Yaliang Li

Orcid: 0000-0002-4204-6096

According to our database1, Yaliang Li authored at least 198 papers between 2011 and 2024.

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Bibliography

2024
When Transformer Meets Large Graphs: An Expressive and Efficient Two-View Architecture.
IEEE Trans. Knowl. Data Eng., October, 2024

Privacy-preserving Cross-domain Recommendation with Federated Graph Learning.
ACM Trans. Inf. Syst., September, 2024

Performance-Based Pricing of Federated Learning via Auction.
Proc. VLDB Endow., February, 2024

Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation.
Proc. VLDB Endow., January, 2024

GenSim: A General Social Simulation Platform with Large Language Model based Agents.
CoRR, 2024

Agent-Oriented Planning in Multi-Agent Systems.
CoRR, 2024

Safety Layers of Aligned Large Language Models: The Key to LLM Security.
CoRR, 2024

Exploring Selective Layer Fine-Tuning in Federated Learning.
CoRR, 2024

Understanding Byzantine Robustness in Federated Learning with A Black-box Server.
CoRR, 2024

Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models.
CoRR, 2024

EIUP: A Training-Free Approach to Erase Non-Compliant Concepts Conditioned on Implicit Unsafe Prompts.
CoRR, 2024

Very Large-Scale Multi-Agent Simulation in AgentScope.
CoRR, 2024

On the Design and Analysis of LLM-Based Algorithms.
CoRR, 2024

Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development.
CoRR, 2024

The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective.
CoRR, 2024

ExVideo: Extending Video Diffusion Models via Parameter-Efficient Post-Tuning.
CoRR, 2024

Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining.
CoRR, 2024

Review of Data-centric Time Series Analysis from Sample, Feature, and Period.
CoRR, 2024

Less is More: Data Value Estimation for Visual Instruction Tuning.
CoRR, 2024

Unleashing the Potential of Large Language Models as Prompt Optimizers: An Analogical Analysis with Gradient-based Model Optimizers.
CoRR, 2024

A Bargaining-based Approach for Feature Trading in Vertical Federated Learning.
CoRR, 2024

Double-I Watermark: Protecting Model Copyright for LLM Fine-tuning.
CoRR, 2024

AgentScope: A Flexible yet Robust Multi-Agent Platform.
CoRR, 2024

Federated Fine-tuning of Large Language Models under Heterogeneous Language Tasks and Client Resources.
CoRR, 2024

An Auction-based Marketplace for Model Trading in Federated Learning.
CoRR, 2024

EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models.
CoRR, 2024

Enhancing Multimodal Large Language Models with Vision Detection Models: An Empirical Study.
CoRR, 2024

Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs.
Proceedings of the ACM on Web Conference 2024, 2024

Data-Juicer: A One-Stop Data Processing System for Large Language Models.
Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

VertiMRF: Differentially Private Vertical Federated Data Synthesis.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

On the Convergence of Zeroth-Order Federated Tuning for Large Language Models.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Multi-modal Data Processing for Foundation Models: Practical Guidances and Use Cases.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Improving LoRA in Privacy-preserving Federated Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

LST2A: Lexical-Syntactic Targeted Adversarial Attack for Texts.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

SGFL-Attack: A Similarity-Guidance Strategy for Hard-Label Textual Adversarial Attack Based on Feedback Learning.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Federated Heterogeneous Contrastive Distillation for Molecular Representation Learning.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

DATA-CUBE: Data Curriculum for Instruction-based Sentence Representation Learning.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Leveraging Long Short-Term User Preference in Conversational Recommendation via Multi-agent Reinforcement Learning.
IEEE Trans. Knowl. Data Eng., November, 2023

Concept-Level Model Interpretation From the Causal Aspect.
IEEE Trans. Knowl. Data Eng., September, 2023

Knowledge-Based Reasoning Network for Relation Detection.
IEEE Trans. Neural Networks Learn. Syst., August, 2023

LOKI: A Practical Data Poisoning Attack Framework Against Next Item Recommendations.
IEEE Trans. Knowl. Data Eng., May, 2023

Multi-grained hypergraph interest modeling for conversational recommendation.
AI Open, January, 2023

FederatedScope: A Flexible Federated Learning Platform for Heterogeneity.
Proc. VLDB Endow., 2023

FS-Real: A Real-World Cross-Device Federated Learning Platform.
Proc. VLDB Endow., 2023

BASE: Bridging the Gap between Cost and Latency for Query Optimization.
Proc. VLDB Endow., 2023

Counterfactual Debiasing for Generating Factually Consistent Text Summaries.
CoRR, 2023

HPN: Personalized Federated Hyperparameter Optimization.
CoRR, 2023

LON-GNN: Spectral GNNs with Learnable Orthonormal Basis.
CoRR, 2023

Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning.
Proceedings of the ACM Web Conference 2023, 2023

Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

FS-REAL: Towards Real-World Cross-Device Federated Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization.
Proceedings of the International Conference on Machine Learning, 2023

