Sriraam Natarajan

CoRR, 2024

Deep Tractable Probabilistic Models.

[BibT_eX]

[DOI]

Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), 2024

Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

RePReL: a unified framework for integrating relational planning and reinforcement learning for effective abstraction in discrete and continuous domains.

[BibT_eX]

[DOI]

Neural Comput. Appl., August, 2023

Learning with privileged and sensitive information: a gradient-boosting approach.

[BibT_eX]

[DOI]

Frontiers Artif. Intell., February, 2023

Active feature elicitation: An unified framework.

[BibT_eX]

[DOI]

Frontiers Artif. Intell., February, 2023

Knowledge-based Refinement of Scientific Publication Knowledge Graphs.

[BibT_eX]

[DOI]

Siwen Yan

CoRR, 2023

MACOptions: Multi-Agent Learning with Centralized Controller and Options Framework.

[BibT_eX]

[DOI]

CoRR, 2023

Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference.

[BibT_eX]

[DOI]

Sahil Sidheekh

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Knowledge Intensive Learning of Cutset Networks.

[BibT_eX]

[DOI]

Saurabh Mathur

Vibhav Gogate

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Active Feature Acquisition via Human Interaction in Relational domains.

[BibT_eX]

[DOI]

Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD), 2023

Never Ending Reasoning and Learning: Opportunities and Challenges.

[BibT_eX]

[DOI]

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

Human-guided Collaborative Problem Solving: A Natural Language based Framework.

[BibT_eX]

[DOI]

CoRR, 2022

Explaining Deep Tractable Probabilistic Models: The sum-product network case.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Information Fusion, 2022

Relational Active Feature Elicitation for DDDAS.

[BibT_eX]

[DOI]

Proceedings of the Dynamic Data Driven Applications Systems - 4th International Conference, 2022

Relational Neural Markov Random Fields.

[BibT_eX]

[DOI]

Yuqiao Chen

Nicholas Ruozzi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

An Anytime Querying Algorithm for Predicting Cardiac Arrest in Children: Work-in-Progress.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence in Medicine, 2022

2021

Structure learning for relational logistic regression: an ensemble approach.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2021

Explaining Deep Tractable Probabilistic Models: The sum-product network case.

[BibT_eX]

[DOI]

CoRR, 2021

Dynamic probabilistic logic models for effective abstractions in RL.

[BibT_eX]

[DOI]

CoRR, 2021

Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN.

[BibT_eX]

[DOI]

Siwen Yan

CoRR, 2021

Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation.

[BibT_eX]

[DOI]

Mayukh Das

Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 30th International Conference, 2021

A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation.

[BibT_eX]

[DOI]

Srijita Das

Rishabh K. Iyer

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021

A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence in Medicine, 2021

Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence in Medicine, 2021

Relational Boosted Bandits.

[BibT_eX]

[DOI]

Ashutosh Kakadiya

Balaraman Ravindran

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Interactive Transfer Learning in Relational Domains.

[BibT_eX]

[DOI]

Künstliche Intell., 2020

Non-parametric learning of lifted Restricted Boltzmann Machines.

[BibT_eX]

[DOI]

Navdeep Kaur

Gautam Kunapuli

Int. J. Approx. Reason., 2020

Few-Shot Induction of Generalized Logical Concepts via Human Guidance.

[BibT_eX]

[DOI]

Frontiers Robotics AI, 2020

Causal Learning From Predictive Modeling for Observational Data.

[BibT_eX]

[DOI]

Nandini Ramanan

Frontiers Big Data, 2020

Fitted Q-Learning for Relational Domains.

[BibT_eX]

[DOI]

CoRR, 2020

Knowledge Graph Alignment using String Edit Distance.

[BibT_eX]

[DOI]

Navdeep Kaur

Gautam Kunapuli

CoRR, 2020

A Preliminary Approach for Learning Relational Policies for the Management of Critically Ill Children.

[BibT_eX]

[DOI]

CoRR, 2020

Non-Parametric Learning of Gaifman Models.

[BibT_eX]

[DOI]

CoRR, 2020

The Best of SIAM Data Mining 2020.

[BibT_eX]

[DOI]

Yan Liu

Big Data, 2020

Discriminative Non-Parametric Learning of Arithmetic Circuits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Knowledge Intensive Learning of Generative Adversarial Networks.

[BibT_eX]

[DOI]

Mayukh Das

Proceedings of the ACM SIGKDD Workshop on Knowledge-infused Mining and Learning for Social Impact co-located with 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Virtual) (SIGKDD 2020), 2020

Cost Aware Feature Elicitation.

