Jiezhong Qiu

Orcid: 0000-0001-9514-0708

According to our database1, Jiezhong Qiu authored at least 44 papers between 2014 and 2024.

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Bibliography

2024
Spatio-temporal Contrastive Learning-enhanced GNNs for Session-based Recommendation.
ACM Trans. Inf. Syst., March, 2024

An Autonomous Large Language Model Agent for Chemical Literature Data Mining.
CoRR, 2024

DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Multi-task bioassay pre-training for protein-ligand binding affinity prediction.
Briefings Bioinform., November, 2023

SketchNE: Embedding Billion-Scale Networks Accurately in One Hour.
IEEE Trans. Knowl. Data Eng., October, 2023

Towards Lightweight and Automated Representation Learning System for Networks.
IEEE Trans. Knowl. Data Eng., September, 2023

Improved the heterodimer protein complex prediction with protein language models.
Briefings Bioinform., July, 2023

TensorCircuit: a Quantum Software Framework for the NISQ Era.
Quantum, February, 2023

Holmes: Towards Distributed Training Across Clusters with Heterogeneous NIC Environment.
CoRR, 2023

Towards an Automatic AI Agent for Reaction Condition Recommendation in Chemical Synthesis.
CoRR, 2023

Multi-Constraint Molecular Generation using Sparsely Labelled Training Data for Localized High-Concentration Electrolyte Diluent Screening.
CoRR, 2023

Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform.
CoRR, 2023

Stable Prediction on Graphs with Agnostic Distribution Shifts.
Proceedings of the KDD'23 Workshop on Causal Discovery, 2023

2022
Spatio-Temporal Contrastive Learning Enhanced GNNs for Session-based Recommendation.
CoRR, 2022

BaGuaLu: targeting brain scale pretrained models with over 37 million cores.
Proceedings of the PPoPP '22: 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Seoul, Republic of Korea, April 2, 2022

Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Approximating Element-Wise Functions of Matrix with Improved Streaming Randomized SVD.
Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

GLM: General Language Model Pretraining with Autoregressive Blank Infilling.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Learning Large-scale Network Embedding from Representative Subgraph.
CoRR, 2021

NetMF+: Network Embedding Based on Fast and Effective Single-Pass Randomized Matrix Factorization.
CoRR, 2021

Stable Prediction on Graphs with Agnostic Distribution Shift.
CoRR, 2021

Modeling Protein Using Large-scale Pretrain Language Model.
CoRR, 2021

Pre-Trained Models: Past, Present and Future.
CoRR, 2021

FastMoE: A Fast Mixture-of-Expert Training System.
CoRR, 2021

All NLP Tasks Are Generation Tasks: A General Pretraining Framework.
CoRR, 2021

Pre-trained models: Past, present and future.
AI Open, 2021

LightNE: A Lightweight Graph Processing System for Network Embedding.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Graph Representation Learning: Foundations, Methods, Applications and Systems.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

The International Workshop on Pretraining: Algorithms, Architectures, and Applications ([email protected] 2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Fast Extraction of Word Embedding from Q-contexts.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Concentration Bounds for Co-occurrence Matrices of Markov Chains.
CoRR, 2020

A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Blockwise Self-Attention for Long Document Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019
Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models.
CoRR, 2019

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization.
Proceedings of the World Wide Web Conference, 2019

2018
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

Engagement and Incentives in Online Community: Observational Data, Prediction Models, and Field Experiments.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

DeepInf: Social Influence Prediction with Deep Learning.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017
Detecting Stress Based on Social Interactions in Social Networks.
IEEE Trans. Knowl. Data Eng., 2017

2016
The Lifecycle and Cascade of WeChat Social Messaging Groups.
Proceedings of the 25th International Conference on World Wide Web, 2016

Modeling and Predicting Learning Behavior in MOOCs.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

2015
The Lifecycle and Cascade of Social Messaging Groups.
CoRR, 2015

2014
Energy-traffic tradeoff cooperative offloading for mobile cloud computing.
Proceedings of the IEEE 22nd International Symposium of Quality of Service, 2014


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