Sriraam Natarajan

发表

Modeling heart procedures from EHRs: An application of exponential families

Fabian Hadiji, Kristian Kersting, Shaun J. Grannis, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Counting Belief Propagation

Kristian Kersting, Babak Ahmadi, Sriraam Natarajan, 2009, UAI.

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs

Kristian Kersting, Sriraam Natarajan, Mayukh Das, 2019, AAAI.

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

Sriraam Natarajan, Joseph A. Maldjian, Baidya Nath Saha, 2012, 2012 11th International Conference on Machine Learning and Applications.

Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach

Kristian Kersting, Sriraam Natarajan, Gautam Kunapuli, 2017, ILP.

A Decision-Theoretic Model of Assistance

Sriraam Natarajan, Alan Fern, Prasad Tadepalli, 2007, IJCAI.

Identifying Rare Diseases from Behavioural Data: A Machine Learning Approach

Shuo Yang, Sriraam Natarajan, Kim Oakes, 2016, 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

MapReduce Lifting for Belief Propagation

Kristian Kersting, Babak Ahmadi, Sriraam Natarajan, 2013, StarAI@AAAI.

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

Christopher Ré, Kristian Kersting, Sriraam Natarajan, 2013, AAAI Workshop: Statistical Relational Artificial Intelligence.

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

Sriraam Natarajan, Prasad Tadepalli, Jude W. Shavlik, 2009, 2009 International Conference on Machine Learning and Applications.

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

Kristian Kersting, Sriraam Natarajan, Prasad Tadepalli, 2011, IJCAI.

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

Kristian Kersting, Sriraam Natarajan, Ameet Soni, 2016, Solving Large Scale Learning Tasks.

Baum-Welch Algorithm

Wulfram Gerstner, Pascal Poupart, Hannu Toivonen, 2009, Encyclopedia of Machine Learning and Data Mining.

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

Kristian Kersting, Shuo Yang, Sriraam Natarajan, 2016, AAAI.

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

Kristian Kersting, Shuo Yang, Sriraam Natarajan, 2014, 2014 IEEE International Conference on Data Mining.

Exploiting symmetries for scaling loopy belief propagation and relational training

Kristian Kersting, Babak Ahmadi, Sriraam Natarajan, 2013, Machine Learning.

Extracting Adverse Drug Events from Text Using Human Advice

Sriraam Natarajan, David Page, Tushar Khot, 2015, AIME.

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

Kristian Kersting, Sriraam Natarajan, Prasad Tadepalli, 2010, StarAI@AAAI.

The Best of SIAM Data Mining 2020

Sriraam Natarajan, Yan Liu, 2020, Big Data.

Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data

Fabian Hadiji, Kristian Kersting, Sriraam Natarajan, 2015, Machine Learning.

Knowledge-Based Probabilistic Logic Learning

Sriraam Natarajan, Tushar Khot, Phillip Odom, 2015, AAAI.

Reports of the AAAI 2014 Conference Workshops

Guy Van den Broeck, André da Motta Salles Barreto, Jenna Wiens, 2015, AI Mag..

Application of Statistical Relational Learning to Hybrid Recommendation Systems pdf

Shuo Yang, Sriraam Natarajan, Khalifeh AlJadda, 2016, ArXiv.

Enabling Autonomy in Command and Control via Game-Theoretic Models and Machine Learning with a Systems Perspective

Sriraam Natarajan, Erik Blasch, Ali K. Raz, 2019, AIAA Scitech 2019 Forum.

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

Kristian Kersting, Sriraam Natarajan, Jude W. Shavlik, 2015, Machine Learning.

A Comparison of Weak Supervision methods for Knowledge Base Construction

Sriraam Natarajan, Ameet Soni, Dileep Viswanathan, 2016, AKBC@NAACL-HLT.

Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge

Christopher Ré, Kristian Kersting, Sriraam Natarajan, 2014, ILP.

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

Sriraam Natarajan, Gautam Kunapuli, Ameet Soni, 2014, SDM.

Learning first-order probabilistic models with combining rules

Thomas G. Dietterich, Sriraam Natarajan, Alan Fern, 2005, Annals of Mathematics and Artificial Intelligence.

Towards Problem Solving Agents that Communicate and Learn

Dan Roth, Sriraam Natarajan, Janardhan Rao Doppa, 2017, RoboNLP@ACL.

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

Sriraam Natarajan, David Page, Jeremy C. Weiss, 2015, AAAI.