[BibT_eX]

[DOI]

Srijita Das

Rishabh K. Iyer

Lifted Hybrid Variational Inference.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

The Curious Case of Stacking Boosted Relational Dependency Networks.

[BibT_eX]

[DOI]

Siwen Yan

Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Planning with actively eliciting preferences.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2019

Editorial: Statistical Relational Artificial Intelligence.

[BibT_eX]

[DOI]

Frontiers Robotics AI, 2019

One-Shot Induction of Generalized Logical Concepts via Human Guidance.

[BibT_eX]

[DOI]

CoRR, 2019

Predicting Drug-Drug Interactions from Molecular Structure Images.

[BibT_eX]

[DOI]

CoRR, 2019

Knowledge-augmented Column Networks: Guiding Deep Learning with Advice.

[BibT_eX]

[DOI]

CoRR, 2019

Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice.

[BibT_eX]

[DOI]

CoRR, 2019

Neural Networks for Relational Data.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 29th International Conference, 2019

Lifted Message Passing for Hybrid Probabilistic Inference.

[BibT_eX]

[DOI]

Yuqiao Chen

Nicholas Ruozzi

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Human-Guided Learning for Probabilistic Logic Models.

[BibT_eX]

[DOI]

Frontiers Robotics AI, 2018

On Whom Should I Perform this Lab Test Next? An Active Feature Elicitation Approach.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Control Diffusion of Information Collection for Situation Understanding Using Boosting MLNs.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Information Fusion, 2018

Preference-Guided Planning: An Active Elicitation Approach.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Biomedical Informatics.

[BibT_eX]

[DOI]

C. David Page

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Combining content-based and collaborative filtering for job recommendation system: A cost-sensitive Statistical Relational Learning approach.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2017

Markov logic networks for adverse drug event extraction from text.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2017

Sum-Product Networks for Hybrid Domains.

[BibT_eX]

[DOI]

CoRR, 2017

User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams.

[BibT_eX]

[DOI]

Proceedings of the Knowledge Capture Conference, 2017

Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 27th International Conference, 2017

Boosting for Postpartum Depression Prediction.

[BibT_eX]

[DOI]

Proceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, 2017

Does Race Play a Role in Invasive Procedure Treatments? An Initial Analysis.

[BibT_eX]

[DOI]

Noah Hammarlund

Proceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, 2017

Modeling heart procedures from EHRs: An application of exponential families.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Discriminative boosted Bayes networks for learning multiple cardiovascular procedures.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Identifying Parkinson's Patients: A Functional Gradient Boosting Approach.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence in Medicine, 2017

Towards Problem Solving Agents that Communicate and Learn.

[BibT_eX]

[DOI]

Proceedings of the First Workshop on Language Grounding for Robotics, 2017

Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions.

[BibT_eX]

[DOI]

Alejandro Molina

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Knowledge-Based Morphological Classification of Galaxies from Vision Features.

[BibT_eX]

[DOI]

David Leake

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

Active Preference Elicitation for Planning.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Statistical Relational Artificial Intelligence: Logic, Probability, and Computation

[BibT_eX]

[DOI]

Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, ISBN: 978-3-031-01574-8, 2016

Relational Learning for Sustainable Health.

[BibT_eX]

[DOI]

Peggy L. Peissig

David Page

Proceedings of the Computational Sustainability, 2016

Application of Statistical Relational Learning to Hybrid Recommendation Systems.

[BibT_eX]

[DOI]

CoRR, 2016

Scaling Lifted Probabilistic Inference and Learning Via Graph Databases.

[BibT_eX]

[DOI]

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Actively Interacting with Experts: A Probabilistic Logic Approach.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Learning Relational Dependency Networks for Relation Extraction.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 26th International Conference, 2016

Learning Through Advice-Seeking via Transfer.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 26th International Conference, 2016

Inductive Logic Programming Meets Relational Databases: Efficient Learning of Markov Logic Networks.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 26th International Conference, 2016

Identifying Rare Diseases from Behavioural Data: A Machine Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the First IEEE International Conference on Connected Health: Applications, 2016

Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction.

[BibT_eX]

[DOI]

Proceedings of the Solving Large Scale Learning Tasks. Challenges and Algorithms, 2016

A Comparison of Weak Supervision methods for Knowledge Base Construction.

