Yan Liu

Orcid: 0000-0002-7055-9518

Affiliations:
  • University of Southern California, Computer Science Department, Los Angeles, CA, USA
  • IBM T. J. Watson Research Center, CA, USA (former)
  • Carnegie Mellon University, Language Technologies Institute, Pittsburgh, PA, USA (former)


According to our database1, Yan Liu authored at least 229 papers between 2002 and 2024.

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Bibliography

2024
Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution.
CoRR, 2024

Elephant in the Room: Unveiling the Impact of Reward Model Quality in Alignment.
CoRR, 2024

Trustworthiness in Retrieval-Augmented Generation Systems: A Survey.
CoRR, 2024

TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model.
CoRR, 2024

A Large-scale Benchmark Dataset for Commuting Origin-destination Matrix Generation.
CoRR, 2024

What's Wrong with Your Code Generated by Large Language Models? An Extensive Study.
CoRR, 2024

The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language Models.
CoRR, 2024

MetaRM: Shifted Distributions Alignment via Meta-Learning.
CoRR, 2024

Prompting Large Language Models with Divide-and-Conquer Program for Discerning Problem Solving.
CoRR, 2024

StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback.
CoRR, 2024

Secrets of RLHF in Large Language Models Part II: Reward Modeling.
CoRR, 2024

TrustLLM: Trustworthiness in Large Language Models.
CoRR, 2024

Toward Mitigating Misinformation and Social Media Manipulation in LLM Era.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series.
Proceedings of the Forty-first International Conference on Machine Learning, 2024


The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Negating Negatives: Alignment with Human Negative Samples via Distributional Dispreference Optimization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

TextGenSHAP: Scalable Post-Hoc Explanations in Text Generation with Long Documents.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

StepCoder: Improving Code Generation with Reinforcement Learning from Compiler Feedback.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

GPT4MTS: Prompt-based Large Language Model for Multimodal Time-series Forecasting.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
LoRAMoE: Revolutionizing Mixture of Experts for Maintaining World Knowledge in Language Model Alignment.
CoRR, 2023

COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning.
CoRR, 2023

Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments.
CoRR, 2023

Secrets of RLHF in Large Language Models Part I: PPO.
CoRR, 2023

Detecting Out-of-Context Multimodal Misinformation with interpretable neural-symbolic model.
CoRR, 2023

Estimating Treatment Effects in Continuous Time with Hidden Confounders.
CoRR, 2023

Time-delayed Multivariate Time Series Predictions.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Uncovering and Quantifying Social Biases in Code Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-supervised Sim-to-Real Kinematics Reconstruction for Video-Based Assessment of Intraoperative Suturing Skills.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Large Scale Financial Time Series Forecasting with Multi-faceted Model.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Capturing Cross-Platform Interaction for Identifying Coordinated Accounts of Misinformation Campaigns.
Proceedings of the Advances in Information Retrieval, 2023

SVGformer: Representation Learning for Continuous Vector Graphics using Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Uncovering and Categorizing Social Biases in Text-to-SQL.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Toward Accurate Spatiotemporal COVID-19 Risk Scores Using High-Resolution Real-World Mobility Data.
ACM Trans. Spatial Algorithms Syst., 2022

Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality.
Patterns, 2022

Surgical gestures as a method to quantify surgical performance and predict patient outcomes.
npj Digit. Medicine, 2022

DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift.
CoRR, 2022

Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality.
CoRR, 2022

When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning.
CoRR, 2022

Construction of Large-Scale Misinformation Labeled Datasets from Social Media Discourse using Label Refinement.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Mu2ReST: Multi-resolution Recursive Spatio-Temporal Transformer for Long-Term Prediction.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

COVID-19 Vaccine Misinformation Campaigns and Social Media Narratives.
Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

Characterizing Online Engagement with Disinformation and Conspiracies in the 2020 U.S. Presidential Election.
Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

Improving Weakly Supervised Scene Graph Parsing through Object Grounding.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

I-SEA: Importance Sampling and Expected Alignment-Based Deep Distance Metric Learning for Time Series Analysis and Embedding.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
PolSIRD: Modeling Epidemic Spread Under Intervention Policies.
J. Heal. Informatics Res., 2021

PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids.
CoRR, 2021

COVID-19 Vaccines: Characterizing Misinformation Campaigns and Vaccine Hesitancy on Twitter.
CoRR, 2021

Interpretable Artificial Intelligence through the Lens of Feature Interaction.
CoRR, 2021

MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset.
CoRR, 2021

Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Gradient-based optimization for multi-resource spatial coverage problems.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Identifying Coordinated Accounts on Social Media through Hidden Influence and Group Behaviours.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

An Examination of Fairness of AI Models for Deepfake Detection.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Network Inference from a Mixture of Diffusion Models for Fake News Mitigation.
Proceedings of the Fifteenth International AAAI Conference on Web and Social Media, 2021

Treatment Recommendation with Preference-based Reinforcement Learning.
Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020
KDD 2020 Highlights.
SIGKDD Explor., 2020

Towards Accurate Spatiotemporal COVID-19 Risk Scores using High Resolution Real-World Mobility Data.
CoRR, 2020

Identifying Coordinated Accounts in Disinformation Campaigns.
CoRR, 2020

Interpretable Deepfake Detection via Dynamic Prototypes.
CoRR, 2020

Coronavirus on Social Media: Analyzing Misinformation in Twitter Conversations.
CoRR, 2020

How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Multi-agent Trajectory Prediction with Fuzzy Query Attention.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection.
Proceedings of the 8th International Conference on Learning Representations, 2020

Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics.
Proceedings of the 8th International Conference on Learning Representations, 2020

Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

NoiseRank: Unsupervised Label Noise Reduction with Dependence Models.
Proceedings of the Computer Vision - ECCV 2020, 2020

Generative Attention Networks for Multi-Agent Behavioral Modeling.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Combating Fake News: A Survey on Identification and Mitigation Techniques.
ACM Trans. Intell. Syst. Technol., 2019

Scalable Interpretable Multi-Response Regression via SEED.
J. Mach. Learn. Res., 2019

Extracting Interpretable Concept-Based Decision Trees from CNNs.
CoRR, 2019

Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting.
CoRR, 2019

D<sup>2</sup>-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios.
CoRR, 2019

Intelligent systems for geosciences: an essential research agenda.
Commun. ACM, 2019

CoSTCo: A Neural Tensor Completion Model for Sparse Tensors.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

DBUS: Human Driving Behavior Understanding System.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

DeepFP for Finding Nash Equilibrium in Continuous Action Spaces.
Proceedings of the Decision and Game Theory for Security - 10th International Conference, 2019

Recommendation-based Team Formation for On-demand Taxi-calling Platforms.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Deep Fictitious Play for Games with Continuous Action Spaces.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Benchmarking deep learning models on large healthcare datasets.
J. Biomed. Informatics, 2018

Can I trust you more? Model-Agnostic Hierarchical Explanations.
CoRR, 2018

DynGEM: Deep Embedding Method for Dynamic Graphs.
CoRR, 2018

SIGIR 2018 Workshop on Intelligent Transportation Informatics.
Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multi-task Representation Learning for Travel Time Estimation.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Neural User Response Generator: Fake News Detection with Collective User Intelligence.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series.
Proceedings of the 35th International Conference on Machine Learning, 2018

Detecting Statistical Interactions from Neural Network Weights.
Proceedings of the 6th International Conference on Learning Representations, 2018

Automatically Inferring Data Quality for Spatiotemporal Forecasting.
Proceedings of the 6th International Conference on Learning Representations, 2018

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.
Proceedings of the 6th International Conference on Learning Representations, 2018

Tensor Regression Meets Gaussian Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Matrix completability analysis via graph k-connectivity.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Partially Generative Neural Networks for Gang Crime Classification with Partial Information.
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

Policy Learning for Continuous Space Security Games Using Neural Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Spatiotemporal Analysis of Social Media Data.
Proceedings of the Encyclopedia of GIS., 2017

Deep Generative Dual Memory Network for Continual Learning.
CoRR, 2017

Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets.
CoRR, 2017

CSI: A Hybrid Deep Model for Fake News.
CoRR, 2017

Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.
CoRR, 2017

Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding.
CoRR, 2017

Not Enough Data?: Joint Inferring Multiple Diffusion Networks via Network Generation Priors.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction.
Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Variational Recurrent Adversarial Deep Domain Adaptation.
Proceedings of the 5th International Conference on Learning Representations, 2017

Deep Learning Solutions to Computational Phenotyping in Health Care.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

CSI: A Hybrid Deep Model for Fake News Detection.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Low-Rank tensor regression: Scalability and applications.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Deep Learning Solutions for Classifying Patients on Opioid Use.
Proceedings of the AMIA 2017, 2017

Time Series Feature Learning with Applications to Health Care.
Proceedings of the Mobile Health - Sensors, Analytic Methods, and Applications, 2017