Dynamic preferences in multi-criteria reinforcement learning

Sriraam Natarajan, Prasad Tadepalli, Prasad Tadepalli, 2005, ICML.

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

Sriraam Natarajan, Mayukh Das, Devendra Singh Dhami, 2019, ArXiv.

Neural Networks for Relational Data pdf

Kristian Kersting, Sriraam Natarajan, Gautam Kunapuli, 2019, ILP.

Boosting for Postpartum Depression Prediction

Sriraam Natarajan, Katie A. Siek, Kay Connelly, 2017, 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

Multiplicative Forests for Continuous-Time Processes

Sriraam Natarajan, David Page, Jeremy C. Weiss, 2012, NIPS.

Statistical Relational Artificial Intelligence: From Distributions through Actions to Optimization

Kristian Kersting, Sriraam Natarajan, K. Kersting, 2015, KI - Künstliche Intelligenz.

Human-Guided Learning for Probabilistic Logic Models

Sriraam Natarajan, Phillip Odom, Sriraam Natarajan, 2018, Front. Robot. AI.

Relational One-Class Classification: A Non-Parametric Approach

Sriraam Natarajan, Jude W. Shavlik, Tushar Khot, 2014, AAAI.

Identifying Adverse Drug Events by Relational Learning

Sriraam Natarajan, David Page, Vítor Santos Costa, 2012, AAAI.

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

Kristian Kersting, Sriraam Natarajan, Alejandro Molina, 2017, AAAI.

Biomedical Informatics

Sriraam Natarajan, David Page, David Page, 2010, Encyclopedia of Machine Learning.

Planning with actively eliciting preferences

Dan Roth, Sriraam Natarajan, Janardhan Rao Doppa, 2019, Knowl. Based Syst..

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

Kristian Kersting, Shuo Yang, Sriraam Natarajan, 2015, AIME.

Effective decision-theoretic assistance through relational hierarchical models

Sriraam Natarajan, Sriraam Natarajan, 2007 .

Boosted Statistical Relational Learners

Kristian Kersting, Sriraam Natarajan, Jude W. Shavlik, 2014, SpringerBriefs in Computer Science.

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

Sriraam Natarajan, Joseph A. Maldjian, Nilanjan Ray, 2013, ECML/PKDD.

Guiding Autonomous Agents to Better Behaviors through Human Advice

Sriraam Natarajan, Jude W. Shavlik, Gautam Kunapuli, 2013, 2013 IEEE 13th International Conference on Data Mining.

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

Sriraam Natarajan, Tushar Khot, Marcin Malec, 2016, ILP.

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

Sriraam Natarajan, David Page, Peggy L. Peissig, 2012, IAAI.

Control Diffusion of Information Collection for Situation Understanding Using Boosting MLNs

Erik Blasch, Sriraam Natarajan, Tim Kelly, 2018, 2018 21st International Conference on Information Fusion (FUSION).

Statistical Relational Artificial Intelligence: Logic, Probability, and Computation

Luc De Raedt, Kristian Kersting, Sriraam Natarajan, 2016, Statistical Relational Artificial Intelligence.

Actively Interacting with Experts: A Probabilistic Logic Approach

Sriraam Natarajan, Phillip Odom, Sriraam Natarajan, 2016, ECML/PKDD.

Interactive Transfer Learning in Relational Domains

Sriraam Natarajan, Phillip Odom, Nandini Ramanan, 2020, KI - Künstliche Intelligenz.

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

Kristian Kersting, Sriraam Natarajan, Joseph A. Maldjian, 2014, Int. J. Mach. Learn. Cybern..

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

Sriraam Natarajan, David Page, Peggy L. Peissig, 2012, AI Mag..

Learning first-order probabilistic models with combining rules

Thomas G. Dietterich, Sriraam Natarajan, Alan Fern, 2009, Annals of Mathematics and Artificial Intelligence.

Non-Parametric Learning of Lifted Restricted Boltzmann Machines pdf

Sriraam Natarajan, Gautam Kunapuli, Navdeep Kaur, 2020, Int. J. Approx. Reason..

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

Kristian Kersting, Sriraam Natarajan, Shrutika Poyrekar, 2014, AAAI Workshop: Statistical Relational Artificial Intelligence.

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

Sriraam Natarajan, Michael A. Skinner, Lakshmi Raman, 2020, ArXiv.

The AAAI-13 Conference Workshops

Diane J. Cook, Christopher W. Geib, Gita Reese Sukthankar, 2013, AI Mag..