Efficient Personalized Federated Learning via Sparse Model-Adaptation.
Proceedings of the International Conference on Machine Learning, 2023

Learned Index with Dynamic $\epsilon$.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Source-Free Unsupervised Domain Adaptation for Question Answering.
Proceedings of the IEEE International Conference on Acoustics, 2023

ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Tunable Soft Prompts are Messengers in Federated Learning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Knowledge-Guided Disentangled Representation Learning for Recommender Systems.
ACM Trans. Inf. Syst., 2022

Interpretable Aspect-Aware Capsule Network for Peer Review Based Citation Count Prediction.
ACM Trans. Inf. Syst., 2022

Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge.
ACM Trans. Inf. Syst., 2022

Toward Personalized Answer Generation in E-Commerce via Multi-perspective Preference Modeling.
ACM Trans. Inf. Syst., 2022

Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing.
Proc. VLDB Endow., 2022

Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning.
CoRR, 2022

FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization.
CoRR, 2022

A Benchmark for Federated Hetero-Task Learning.
CoRR, 2022

FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing.
CoRR, 2022

KoMen: Domain Knowledge Guided Interaction Recommendation for Emerging Scenarios.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Explainable Neural Rule Learning.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Alleviating Spurious Correlations in Knowledge-aware Recommendations through Counterfactual Generator.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph Neural Networks with Node-wise Architecture.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

A Practical Introduction to Federated Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Towards Universal Sequence Representation Learning for Recommender Systems.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Finding Meta Winning Ticket to Train Your MAML.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

iFlood: A Stable and Effective Regularizer.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Privacy-Preserved Neural Graph Similarity Learning.
Proceedings of the IEEE International Conference on Data Mining, 2022

MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

A Unified Transferable Model for ML-Enhanced DBMS.
Proceedings of the 12th Conference on Innovative Data Systems Research, 2022

ID-Agnostic User Behavior Pre-training for Sequential Recommendation.
Proceedings of the Information Retrieval - 28th China Conference, 2022

2021
Modeling Relation Paths for Knowledge Graph Completion.
IEEE Trans. Knowl. Data Eng., 2021

A Survey on Causal Inference.
ACM Trans. Knowl. Discov. Data, 2021

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition.
Proc. VLDB Endow., 2021

Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modeling.
CoRR, 2021

A Pluggable Learned Index Method via Sampling and Gap Insertion.
CoRR, 2021

Automated Graph Learning via Population Based Self-Tuning GCN.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

RAST: A Reward Augmented Model for Fine-Grained Sentiment Transfer.
Proceedings of the Natural Language Processing and Chinese Computing, 2021

Data Poisoning Attack against Recommender System Using Incomplete and Perturbed Data.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Debiasing Learning based Cross-domain Recommendation.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

AutoML: A Perspective where Industry Meets Academy.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Profanity-Avoiding Training Framework for Seq2seq Models with Certified Robustness.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Wasserstein Selective Transfer Learning for Cross-domain Text Mining.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

EasyTransfer: A Simple and Scalable Deep Transfer Learning Platform for NLP Applications.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

AutoML: From Methodology to Application.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

CRSLab: An Open-Source Toolkit for Building Conversational Recommender System.
Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Differential Privacy for Text Analytics via Natural Text Sanitization.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Learning to Augment for Data-scarce Domain BERT Knowledge Distillation.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Learning Distance Metrics from Probabilistic Information.
ACM Trans. Knowl. Discov. Data, 2020

Extracting Medical Knowledge from Crowdsourced Question Answering Website.
IEEE Trans. Big Data, 2020

EasyTransfer - A Simple and Scalable Deep Transfer Learning Platform for NLP Applications.
CoRR, 2020

Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph.
CoRR, 2020

Practical Data Poisoning Attack against Next-Item Recommendation.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Sequential Recommendation with Self-Attentive Multi-Adversarial Network.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Bridging Hierarchical and Sequential Context Modeling for Question-driven Extractive Answer Summarization.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Learning to Mutate with Hypergradient Guided Population.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Scalable Graph Neural Networks via Bidirectional Propagation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Causal Inference Meets Machine Learning.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Entity Synonym Discovery via Multipiece Bilateral Context Matching.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Simple and Deep Graph Convolutional Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Automated Relational Meta-learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Towards Differentially Private Truth Discovery for Crowd Sensing Systems.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

An Adaptive Embedding Framework for Heterogeneous Information Networks.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Attentive User-Engaged Adversarial Neural Network for Community Question Answering.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

On the Generation of Medical Question-Answer Pairs.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Privacy-Preserving Truth Discovery in Crowd Sensing Systems.
ACM Trans. Sens. Networks, 2019

KMR: knowledge-oriented medicine representation learning for drug-drug interaction and similarity computation.
J. Cheminformatics, 2019

