Liang Zhao

Orcid: 0000-0002-2648-9989

Affiliations:
  • Emory University, Atlanta, GA, USA
  • George Mason University, Department of Information Science and Technology, Fairfax, VA, USA (former)
  • Virginia Tech, Blacksburg, VA, USA (PhD 2016)


According to our database1, Liang Zhao authored at least 195 papers between 2013 and 2024.

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Bibliography

2024
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks.
ACM Comput. Surv., May, 2024

Toward Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

Functional Connectivity Prediction With Deep Learning for Graph Transformation.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

DUE: Dynamic Uncertainty-Aware Explanation Supervision via 3D Imputation.
CoRR, 2024

ELAD: Explanation-Guided Large Language Models Active Distillation.
CoRR, 2024

Distilling Large Language Models for Text-Attributed Graph Learning.
CoRR, 2024

Explaining latent representations of generative models with large multimodal models.
CoRR, 2024

3DPFIX: Improving Remote Novices' 3D Printing Troubleshooting through Human-AI Collaboration.
CoRR, 2024

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models.
CoRR, 2024

2023
Deep Graph Translation.
IEEE Trans. Neural Networks Learn. Syst., November, 2023

Deep Spatial Prediction via Heterogeneous Multi-source Self-supervision.
ACM Trans. Spatial Algorithms Syst., September, 2023

Motif-guided heterogeneous graph deep generation.
Knowl. Inf. Syst., July, 2023

A Systematic Survey on Deep Generative Models for Graph Generation.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Modeling Health Stage Development of Patients With Dynamic Attributed Graphs in Online Health Communities.
IEEE Trans. Knowl. Data Eng., 2023

Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations.
Proc. ACM Hum. Comput. Interact., 2023

XAI Benchmark for Visual Explanation.
CoRR, 2023

Visual Attention-Prompted Prediction and Learning.
CoRR, 2023

SurroCBM: Concept Bottleneck Surrogate Models for Generative Post-hoc Explanation.
CoRR, 2023

Controllable Data Generation Via Iterative Data-Property Mutual Mappings.
CoRR, 2023

Saliency-Guided Hidden Associative Replay for Continual Learning.
CoRR, 2023

Multi-Prompt Fine-Tuning of Foundation Models for Enhanced Medical Image Segmentation.
CoRR, 2023

Helper Recommendation with seniority control in Online Health Community.
CoRR, 2023

Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction.
CoRR, 2023

Graph Neural Network for spatiotemporal data: methods and applications.
CoRR, 2023

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models.
CoRR, 2023

Domain Generalization Deep Graph Transformation.
CoRR, 2023

Deep Graph Representation Learning and Optimization for Influence Maximization.
CoRR, 2023

Knowledge-enhanced Neural Machine Reasoning: A Review.
CoRR, 2023


Sign-Regularized Multi-Task Learning.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Saliency-Augmented Memory Completion for Continual Learning.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Graph Neural Networks: Foundation, Frontiers and Applications.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

ESSA: Explanation Iterative Supervision via Saliency-guided Data Augmentation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Unsupervised Deep Subgraph Anomaly Detection (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Deep Graph Representation Learning and Optimization for Influence Maximization.
Proceedings of the International Conference on Machine Learning, 2023

Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Infinitely Deep Graph Transformation Networks.
Proceedings of the IEEE International Conference on Data Mining, 2023

Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

MAGI: Multi-Annotated Explanation-Guided Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023


2022
Spatio-Temporal Event Forecasting Using Incremental Multi-Source Feature Learning.
ACM Trans. Knowl. Discov. Data, 2022

Online and Distributed Robust Regressions with Extremely Noisy Labels.
ACM Trans. Knowl. Discov. Data, 2022

Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment.
Proc. ACM Hum. Comput. Interact., 2022

Accelerated Gradient-free Neural Network Training by Multi-convex Alternating Optimization.
Neurocomputing, 2022

Event Prediction in the Big Data Era: A Systematic Survey.
ACM Comput. Surv., 2022

Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning.
CoRR, 2022

Controllable Data Generation by Deep Learning: A Review.
CoRR, 2022

Distributed Graph Neural Network Training with Periodic Historical Embedding Synchronization.
CoRR, 2022

Temporal Domain Generalization with Drift-Aware Dynamic Neural Network.
CoRR, 2022

Black-box Node Injection Attack for Graph Neural Networks.
CoRR, 2022

Small molecule generation via disentangled representation learning.
Bioinform., 2022

An Invertible Graph Diffusion Neural Network for Source Localization.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Beam Pattern Fingerprinting with Missing Features for Spoofing Attack Detection in Millimeter-Wave Networks.
Proceedings of the WiseML@WiSec 2022: Proceedings of the 2022 ACM Workshop on Wireless Security and Machine Learning, 2022

Interpretable Molecular Graph Generation via Monotonic Constraints.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

STGEN: Deep Continuous-Time Spatiotemporal Graph Generation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Convergence and Applications of ADMM on the Multi-convex Problems.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Multi-objective Deep Data Generation with Correlated Property Control.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep Generative Model for Periodic Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

RES: A Robust Framework for Guiding Visual Explanation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Saliency-Regularized Deep Multi-Task Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

DeepSpatial'22: The 3rd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Unsupervised Deep Subgraph Anomaly Detection.
Proceedings of the IEEE International Conference on Data Mining, 2022

Deep Spatial Domain Generalization.
Proceedings of the IEEE International Conference on Data Mining, 2022

DeepGAR: Deep Graph Learning for Analogical Reasoning.
Proceedings of the IEEE International Conference on Data Mining, 2022

RAPTA: A Hierarchical Representation Learning Solution For Real-Time Prediction of Path-Based Static Timing Analysis.
Proceedings of the GLSVLSI '22: Great Lakes Symposium on VLSI 2022, Irvine CA USA, June 6, 2022

Deep geometric neural network for spatial interpolation.
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

Factorized deep generative models for end-to-end trajectory generation with spatiotemporal validity constraints.
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

Generation and Characterization of Quaternary Ammonium Compounds via Deep Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Property-Controllable Generation of Quaternary Ammonium Compounds.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

From "Dynamics on Graphs" to "Dynamics of Graphs": An Adaptive Echo-State Network Solution (Student Abstract).
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Adaptive Kernel Graph Neural Network.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Disentangled Spatiotemporal Graph Generative Models.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Dataset for Disentangled Representation Learning for Interpretable Molecule Generation.
Dataset, April, 2021

Dataset for Generative Adversarial Learning of Protein Tertiary Structures. Molecules, 2021.
Dataset, February, 2021

Large-scale Cost-Aware Classification Using Feature Computational Dependency Graph.
IEEE Trans. Knowl. Data Eng., 2021

CPM: A general feature dependency pattern mining framework for contrast multivariate time series.
Pattern Recognit., 2021

Schematic memory persistence and transience for efficient and robust continual learning.
Neural Networks, 2021

Deep graph transformation for attributed, directed, and signed networks.
Knowl. Inf. Syst., 2021

BEAN: Interpretable and Efficient Learning With Biologically-Enhanced Artificial Neuronal Assembly Regularization.
Frontiers Neurorobotics, 2021

Deep Graph Learning for Circuit Deobfuscation.
Frontiers Big Data, 2021

Time series clustering in linear time complexity.
Data Min. Knowl. Discov., 2021

Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token Attributions in Different Languages?
CoRR, 2021

A Convergent ADMM Framework for Efficient Neural Network Training.
CoRR, 2021

Community-based Layerwise Distributed Training of Graph Convolutional Networks.
CoRR, 2021

Heterogeneous Temporal Graph Neural Network.
CoRR, 2021

Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks.
CoRR, 2021

Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework.
CoRR, 2021

Integrating memory-mapping and N-dimensional hash function for fast and efficient grid-based climate data query.
Ann. GIS, 2021

TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Dr.Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Disentangled Dynamic Graph Deep Generation.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

FedAT: a high-performance and communication-efficient federated learning system with asynchronous tiers.
Proceedings of the International Conference for High Performance Computing, 2021

Representation Learning on Spatial Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

GraphGT: Machine Learning Datasets for Graph Generation and Transformation.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

DeepSpatial'21: 2nd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Deep Generative Models for Spatial Networks.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Property Controllable Variational Autoencoder via Invertible Mutual Dependence.
Proceedings of the 9th International Conference on Learning Representations, 2021

Deep Generation of Heterogeneous Networks.
Proceedings of the IEEE International Conference on Data Mining, 2021

GNES: Learning to Explain Graph Neural Networks.
Proceedings of the IEEE International Conference on Data Mining, 2021

Deep Latent-Variable Models for Controllable Molecule Generation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Deep Graph Spectral Evolution Networks for Graph Topological Evolution.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Contrast Pattern Mining in Paired Multivariate Time Series of a Controlled Driving Behavior Experiment.
ACM Trans. Spatial Algorithms Syst., 2020

Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting.
IEEE Trans. Knowl. Data Eng., 2020

Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification Over Encrypted Wi-Fi Traffic.
IEEE Trans. Inf. Forensics Secur., 2020

Online flu epidemiological deep modeling on disease contact network.
GeoInformatica, 2020

Taking the pulse of COVID-19: a spatiotemporal perspective.
Int. J. Digit. Earth, 2020

Online Decision Trees with Fairness.
CoRR, 2020

FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data.
CoRR, 2020

Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints.
CoRR, 2020

Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training.
CoRR, 2020

TG-GAN: Deep Generative Models for Continuously-time Temporal Graph Generation.
CoRR, 2020

Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder.
CoRR, 2020

Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks.
CoRR, 2020

Cognitive and Scalable Technique for Securing IoT Networks Against Malware Epidemics.
IEEE Access, 2020

Interpretable Deep Graph Generation with Node-edge Co-disentanglement.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks.
Proceedings of the 21st International Symposium on Quality Electronic Design, 2020

Toward Model Parallelism for Deep Neural Network based on Gradient-free ADMM Framework.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Cyber-guided Deep Neural Network for Malicious Repository Detection in GitHub.
Proceedings of the 2020 IEEE International Conference on Knowledge Graph, 2020

Mitigating Cache-Based Side-Channel Attacks through Randomization: A Comprehensive System and Architecture Level Analysis.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Estimating the Circuit De-obfuscation Runtime based on Graph Deep Learning.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints.
ACM Trans. Spatial Algorithms Syst., 2019

Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation.
ACM Trans. Knowl. Discov. Data, 2019

GeoAI 2019 workshop report: The 3nd ACM SIGSPATIAL International Workshop on GeoAI: AI for Geographic Knowledge Discovery: Seattle, WA, USA - November 5, 2019.
ACM SIGSPATIAL Special, 2019

BEAN: Interpretable Representation Learning with Biologically-Enhanced Artificial Neuronal Assembly Regularization.
CoRR, 2019

Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design.
CoRR, 2019

Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning.
CoRR, 2019

Your Style Your Identity: Leveraging Writing and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network.
Proceedings of the World Wide Web Conference, 2019

Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Efficient Global String Kernel with Random Features: Beyond Counting Substructures.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

ADMM for Efficient Deep Learning with Global Convergence.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Spatio-temporal Event Forecasting and Precursor Identification.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Interpreting and Evaluating Neural Network Robustness.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

ECoST: Energy-Efficient Co-Locating and Self-Tuning MapReduce Applications.
Proceedings of the 48th International Conference on Parallel Processing, 2019

Contrast Feature Dependency Pattern Mining for Controlled Experiments with Application to Driving Behavior.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Deep Multi-attributed Graph Translation with Node-Edge Co-Evolution.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction.
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

Machine Learning-Based Delay-Aware UAV Detection Over Encrypted Wi-Fi Traffic.
Proceedings of the 7th IEEE Conference on Communications and Network Security, 2019

Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Multi-stage Deep Classifier Cascades for Open World Recognition.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

iTrustSO: an intelligent system for automatic detection of insecure code snippets in stack overflow.
Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
2nd ACM SIGSPATIAL workshop on analytics for local events and news (LENS 2018) seattle, washington, USA - November 6, 2018.
ACM SIGSPATIAL Special, 2018

Interpretable Convolutional Filter Pruning.
CoRR, 2018

Interpreting Adversarial Robustness: A View from Decision Surface in Input Space.
CoRR, 2018

Adverse event detection by integrating twitter data and VAERS.
J. Biomed. Semant., 2018

Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Forecasting Gang Homicides with Multi-level Multi-task Learning.
Proceedings of the Social, Cultural, and Behavioral Modeling, 2018

Prediction-time Efficient Classification Using Feature Computational Dependencies.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Distributed Self-Paced Learning in Alternating Direction Method of Multipliers.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Social Media based Simulation Models for Understanding Disease Dynamics.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Robust Regression via Online Feature Selection Under Adversarial Data Corruption.
Proceedings of the IEEE International Conference on Data Mining, 2018

Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features.
Proceedings of the IEEE International Conference on Data Mining, 2018

KADetector: Automatic Identification of Key Actors in Online Hack Forums Based on Structured Heterogeneous Information Network.
Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

Local Event Forecasting and Synthesis Using Unpaired Deep Graph Translations.
Proceedings of the 2nd ACM SIGSPATIAL Workshop on Analytics for Local Events and News, 2018

Situation-Based Interpretable Learning for Personality Prediction in Social Media.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Semi-supervised Multi-instance Interpretable Models for Flu Shot Adverse Event Detection.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

ICSD: An Automatic System for Insecure Code Snippet Detection in Stack Overflow over Heterogeneous Information Network.
Proceedings of the 34th Annual Computer Security Applications Conference, 2018

Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Distant-Supervision of Heterogeneous Multitask Learning for Social Event Forecasting With Multilingual Indicators.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting.
IEEE Trans. Knowl. Data Eng., 2017

Spatial Event Forecasting in Social Media With Geographically Hierarchical Regularization.
Proc. IEEE, 2017

Robust Regression via Heuristic Hard Thresholding.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Online and Distributed Robust Regressions Under Adversarial Data Corruption.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Modeling and Prediction of People's Needs (Vision Paper).
Proceedings of the 1st ACM SIGSPATIAL Workshop on Analytics for Local Events and News, 2017

A Uniform Representation for Trajectory Learning Tasks.
Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017

Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Trendi: Tracking stories in news and microblogs via emerging, evolving and fading topics.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

TRACES: Generating Twitter stories via shared subspace and temporal smoothness.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

A natural language normalization approach to enhance social media text reasoning.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Determining Relative Airport Threats from News and Social Media.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Online Spatial Event Forecasting in Microblogs.
ACM Trans. Spatial Algorithms Syst., 2016

A Framework for Discovering Evolving Domain Related Spatio-Temporal Patterns in Twitter.
ISPRS Int. J. Geo Inf., 2016

Automatic targeted-domain spatiotemporal event detection in twitter.
GeoInformatica, 2016

A topic-focused trust model for Twitter.
Comput. Commun., 2016

Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Multi-resolution Spatial Event Forecasting in Social Media.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
How events unfold: spatiotemporal mining in social media.
ACM SIGSPATIAL Special, 2015

Spatiotemporal Event Forecasting in Social Media.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Multi-Task Learning for Spatio-Temporal Event Forecasting.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

SimNest: Social Media Nested Epidemic Simulation via Online Semi-Supervised Deep Learning.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Dynamic theme tracking in Twitter.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
Misinformation Propagation in the Age of Twitter.
Computer, 2014

Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System.
Big Data, 2014


The EMBERS architecture for streaming predictive analytics.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013
STED: semi-supervised targeted-interest event detectionin in twitter.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013


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