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

Sriraam Natarajan, Mayukh Das, Alexander L. Hayes, 2017, K-CAP.

A machine learning based approach to improve sidechain optimization

Sriraam Natarajan, Alessandro Senes, Sabareesh Subramaniam, 2011, BCB '11.

Learning Relational Dependency Networks for Relation Extraction pdf

Sriraam Natarajan, Jude W. Shavlik, Ameet Soni, 2016, ILP.

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

Kristian Kersting, Sriraam Natarajan, Floriana Esposito, 2018, AAAI.

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

Sriraam Natarajan, Noah Hammarlund, 2017, 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

Statistical Relational Learning for Handwriting Recognition

Venu Govindaraju, Sriraam Natarajan, Arti Shivram, 2014, ILP.

Identifying Parkinson's Patients: A Functional Gradient Boosting Approach

Sriraam Natarajan, David Page, Devendra Singh Dhami, 2017, AIME.

Preference-Guided Planning: An Active Elicitation Approach

Dan Roth, Sriraam Natarajan, Janardhan Rao Doppa, 2018, AAMAS.

Classification from One Class of Examples for Relational Domains

Sriraam Natarajan, Jude W. Shavlik, Tushar Khot, 2014, StarAI@AAAI.

Relational Learning for Sustainable Health

Sriraam Natarajan, David Page, Peggy L. Peissig, 2016, Computational Sustainability.

Learning from Human Teachers: Issues and Challenges for ILP in Bootstrap Learning

Ciaran O'Reilly, Sriraam Natarajan, Gautam Kunapuli, 2010 .

Lifted Online Training of Relational Models with Stochastic Gradient Methods

Kristian Kersting, Babak Ahmadi, Sriraam Natarajan, 2012, ECML/PKDD.

Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities.

Sriraam Natarajan, Mayukh Das, Devendra Singh Dhami, 2018, Smart health.

Learning When to Reject an Importance Sample

Sriraam Natarajan, David Page, Jeremy C. Weiss, 2013, AAAI.

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

Kristian Kersting, Sriraam Natarajan, Joseph A. Maldjian, 2012, 2012 11th International Conference on Machine Learning and Applications.

Accelerating Imitation Learning in Relational Domains via Transfer by Initialization

Kristian Kersting, Sriraam Natarajan, Prasad Tadepalli, 2013, ILP.

Knowledge-Based Morphological Classification of Galaxies from Vision Features

Sriraam Natarajan, Devendra Singh Dhami, David B. Leake, 2017, AAAI Workshops.

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

Ciaran O'Reilly, Sriraam Natarajan, David Page, 2010, ILP.

Population Size Extrapolation in Relational Probabilistic Modelling

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2014, SUM.

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

Sriraam Natarajan, Jude W. Shavlik, 2009, IJCAI.

Active Preference Elicitation for Planning

Dan Roth, Sriraam Natarajan, Janardhan Rao Doppa, 2017, AAAI Workshops.

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

Sriraam Natarajan, Predrag Radivojac, Gautam Kunapuli, 2018, IJCAI.

Multi-Agent Inverse Reinforcement Learning

Kristian Kersting, Sriraam Natarajan, Prasad Tadepalli, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Learning Probabilistic Logic Models with Human Advice

Sriraam Natarajan, Tushar Khot, Phillip Odom, 2015, AAAI Spring Symposia.

Reports of the AAAI 2010 Conference Workshops

Gregory M. Provan, David W. Aha, Robert P. Goldman, 2010, AI Mag..

Learning Markov Logic Networks via Functional Gradient Boosting

Kristian Kersting, Sriraam Natarajan, Jude W. Shavlik, 2011, 2011 IEEE 11th International Conference on Data Mining.

Anomaly Detection in Text: The Value of Domain Knowledge

Sriraam Natarajan, Jude W. Shavlik, Tushar Khot, 2015, FLAIRS.

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

Shuo Yang, Sriraam Natarajan, Sriraam Natarajan, 2013, ECML/PKDD.

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

Marc Cavazza, Nathan R. Sturtevant, Blai Bonet, 2015, AI Mag..

Bootstrapping Knowledge Base Acceleration

Christopher Ré, Sriraam Natarajan, Jude W. Shavlik, 2013, TREC.

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

Sriraam Natarajan, Alan Fern, Prasad Tadepalli, 2007, Interaction Challenges for Intelligent Assistants.

