Yongjun Xu

A Distributed SGD Algorithm with Global Sketching for Deep Learning Training Acceleration

2021 · arXiv (Cornell University)

Distributed training is an effective way to accelerate the training process of large-scale deep learning models. However, the parameter exchange and synchronization of distributed stochastic gradient descent introduce a large amount of communication overhead. Gradient …

Towards Robust Knowledge Graph Embedding via Multi-Task Reinforcement Learning

2021 · IEEE Transactions on Knowledge and Data Engineering

Nowadays, Knowledge graphs (KGs) have been playing a pivotal role in AI-related applications. Despite the large sizes, existing KGs are far from complete and comprehensive. In order to continuously enrich KGs, automatic knowledge construction and …

Along the Time

2022 · Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Recent years have witnessed remarkable progress on knowledge graph embedding (KGE) methods to learn the representations of entities and relations in static knowledge graphs (SKGs). However, knowledge changes over time. In order to represent the …

Attacking Pre-trained Recommendation

2023

Recently, a series of pioneer studies have shown the potency of pre-trained models in sequential recommendation, illuminating the path of building an omniscient unified pre-trained recommendation model for different downstream recommendation tasks. Despite these advancements, …

AdapTraj: A Multi-Source Domain Generalization Framework for Multi-Agent Trajectory Prediction

2024

Multi-agent trajectory prediction, as a critical task in modeling complex interactions of objects in dynamic systems, has attracted significant research attention in recent years. Despite the promising advances, existing studies all follow the assumption that …