Yingxia Shao

Orcid: 0000-0002-8559-2628

According to our database1, Yingxia Shao authored at least 103 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning.
Proc. VLDB Endow., February, 2024

ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs.
Proc. VLDB Endow., January, 2024

LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model.
CoRR, 2024

LLM vs Small Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Experimental Analysis of Large-scale Learnable Vector Storage Compression.
Proc. VLDB Endow., December, 2023

Multi-View Scholar Clustering With Dynamic Interest Tracking.
IEEE Trans. Knowl. Data Eng., September, 2023

P<sup>2</sup>CG: a privacy preserving collaborative graph neural network training framework.
VLDB J., July, 2023

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture.
IEEE Trans. Knowl. Data Eng., 2023

ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems.
Proc. VLDB Endow., 2023

DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU.
Proc. ACM Manag. Data, 2023

Making Large Language Models A Better Foundation For Dense Retrieval.
CoRR, 2023

Relation Extraction Model Based on Semantic Enhancement Mechanism.
CoRR, 2023

Dynamic Fair Federated Learning Based on Reinforcement Learning.
CoRR, 2023

Entity Alignment Method of Science and Technology Patent based on Graph Convolution Network and Information Fusion.
CoRR, 2023

Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation.
CoRR, 2023

LibVQ: A Toolkit for Optimizing Vector Quantization and Efficient Neural Retrieval.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Diversity-aware Deep Ranking Network for Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Knowledgeable Parameter Efficient Tuning Network for Commonsense Question Answering.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs.
IEEE Trans. Knowl. Data Eng., 2022

SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks.
Proc. VLDB Endow., 2022

An I/O-Efficient Disk-based Graph System for Scalable Second-Order Random Walk of Large Graphs.
Proc. VLDB Endow., 2022

Efficient Graph Neural Network Inference at Large Scale.
CoRR, 2022

Distributed Graph Neural Network Training: A Survey.
CoRR, 2022

Diffusion Models: A Comprehensive Survey of Methods and Applications.
CoRR, 2022

A Rare Topic Discovery Model for Short Texts Based on Co-occurrence word Network.
CoRR, 2022

Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency.
CoRR, 2022

A sentiment analysis model for car review texts based on adversarial training and whole word mask BERT.
CoRR, 2022

Sentiment Analysis of Online Travel Reviews Based on Capsule Network and Sentiment Lexicon.
CoRR, 2022

RetroMAE: Pre-training Retrieval-oriented Transformers via Masked Auto-Encoder.
CoRR, 2022

Research on Intellectual Property Resource Profile and Evolution Law.
CoRR, 2022

Retrieval of Scientific and Technological Resources for Experts and Scholars.
CoRR, 2022

Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings.
CoRR, 2022

Scientific and Technological Text Knowledge Extraction Method of based on Word Mixing and GRU.
CoRR, 2022

An Intellectual Property Entity Recognition Method Based on Transformer and Technological Word Information.
CoRR, 2022

Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search.
CoRR, 2022

LECF: recommendation via learnable edge collaborative filtering.
Sci. China Inf. Sci., 2022

Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Uni-Retriever: Towards Learning the Unified Embedding Based Retriever in Bing Sponsored Search.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Training Large-Scale News Recommenders with Pretrained Language Models in the Loop.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract).
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Scalable Graph Sampling on GPUs with Compressed Graph.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Adaptive Dual Channel Convolution Hypergraph Representation Learning for Technological Intellectual Property.
Proceedings of the 8th IEEE International Conference on Cloud Computing and Intelligent Systems, 2022

A Relational Triple Extraction Method Based on Feature Reasoning for Technological Patents.
Proceedings of the 8th IEEE International Conference on Cloud Computing and Intelligent Systems, 2022

2021
Memory-aware framework for fast and scalable second-order random walk over billion-edge natural graphs.
VLDB J., 2021

Sys-TM: A Fast and General Topic Modeling System.
IEEE Trans. Knowl. Data Eng., 2021

Gated Graph Neural Attention Networks for abstractive summarization.
Neurocomputing, 2021

Multiple Local Community Detection via High-Quality Seed Identification over Both Static and Dynamic Networks.
Data Sci. Eng., 2021

Search-oriented Differentiable Product Quantization.
CoRR, 2021

Training Microsoft News Recommenders with Pretrained Language Models in the Loop.
CoRR, 2021

Heterogeneous Hypergraph Embedding for Graph Classification.
Proceedings of the WSDM '21, 2021

Radio resource management algorithm for urban rail transit communication system based on Stackelberg game.
Proceedings of the 93rd IEEE Vehicular Technology Conference, 2021

Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

VF<sup>2</sup>Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

DeGNN: Improving Graph Neural Networks with Graph Decomposition.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract).
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Matching-oriented Embedding Quantization For Ad-hoc Retrieval.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Self-Supervised Graph Co-Training for Session-based Recommendation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Urban Fatigue Driving Prediction With Federated Learning.
Proceedings of the 7th IEEE International Conference on Cloud Computing and Intelligent Systems, 2021

Federated Graph Neural Network for Cross-graph Node Classification.
Proceedings of the 7th IEEE International Conference on Cloud Computing and Intelligent Systems, 2021

Multi-Modal COVID-19 Discovery With Collaborative Federated Learning.
Proceedings of the 7th IEEE International Conference on Cloud Computing and Intelligent Systems, 2021

2020
SKCompress: compressing sparse and nonuniform gradient in distributed machine learning.
VLDB J., 2020

DASFAA 20202 Special Issue Editorial.
Data Sci. Eng., 2020

Snapshot boosting: a fast ensemble framework for deep neural networks.
Sci. China Inf. Sci., 2020

Reliable Data Distillation on Graph Convolutional Network.
Proceedings of the 2020 International Conference on Management of Data, 2020

Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs.
Proceedings of the 2020 International Conference on Management of Data, 2020

Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript.
Proceedings of the 37th International Conference on Machine Learning, 2020

Efficient Diversity-Driven Ensemble for Deep Neural Networks.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Decentralized Embedding Framework for Large-Scale Networks.
Proceedings of the Database Systems for Advanced Applications, 2020

Densely-Connected Transformer with Co-attentive Information for Matching Text Sequences.
Proceedings of the Web and Big Data - 4th International Joint Conference, 2020

Multiple Local Community Detection via High-Quality Seed Identification.
Proceedings of the Web and Big Data - 4th International Joint Conference, 2020

Efficient Automatic CASH via Rising Bandits.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Large-scale Graph Analysis: System, Algorithm and Optimization
Springer, ISBN: 978-981-15-3927-5, 2020

2019
An Experimental Evaluation of Large Scale GBDT Systems.
Proc. VLDB Endow., 2019

Fast De-anonymization of Social Networks with Structural Information.
Data Sci. Eng., 2019

CNN Compression-Recovery Framework via Rank Allocation Decomposition With Knowledge Transfer.
IEEE Access, 2019

PS2: Parameter Server on Spark.
Proceedings of the 2019 International Conference on Management of Data, 2019

NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Sparse Gradient Compression for Distributed SGD.
Proceedings of the Database Systems for Advanced Applications, 2019

Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

FeatureBand: A Feature Selection Method by Combining Early Stopping and Genetic Local Search.
Proceedings of the Web and Big Data - Third International Joint Conference, 2019

Towards Reliable Learning for High Stakes Applications.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
GLM+: An Efficient System for Generalized Linear Models.
Proceedings of the 2018 IEEE International Conference on Big Data and Smart Computing, 2018

CUTE: Querying Knowledge Graphs by Tabular Examples.
Proceedings of the Web and Big Data - Second International Joint Conference, 2018

2017
Fast Parallel Path Concatenation for Graph Extraction.
IEEE Trans. Knowl. Data Eng., 2017

An Experimental Evaluation of SimRank-based Similarity Search Algorithms.
Proc. VLDB Endow., 2017

LDA*: A Robust and Large-scale Topic Modeling System.
Proc. VLDB Endow., 2017

2016
Tornado: A System For Real-Time Iterative Analysis Over Evolving Data.
Proceedings of the 2016 International Conference on Management of Data, 2016

2015
Heterogeneous Environment Aware Streaming Graph Partitioning.
IEEE Trans. Knowl. Data Eng., 2015

PAGE: A Partition Aware Engine for Parallel Graph Computation.
IEEE Trans. Knowl. Data Eng., 2015

An Efficient Similarity Search Framework for SimRank over Large Dynamic Graphs.
Proc. VLDB Endow., 2015

Exploiting Matrix Dependency for Efficient Distributed Matrix Computation.
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31, 2015

Joint Modeling of User Check-in Behaviors for Point-of-Interest Recommendation.
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

2014
Parallel subgraph listing in a large-scale graph.
Proceedings of the International Conference on Management of Data, 2014

Efficient cohesive subgraphs detection in parallel.
Proceedings of the International Conference on Management of Data, 2014

2013
bCATE: A Balanced Contention-Aware Transaction Execution Model for Highly Concurrent OLTP Systems.
Proceedings of the Web-Age Information Management - 14th International Conference, 2013

PAGE: a partition aware graph computation engine.
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013


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