[BibT_eX]

[DOI]

Ameet Soni

Dileep Viswanathan

Niranjan Pachaiyappan

Proceedings of the 5th Workshop on Automated Knowledge Base Construction, 2016

Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases.

[BibT_eX]

[DOI]

Mach. Learn., 2015

Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data.

[BibT_eX]

[DOI]

Mach. Learn., 2015

Statistical Relational Artificial Intelligence: From Distributions through Actions to Optimization.

[BibT_eX]

[DOI]

Künstliche Intell., 2015

A Summary of the Twenty-Ninth AAAI Conference on Artificial Intelligence.

[BibT_eX]

[DOI]

George Dimitri Konidaris

AI Mag., 2015

Reports of the AAAI 2014 Conference Workshops.

[BibT_eX]

[DOI]

AI Mag., 2015

TAC KBP 2015 : English Slot Filling Track Relational Learning with Expert Advice.

[BibT_eX]

[DOI]

Proceedings of the 2015 Text Analysis Conference, 2015

Transfer Learning via Relational Type Matching.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Anomaly Detection in Text: The Value of Domain Knowledge.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

Modeling Coronary Artery Calcification Levels from Behavioral Data in a Clinical Study.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence in Medicine, 2015

Extracting Adverse Drug Events from Text Using Human Advice.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence in Medicine, 2015

Learning Probabilistic Logic Models with Human Advice.

[BibT_eX]

[DOI]

Tushar Khot

Proceedings of the 2015 AAAI Spring Symposia, 2015

Learning to Reject Sequential Importance Steps for Continuous-Time Bayesian Networks.

[BibT_eX]

[DOI]

Jeremy C. Weiss

C. David Page Jr.

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Active Advice Seeking for Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Knowledge-Based Probabilistic Logic Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Boosted Statistical Relational Learners - From Benchmarks to Data-Driven Medicine

[BibT_eX]

[DOI]

Springer Briefs in Computer Science, Springer, ISBN: 978-3-319-13644-8, 2014

Relational learning helps in three-way classification of Alzheimer patients from structural magnetic resonance images of the brain.

[BibT_eX]

[DOI]

Elizabeth M. Davenport

Christopher T. Whitlow

Joseph A. Maldjian

Int. J. Mach. Learn. Cybern., 2014

A Decision-Theoretic Model of Assistance.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2014

Population Size Extrapolation in Relational Probabilistic Modelling.

[BibT_eX]

[DOI]

Proceedings of the Scalable Uncertainty Management - 8th International Conference, 2014

A graphical model approach to ATLAS-free mining of MRI images.

[BibT_eX]

[DOI]

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Relational Logistic Regression.

[BibT_eX]

[DOI]

Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Fourteenth International Conference, 2014

Statistical Relational Learning for Handwriting Recognition.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 24th International Conference, 2014

Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 24th International Conference, 2014

Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

A Deeper Empirical Analysis of CBP Algorithm: Grounding Is the Bottleneck.

[BibT_eX]

[DOI]

Shrutika Poyrekar

Proceedings of the Statistical Relational Artificial Intelligence, 2014

Organizers.

[BibT_eX]

[DOI]

Proceedings of the Statistical Relational Artificial Intelligence, 2014

Classification from One Class of Examples for Relational Domains.

[BibT_eX]

[DOI]

Tushar Khot

Jude W. Shavlik

Proceedings of the Statistical Relational Artificial Intelligence, 2014

Relational One-Class Classification: A Non-Parametric Approach.

[BibT_eX]

[DOI]

Tushar Khot

Jude W. Shavlik

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Relational Logistic Regression: The Directed Analog of Markov Logic Networks.

[BibT_eX]

[DOI]

Proceedings of the Statistical Relational Artificial Intelligence, 2014

Preface.

[BibT_eX]

[DOI]

Proceedings of the Statistical Relational Artificial Intelligence, 2014

2013

Exploiting symmetries for scaling loopy belief propagation and relational training.

[BibT_eX]

[DOI]

Mach. Learn., 2013

The AAAI-13 Conference Workshops.

[BibT_eX]

[DOI]

AI Mag., 2013

Bootstrapping Knowledge Base Acceleration.

[BibT_eX]

[DOI]

Proceedings of The Twenty-Second Text REtrieval Conference, 2013

Knowledge Intensive Learning: Combining Qualitative Constraints with Causal Independence for Parameter Learning in Probabilistic Models.