2016
Inferring Social Strength from Spatiotemporal Data.
ACM Trans. Database Syst., 2016

Lifecycle Modeling for Buzz Temporal Pattern Discovery.
ACM Trans. Knowl. Discov. Data, 2016

A Survey on Social Media Anomaly Detection.
SIGKDD Explor., 2016

The DARPA Twitter Bot Challenge.
CoRR, 2016

On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps.
CoRR, 2016

Recurrent Neural Networks for Multivariate Time Series with Missing Values.
CoRR, 2016

Geographic Segmentation via Latent Poisson Factor Model.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Learning Influence Functions from Incomplete Observations.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Latent Space Model for Road Networks to Predict Time-Varying Traffic.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Timeline Summarization from Social Media with Life Cycle Models.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning from Multiway Data: Simple and Efficient Tensor Regression.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Normal / Abnormal Heart Sound Recordings Classification Using Convolutional Neural Network.
Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016

Interpretable Deep Models for ICU Outcome Prediction.
Proceedings of the AMIA 2016, 2016

2015
GLAD: Group Anomaly Detection in Social Media Analysis.
ACM Trans. Knowl. Discov. Data, 2015

Scalable Multivariate Time-Series Models for Climate Informatics.
Comput. Sci. Eng., 2015

Spectral Sparsification of Random-Walk Matrix Polynomials.
CoRR, 2015

Distilling Knowledge from Deep Networks with Applications to Healthcare Domain.
CoRR, 2015

Hierarchical Active Transfer Learning.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Social Media Anomaly Detection: Challenges and Solutions.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Deep Computational Phenotyping.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams.
Proceedings of the 32nd International Conference on Machine Learning, 2015

HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Functional Subspace Clustering with Application to Time Series.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification.
Proceedings of The 28th Conference on Learning Theory, 2015

Causal Phenotype Discovery via Deep Networks.
Proceedings of the AMIA 2015, 2015

Model Selection for Topic Models via Spectral Decomposition.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
What is Tumblr: a statistical overview and comparison.
SIGKDD Explor., 2014

A general framework for scalable transductive transfer learning.
Knowl. Inf. Syst., 2014

GLAD: Group Anomaly Detection in Social Media Analysis- Extended Abstract.
CoRR, 2014

Analyzing the Number of Latent Topics via Spectral Decomposition.
CoRR, 2014

Scalable Parallel Factorizations of SDD Matrices and Efficient Sampling for Gaussian Graphical Models.
CoRR, 2014

Reports on the 2013 AAAI Fall Symposium Series.
AI Mag., 2014

Linking Heterogeneous Input Spaces with Pivots for Multi-Task Learning.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Which Tweets Will Be Headlines? A Hierarchical Bayesian Model for Bridging Social Media and Traditional Media.
Proceedings of the 8th Workshop on Social Network Mining and Analysis, 2014

Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

FBLG: a simple and effective approach for temporal dependence discovery from time series data.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Scalable Heterogeneous Transfer Ranking.
Proceedings of the 3rd International Workshop on Big Data, 2014

An Examination of Multivariate Time Series Hashing with Applications to Health Care.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Ups and Downs in Buzzes: Life Cycle Modeling for Temporal Pattern Discovery.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

2013
Improving recency ranking using twitter data.
ACM Trans. Intell. Syst. Technol., 2013

Towards Twitter context summarization with user influence models.
Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

EBM: an entropy-based model to infer social strength from spatiotemporal data.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

An Examination of Practical Granger Causality Inference.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Fast structure learning in generalized stochastic processes with latent factors.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Capturing Data Analytics Expertise with Visualizations in Workflows.
Proceedings of the 2013 AAAI Fall Symposia, Arlington, Virginia, USA, November 15-17, 2013, 2013

Preface.
Proceedings of the 2013 AAAI Fall Symposia, Arlington, Virginia, USA, November 15-17, 2013, 2013

Organizing Committee.
Proceedings of the 2013 AAAI Fall Symposia, Arlington, Virginia, USA, November 15-17, 2013, 2013

2012
Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems
CoRR, 2012

Transfer Topic Modeling with Ease and Scalability.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Granger Causality Analysis in Irregular Time Series.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Community discovery and profiling with social messages.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems.
Proceedings of the 29th International Conference on Machine Learning, 2012

Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling.
Proceedings of the 29th International Conference on Machine Learning, 2012

Granger Causality for Time-Series Anomaly Detection.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