Towards Data Poisoning Attack against Knowledge Graph Embedding.
CoRR, 2019

SynonymNet: Multi-context Bilateral Matching for Entity Synonyms.
CoRR, 2019

Enhancing ontology-driven diagnostic reasoning with a symptom-dependency-aware Naïve Bayes classifier.
BMC Bioinform., 2019

MCVAE: Margin-based Conditional Variational Autoencoder for Relation Classification and Pattern Generation.
Proceedings of the World Wide Web Conference, 2019

Answer-enhanced Path-aware Relation Detection over Knowledge Base.
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

DTEC: Distance Transformation Based Early Time Series Classification.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Path-based Attribute-aware Representation Learning for Relation Prediction.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Deep Skip-Gram Networks for Text Classification.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

A Minimax Game for Instance based Selective Transfer Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Data Poisoning Attack against Knowledge Graph Embedding.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

On the Estimation of Treatment Effect with Text Covariates.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

ACE: Adaptively Similarity-Preserved Representation Learning for Individual Treatment Effect Estimation.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

MedTruth: A Semi-supervised Approach to Discovering Knowledge Condition Information from Multi-Source Medical Data.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Knowledge-aware Textual Entailment with Graph Attention Network.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Joint Slot Filling and Intent Detection via Capsule Neural Networks.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Multi-grained Named Entity Recognition.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
CBN: Constructing a clinical Bayesian network based on data from the electronic medical record.
J. Biomed. Informatics, 2018

Finding Similar Medical Questions from Question Answering Websites.
CoRR, 2018

When Truth Discovery Meets Medical Knowledge Graph: Estimating Trustworthiness Degree for Medical Knowledge Condition.
CoRR, 2018

An ontology-driven clinical decision support system (IDDAP) for infectious disease diagnosis and antibiotic prescription.
Artif. Intell. Medicine, 2018

Gastroenterology Ontology Construction Using Synonym Identification and Relation Extraction.
IEEE Access, 2018

Knowledge-aware Attentive Neural Network for Ranking Question Answer Pairs.
Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Ontology Evaluation with Path-based Text-aware Entropy Computation.
Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Online Truth Discovery on Time Series Data.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Uncorrelated Patient Similarity Learning.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Representation Learning for Treatment Effect Estimation from Observational Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

TextTruth: An Unsupervised Approach to Discover Trustworthy Information from Multi-Sourced Text Data.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

On the Generative Discovery of Structured Medical Knowledge.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

An Efficient Two-Layer Mechanism for Privacy-Preserving Truth Discovery.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Metric Learning from Probabilistic Labels.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

IDDAT: An Ontology-Driven Decision Support System for Infectious Disease Diagnosis and Therapy.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Cooperative Denoising for Distantly Supervised Relation Extraction.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Knowledge as A Bridge: Improving Cross-domain Answer Selection with External Knowledge.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Drug2Vec: Knowledge-aware Feature-driven Method for Drug Representation Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Leveraging the Power of Informative Users for Local Event Detection.
Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

2017
A Weighted Crowdsourcing Approach for Network Quality Measurement in Cellular Data Networks.
IEEE Trans. Mob. Comput., 2017

Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Collaboratively Improving Topic Discovery and Word Embeddings by Coordinating Global and Local Contexts.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

A lightweight privacy-preserving truth discovery framework for mobile crowd sensing systems.
Proceedings of the 2017 IEEE Conference on Computer Communications, 2017

A Correlated Topic Model Using Word Embeddings.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Generating Medical Hypotheses Based on Evolutionary Medical Concepts.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Bringing semantic structures to user intent detection in online medical queries.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Conflicts to Harmony: A Framework for Resolving Conflicts in Heterogeneous Data by Truth Discovery.
IEEE Trans. Knowl. Data Eng., 2016

Topic Discovery for Short Texts Using Word Embeddings.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Augmented LSTM Framework to Construct Medical Self-Diagnosis Android.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Multi-source Hierarchical Prediction Consolidation.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

Influence-Aware Truth Discovery.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

Multi-View Time Series Classification: A Discriminative Bilinear Projection Approach.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
A Survey on Truth Discovery.
SIGKDD Explor., 2015

Cloud-Enabled Privacy-Preserving Truth Discovery in Crowd Sensing Systems.
Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, 2015

Truth Discovery on Crowd Sensing of Correlated Entities.
Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, 2015

Believe It Today or Tomorrow? Detecting Untrustworthy Information from Dynamic Multi-Source Data.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

On the Discovery of Evolving Truth.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
A Confidence-Aware Approach for Truth Discovery on Long-Tail Data.
Proc. VLDB Endow., 2014

Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation.
Proceedings of the International Conference on Management of Data, 2014

Crowdsourcing for Multiple-Choice Question Answering.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Ensemble Learning.
Proceedings of the Data Classification: Algorithms and Applications, 2014

2012
Query-Oriented Keyphrase Extraction.
Proceedings of the Information Retrieval Technology, 2012

2011
Extracting Relation Descriptors with Conditional Random Fields.
Proceedings of the Fifth International Joint Conference on Natural Language Processing, 2011


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