Belt, One Road" initiative, transnational railway container transportation has played an increasingly important role in the field of international trade and logistics. The transnational railway container transportation business involves multiple …

An abnormal data identification algorithm based on mutual checking between PMU and SCADA

2021 · 2021 IEEE Sustainable Power and Energy Conference (iSPEC)

With the development of the smart grid, the data center generates a large amount of abnormal data while obtaining massive multi-source data. Based on the analysis of PMU and SCADA measurement data, this paper proposes …

Prediction of Remaining Useful Life of Bearing Based on Long Short-Term Memory Network Optimized by Slime Mould Algorithm

2021 · 2021 China Automation Congress (CAC)

For resolve the trouble of low prediction accuracy and poor generalization ability of the neural network in the prediction of remaining useful life (RUL) of bearing, a prediction manner because of the combination of slime …

MIT: A Multi-Tower Information Transfer Framework Based on Hierarchical Task Relationship Modeling

2025

With the advancement of e-commerce platforms and online recommendation systems, conversion objectives have evolved from singular to diverse goals. To simultaneously enhance the performance of multiple conversion objectives, multi-task learning has become a classic solution. …

Silent Until Sparse: Backdoor Attacks on Semi-Structured Sparsity

2025 · arXiv (Cornell University)

Semi-structured (2:4) sparsity is a widely adopted pruning method in modern hardware and software ecosystems (e.g., NVIDIA Sparse Tensor Cores and PyTorch), achieving up to 2X faster inference and reduced memory footprint with negligible accuracy …