[BibT_eX]

[DOI]

Shuo Yang

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Accelerating Imitation Learning in Relational Domains via Transfer by Initialization.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

Guiding Autonomous Agents to Better Behaviors through Human Advice.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Early Prediction of Coronary Artery Calcification Levels Using Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fifth Innovative Applications of Artificial Intelligence Conference, 2013

Learning When to Reject an Importance Sample.

[BibT_eX]

[DOI]

Jeremy C. Weiss

C. David Page Jr.

Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013

Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text.

[BibT_eX]

[DOI]

Proceedings of the Statistical Relational Artificial Intelligence, 2013

Preface.

[BibT_eX]

[DOI]

Proceedings of the Statistical Relational Artificial Intelligence, 2013

MapReduce Lifting for Belief Propagation.

[BibT_eX]

[DOI]

Babak Ahmadi

Proceedings of the Statistical Relational Artificial Intelligence, 2013

2012

Gradient-based boosting for statistical relational learning: The relational dependency network case.

[BibT_eX]

[DOI]

Mach. Learn., 2012

A relational hierarchical model for decision-theoretic assistance.

[BibT_eX]

[DOI]

Prasad Tadepalli

Alan Fern

Knowl. Inf. Syst., 2012

Machine Learning for Personalized Medicine: Predicting Primary Myocardial Infarction from Electronic Health Records.

[BibT_eX]

[DOI]

AI Mag., 2012

Aggregation and Population Growth: The Relational Logistic Regression and Markov Logic Cases.

[BibT_eX]

[DOI]

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Accelarating Imitation Learning in Relational Domains via Transfer by Initialization.

[BibT_eX]

[DOI]

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Integrating Human Instructions and Reinforcement Learners: An SRL Approach.

[BibT_eX]

[DOI]

Pradyot Korupolu V. N.

S. S. Manimaran

Balaraman Ravindran

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Learning Relational Structure for Temporal Relation Extraction.

[BibT_eX]

[DOI]

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Initial Empirical Evaluation of Anytime Lifted Belief Propagation.

[BibT_eX]

[DOI]

Richard G. Freedman

Rodrigo de Salvo Braz

Hung Bui

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Lifted Online Training of Relational Models with Stochastic Gradient Methods.

[BibT_eX]

[DOI]

Babak Ahmadi

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Multiplicative Forests for Continuous-Time Processes.

[BibT_eX]

[DOI]

Jeremy C. Weiss

David Page

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A Novel Hierarchical Level Set with AR-boost for White Matter Lesion Segmentation in Diabetes.

[BibT_eX]

[DOI]

Baidya Nath Saha

Gopi Kota

Christopher T. Whitlow

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain.

[BibT_eX]

[DOI]

Christopher T. Whitlow

Joseph A. Maldjian

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth Conference on Innovative Applications of Artificial Intelligence, 2012

Identifying Adverse Drug Events by Relational Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2011, 2011

Learning Markov Logic Networks via Functional Gradient Boosting.

[BibT_eX]

[DOI]

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

A machine learning based approach to improve sidechain optimization.

[BibT_eX]

[DOI]

Sabareesh Subramaniam

Alessandro Senes

Proceedings of the ACM International Conference on Bioinformatics, 2011

2010

Biomedical Informatics.

[BibT_eX]

[DOI]

C. David Page Jr.

Proceedings of the Encyclopedia of Machine Learning, 2010

Reports of the AAAI 2010 Conference Workshops.

[BibT_eX]

[DOI]

AI Mag., 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

Multi-Agent Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

2009

Counting Belief Propagation.

[BibT_eX]

[DOI]

Babak Ahmadi

Proceedings of the UAI 2009, 2009

Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network.

[BibT_eX]

[DOI]

Jude W. Shavlik

Proceedings of the IJCAI 2009, 2009

Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2009

2008

Transfer in variable-reward hierarchical reinforcement learning.

[BibT_eX]

[DOI]

Mach. Learn., 2008

Learning first-order probabilistic models with combining rules.

[BibT_eX]

[DOI]

Ann. Math. Artif. Intell., 2008

Logical Hierarchical Hidden Markov Models for Modeling User Activities.

[BibT_eX]

[DOI]

Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

A context-aware personal desktop assistant.

[BibT_eX]

[DOI]

Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 2008

2007

A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems.

[BibT_eX]

Proceedings of the Interaction Challenges for Intelligent Assistants, 2007

Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies.

[BibT_eX]

[DOI]

Prasad Tadepalli

Alan Fern

Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

2005

Learning first-order probabilistic models with combining rules.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2005

Dynamic preferences in multi-criteria reinforcement learning.

[BibT_eX]

[DOI]