On Causality Inference in Time Series.
Proceedings of the Discovery Informatics: The Role of AI Research in Innovating Scientific Processes, 2012

2011
Introduction to Special Issue on Large-Scale Data Mining.
ACM Trans. Knowl. Discov. Data, 2011

Temporal Graphical Models for Cross-Species Gene Regulatory Network Discovery.
J. Bioinform. Comput. Biol., 2011

Making data analysis expertise broadly accessible through workflows.
Proceedings of the WORKS'11, 2011

Multiple Instance Learning on Structured Data.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Serendipitous learning: learning beyond the predefined label space.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Multi-view transfer learning with a large margin approach.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Latent graphical models for quantifying and predicting patent quality.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Learning with Minimum Supervision: A General Framework for Transductive Transfer Learning.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

A Framework for Efficient Data Analytics through Automatic Configuration and Customization of Scientific Workflows.
Proceedings of the IEEE 7th International Conference on E-Science, 2011

Transfer Latent Semantic Learning: Microblog Mining with Less Supervision.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

Detecting Multilingual and Multi-Regional Query Intent in Web Search.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Medical data mining: insights from winning two competitions.
Data Min. Knowl. Discov., 2010

Learning Temporal Causal Graphs for Relational Time-Series Analysis.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

ALPOS: A Machine Learning Approach for Analyzing Microblogging Data.
Proceedings of the ICDMW 2010, 2010

Collaboration analytics: mining work patterns from collaboration activities.
Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Winning the KDD Cup Orange Challenge with Ensemble Selection.
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

Conditional Graphical Models for Protein Structural Motif Recognition.
J. Comput. Biol., 2009

Grouped graphical Granger modeling for gene expression regulatory networks discovery.
Bioinform., 2009

Proximity-Based Anomaly Detection Using Sparse Structure Learning.
Proceedings of the SIAM International Conference on Data Mining, 2009

Spatial-temporal causal modeling for climate change attribution.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Grouped graphical Granger modeling methods for temporal causal modeling.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Learning dynamic temporal graphs for oil-production equipment monitoring system.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Topic-link LDA: joint models of topic and author community.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Who is the expert? Analyzing gaze data to predict expertise level in collaborative applications.
Proceedings of the 2009 IEEE International Conference on Multimedia and Expo, 2009

Graph-based transfer learning.
Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

2008
Breast cancer identification: KDD CUP winner's report.
SIGKDD Explor., 2008

Harmonium Models for Video Classification.
Stat. Anal. Data Min., 2008

Graph-Based Rare Category Detection.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007
Making the most of your data: KDD Cup 2007 "How Many Ratings" winner's report.
SIGKDD Explor., 2007

Predicting who rated what in large-scale datasets.
SIGKDD Explor., 2007

Harmonium Models for Semantic Video Representation and Classification.
Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

Looking for Great Ideas: Analyzing the Innovation Jam.
Proceedings of the Advances in Web Mining and Web Usage Analysis, 2007

Temporal causal modeling with graphical granger methods.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Semi-Supervised Learning of Attribute-Value Pairs from Product Descriptions.
Proceedings of the IJCAI 2007, 2007

Protein Quaternary Fold Recognition Using Conditional Graphical Models.
Proceedings of the IJCAI 2007, 2007

Graph-Based Semi-Supervised Learning as a Generative Model.
Proceedings of the IJCAI 2007, 2007

Undirected Graphical Models for Video Analysis and Classification.
Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, 2007

2006
Text mining for product attribute extraction.
SIGKDD Explor., 2006

Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs).
J. Comput. Biol., 2006

Extracting and Using Attribute-Value Pairs from Product Descriptions on the Web.
Proceedings of the From Web to Social Web: Discovering and Deploying User and Content Profiles, 2006

2005
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition.
Proceedings of the Research in Computational Molecular Biology, 2005

Predicting protein folds with structural repeats using a chain graph model.
Proceedings of the Machine Learning, 2005

2004
Comparison of probabilistic combination methods for protein secondary structure prediction.
Bioinform., 2004

Context sensitive vocabulary and its application in protein secondary structure prediction.
Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

Kernel conditional random fields: representation and clique selection.
Proceedings of the Machine Learning, 2004

2003
On predicting rare classes with SVM ensembles in scene classification.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

A New Pairwise Ensemble Approach for Text Classification.
Proceedings of the Machine Learning: ECML 2003, 2003

2002
Boosting to correct inductive bias in text classification.
Proceedings of the 2002 ACM CIKM International Conference on Information and Knowledge Management, 2002


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