Deepak Venugopal

According to our database, Deepak Venugopal authored at least 52 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Mastery Guided Non-parametric Clustering to Scale-up Strategy Prediction.

Anup Shakya, Vasile Rus, Deepak Venugopal

CoRR, 2024

2023

On the verification of Embeddings using Hybrid Markov Logic.

Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal

CoRR, 2023

On the Verification of Embeddings with Hybrid Markov Logic.

Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the IEEE International Conference on Data Mining, 2023

Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data.

Anup Shakya, Vasile Rus, Deepak Venugopal

Proceedings of the 16th International Conference on Educational Data Mining, 2023

Verifying Relational Explanations: A Probabilistic Approach.

Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Question Modifiers in Visual Question Answering.

William Britton, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

Evaluating Captioning Models using Markov Logic Networks.

Monika Shah, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the IEEE International Conference on Big Data, 2022

2021

An Information-theoretic approach to dimensionality reduction in data science.

Sambriddhi Mainali, Max H. Garzon, Deepak Venugopal, Kalidas Jana, Ching-Chi Yang, Nirman Kumar, Dale Bowman, Lih-Yuan Deng

Int. J. Data Sci. Anal., 2021

Neuro-Symbolic Models: A Scalable, Explainable Framework for Strategy Discovery from Big Edu-Data.

Deepak Venugopal, Vasile Rus, Anup Shakya

Proceedings of the Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021 co-located with 14th International Conference on Educational Data Mining (EDM 2021), 2021

Student Strategy Prediction using a Neuro-Symbolic Approach.

Anup Shakya, Vasile Rus, Deepak Venugopal

Proceedings of the 14th International Conference on Educational Data Mining, 2021

The Learner Data Institute - Conceptualization: A Progress Report.

Vasile Rus, Stephen E. Fancsali, Philip I. Pavlik Jr., Deepak Venugopal, Arthur C. Graesser, Steven Ritter, Dale Bowman, The L. D. I. Team

Proceedings of the Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021 co-located with 14th International Conference on Educational Data Mining (EDM 2021), 2021

The Nature of Achievement Goal Motivation Profiles: Exploring Situational Motivation in An Algebra-Focused Intelligent Tutoring System.

Leigh M. Harrell-Williams, Christian Mueller, Stephen Fancsali, Steven Ritter, Xiaofei Zhang, Deepak Venugopal

Proceedings of the Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021 co-located with 14th International Conference on Educational Data Mining (EDM 2021), 2021

Contrastive Learning in Neural Tensor Networks using Asymmetric Examples.

Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Interpretable Explanations for Probabilistic Inference in Markov Logic.

Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Ensemble Classifiers for Network Intrusion Detection Using a Novel Network Attack Dataset.

Ahmed M. Mahfouz, Abdullah Abuhussein, Deepak Venugopal, Sajjan G. Shiva

Future Internet, 2020

Taxonomy and Survey of Interpretable Machine Learning Method.

Saikat Das, Namita Agarwal, Deepak Venugopal, Frederick T. Sheldon, Sajjan G. Shiva

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space.

Anik Khan, Kishor Datta Gupta, Deepak Venugopal, Nirman Kumar

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Empirical Evaluation of the Ensemble Framework for Feature Selection in DDoS Attack.

Saikat Das, Deepak Venugopal, Sajjan G. Shiva, Frederick T. Sheldon

Proceedings of the 7th IEEE International Conference on Cyber Security and Cloud Computing, 2020

Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks.

Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Detecting Anomalous Online Reviewers: An Unsupervised Approach Using Mixture Models.

Naveen Kumar, Deepak Venugopal, Liangfei Qiu, Subodha Kumar

J. Manag. Inf. Syst., 2019

DDoS Intrusion Detection Through Machine Learning Ensemble.

Saikat Das, Ahmed M. Mahfouz, Deepak Venugopal, Sajjan G. Shiva

Proceedings of the 19th IEEE International Conference on Software Quality, 2019

Fine-Grained Explanations Using Markov Logic.

Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Comparative Analysis of ML Classifiers for Network Intrusion Detection.

Ahmed M. Mahfouz, Deepak Venugopal, Sajjan G. Shiva

Proceedings of the Fourth International Congress on Information and Communication Technology, 2019

Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models.

Craig Kelly, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

On Lifted Inference Using Neural Embeddings.

Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal

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

2018

Detecting Review Manipulation on Online Platforms with Hierarchical Supervised Learning.

Naveen Kumar, Deepak Venugopal, Liangfei Qiu, Subodha Kumar

J. Manag. Inf. Syst., 2018

Fine-Grained Crime Prediction in an Urban Neighborhood.

Christopher Kent, Deepak Venugopal

Proceedings of the IEEE International Smart Cities Conference, 2018

Scaling up Inference in MLNs with Spark.

Mohammad Maminur Islam, Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Efficient Weight Learning in High-Dimensional Untied MLNs.

Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Learning Mixtures of MLNs.

Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal

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

2017

Advances in Inference Methods for Markov Logic Networks.

Deepak Venugopal

IEEE Intell. Informatics Bull., 2017

Adaptive blocked Gibbs sampling for inference in probabilistic graphical models.

Mohammad Maminur Islam, Mohammad Khan Al Farabi, Deepak Venugopal

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Efficient Inference for Untied MLNs.

Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs.

Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Joint Inference for Mode Identification in Tutorial Dialogues.

Deepak Venugopal, Vasile Rus

Proceedings of the COLING 2016, 2016

Joint Inference for Event Coreference Resolution.

Jing Lu, Deepak Venugopal, Vibhav Gogate, Vincent Ng

Proceedings of the COLING 2016, 2016

Scalable Training of Markov Logic Networks Using Approximate Counting.

Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla, Vibhav Gogate

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs.

Deepak Venugopal, Somdeb Sarkhel, Vibhav Gogate

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

Scaling-Up Inference in Markov Logic.

Deepak Venugopal

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

2014

Evidence-Based Clustering for Scalable Inference in Markov Logic.

Deepak Venugopal, Vibhav Gogate

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Scaling-up Importance Sampling for Markov Logic Networks.

Deepak Venugopal, Vibhav Gogate

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

An Integer Polynomial Programming Based Framework for Lifted MAP Inference.

Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features.

Deepak Venugopal, Chen Chen, Vibhav Gogate, Vincent Ng

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

Lifted MAP Inference for Markov Logic Networks.

Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Dynamic Blocking and Collapsing for Gibbs Sampling.

Deepak Venugopal, Vibhav Gogate

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

GiSS: Combining Gibbs Sampling and SampleSearch for Inference in Mixed Probabilistic and Deterministic Graphical Models.

Deepak Venugopal, Vibhav Gogate

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012

On Lifting the Gibbs Sampling Algorithm.

Deepak Venugopal, Vibhav Gogate

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

Advances in Lifted Importance Sampling.

Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal

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

2008

Efficient signature based malware detection on mobile devices.

Deepak Venugopal, Guoning Hu

Mob. Inf. Syst., 2008

2007

A Malware Signature Extraction and Detection Method Applied to Mobile Networks.

Guoning Hu, Deepak Venugopal

Proceedings of the 26th IEEE International Performance Computing and Communications Conference, 2007

2006

An efficient signature representation and matching method for mobile devices.

Deepak Venugopal

Proceedings of the 2nd International ICST Conference on Wireless Internet, 2006

Intelligent virus detection on mobile devices.

Deepak Venugopal, Guoning Hu, Nicoleta Roman

Proceedings of the 2006 International Conference on Privacy, 2006