Early Prediction of Coronary Artery Calcification Levels Using Machine Learning

Kristian Kersting, Sriraam Natarajan, Jeffrey Carr, 2013, IAAI.

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

Sriraam Natarajan, Mayukh Das, Devendra Singh Dhami, 2019, ArXiv.

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

Sriraam Natarajan, Alan Fern, Prasad Tadepalli, 2007, Probabilistic, Logical and Relational Learning - A Further Synthesis.

Structure learning for relational logistic regression: an ensemble approach

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2018, Data Mining and Knowledge Discovery.

Transfer in variable-reward hierarchical reinforcement learning

Sriraam Natarajan, Alan Fern, Prasad Tadepalli, 2008, Machine Learning.

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

Sriraam Natarajan, Jude W. Shavlik, Ameet Soni, 2015, TAC.

Discriminative boosted Bayes networks for learning multiple cardiovascular procedures

Shaun J. Grannis, Shuo Yang, Sriraam Natarajan, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Transfer Learning via Relational Type Matching

Kristian Kersting, Sriraam Natarajan, David B. Leake, 2015, 2015 IEEE International Conference on Data Mining.

Markov logic networks for adverse drug event extraction from text

Sriraam Natarajan, Jose Picado, David Page, 2016, Knowledge and Information Systems.

Scaling Lifted Probabilistic Inference and Learning Via Graph Databases

Kristian Kersting, Sriraam Natarajan, Yuqing Wu, 2016, SDM.

Active Advice Seeking for Inverse Reinforcement Learning

Sriraam Natarajan, Phillip Odom, 2015, AAAI.

Statistical Relational Artificial Intelligence, Papers from the 2010 AAAI Workshop, Atlanta, Georgia, USA, July 12, 2010

Leslie Pack Kaelbling, Kristian Kersting, Sriraam Natarajan, 2010, Statistical Relational Artificial Intelligence.

Lifted Hybrid Variational Inference

Nicholas Ruozzi, Sriraam Natarajan, Yuqiao Chen, 2020, IJCAI.

A relational hierarchical model for decision-theoretic assistance

Sriraam Natarajan, Alan Fern, Prasad Tadepalli, 2011, Knowledge and Information Systems.

Sum-Product Networks for Hybrid Domains pdf

Kristian Kersting, Sriraam Natarajan, Floriana Esposito, 2017, ArXiv.

Relational Logistic Regression: The Directed Analog of Markov Logic Networks

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2014, StarAI@AAAI.

Learning Through Advice-Seeking via Transfer

Kristian Kersting, Sriraam Natarajan, Phillip Odom, 2016, ILP.

A Relational Hierarchical Model for Decision-Theoretic Assistance

Sriraam Natarajan, Alan Fern, Prasad Tadepalli, 2007, ILP.

A context-aware personal desktop assistant

Eric Yeh, Sriraam Natarajan, Daniel Elenius, 2008, AAMAS.

Biomedical Informatics

Sriraam Natarajan, C. David Page, 2017, Encyclopedia of Machine Learning and Data Mining.

Relational Logistic Regression: The Directed Analog of Markov Logic Networks

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2014, StarAI@AAAI.

Human-Guided Column Networks: Augmenting Deep Learning with Advice

Sriraam Natarajan, Mayukh Das, Devendra Singh Dhami, 2018 .

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

Kristian Kersting, Sriraam Natarajan, Jude W. Shavlik, 2011, Machine Learning.

Logical Hierarchical Hidden Markov Models for Modeling User Activities

Weng-Keen Wong, Kristian Kersting, Sriraam Natarajan, 2008, ILP.

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

Shuo Yang, Sriraam Natarajan, Khalifeh AlJadda, 2017, Knowl. Based Syst..

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

Kristian Kersting, Sriraam Natarajan, Predrag Radivojac, 2021, ArXiv.

Relational Neural Markov Random Fields pdf

Nicholas Ruozzi, Sriraam Natarajan, Yuqiao Chen, 2021, AISTATS.

RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction

Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, 2021, ICAPS.

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

Sriraam Natarajan, Mayukh Das, Devendra Singh Dhami, 2021, KR.

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

Sriraam Natarajan, Predrag Radivojac, Alexander L. Hayes, 2021, AIME.

Dynamic probabilistic logic models for effective abstractions in RL pdf

Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, 2021, ArXiv.

Discriminative Non-Parametric Learning of Arithmetic Circuits

Kristian Kersting, Sriraam Natarajan, Mayukh Das, 2020, PGM.