Kun Xu

Evaluation System and Its Empirical Analysis of Students' Practical Ability for Application-oriented University

2018

There are many literatures on college students' practical ability, but the relevant empirical research methods are very few. From the views of the basic practical ability, professional practical ability and innovative practice ability, a practical …

Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

2019 · arXiv (Cornell University)

Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities that have different facts in two KGs. In this paper, we …

Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment

2020 · Proceedings of the AAAI Conference on Artificial Intelligence

Existing entity alignment methods mainly vary on the choices of encoding the knowledge graph, but they typically use the same decoding method, which independently chooses the local optimal match for each source entity. This decoding …

Large-scale coherent Ising machine based on optoelectronic parametric oscillator

2022 · Light Science & Applications

Ising machines based on analog systems have the potential to accelerate the solution of ubiquitous combinatorial optimization problems. Although some artificial spins to support large-scale Ising machines have been reported, e.g., superconducting qubits in quantum …

Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling

2015

Syntactic features play an essential role in identifying relationship in a sentence. Previous neural network models directly work on raw word sequences or constituent parse trees, thus often suffer from irrelevant information introduced when subjects …

Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks

2018 · arXiv (Cornell University)

The celebrated Sequence to Sequence learning (Seq2Seq) technique and its numerous variants achieve excellent performance on many tasks. However, many machine learning tasks have inputs naturally represented as graphs; existing Seq2Seq models face a significant …

Question Answering on Freebase via Relation Extraction and Textual Evidence

2016

Existing knowledge-based question answering systems often rely on small annotated training data. While shallow methods like relation extraction are robust to data scarcity, they are less expressive than the deep meaning representation methods like semantic …