Deepak Venugopal

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 41

Top Topics

Intrusion Detection

Intelligent Tutoring

Probabilistic Graphical Models

Top Venues

EDM (Workshops)

Publications

Anup Shakya, Vasile Rus, Deepak Venugopal
Mastery Guided Non-parametric Clustering to Scale-up Strategy Prediction. CoRR (2024)
Abisha Thapa Magar, Stephen E. Fancsali, Vasile Rus, April Murphy, Steven Ritter, Deepak Venugopal
Learning Representations for Math Strategies using BERT. L@S (2024)
Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal
Verifying Relational Explanations: A Probabilistic Approach. CoRR (2024)
Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
On the Verification of Embeddings with Hybrid Markov Logic. ICDM (2023)
Anup Shakya, Vasile Rus, Deepak Venugopal
Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. EDM (2023)
Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
On the verification of Embeddings using Hybrid Markov Logic. CoRR (2023)
Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal
Verifying Relational Explanations: A Probabilistic Approach. BigData (2023)
Anup Shakya, Vasile Rus, Deepak Venugopal
Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. CoRR (2023)
William Britton, Somdeb Sarkhel, Deepak Venugopal
Question Modifiers in Visual Question Answering. LREC (2022)
Monika Shah, Somdeb Sarkhel, Deepak Venugopal
Evaluating Captioning Models using Markov Logic Networks. Big Data (2022)
Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal
Interpretable Explanations for Probabilistic Inference in Markov Logic. IEEE BigData (2021)
Vasile Rus, Stephen E. Fancsali, Philip I. Pavlik Jr., Deepak Venugopal, Arthur C. Graesser, Steven Ritter, Dale Bowman, The L. D. I. Team
The Learner Data Institute - Conceptualization: A Progress Report. EDM (Workshops) (2021)
Sambriddhi Mainali, Max H. Garzon, Deepak Venugopal, Kalidas Jana, Ching-Chi Yang, Nirman Kumar, Dale Bowman, Lih-Yuan Deng
An Information-theoretic approach to dimensionality reduction in data science. Int. J. Data Sci. Anal. 12 (3) (2021)
Anup Shakya, Vasile Rus, Deepak Venugopal
Student Strategy Prediction using a Neuro-Symbolic Approach. EDM (2021)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
Contrastive Learning in Neural Tensor Networks using Asymmetric Examples. IEEE BigData (2021)
Deepak Venugopal, Vasile Rus, Anup Shakya
Neuro-Symbolic Models: A Scalable, Explainable Framework for Strategy Discovery from Big Edu-Data. EDM (Workshops) (2021)
Leigh M. Harrell-Williams, Christian Mueller, Stephen Fancsali, Steven Ritter, Xiaofei Zhang, Deepak Venugopal
The Nature of Achievement Goal Motivation Profiles: Exploring Situational Motivation in An Algebra-Focused Intelligent Tutoring System. EDM (Workshops) (2021)
Anik Khan, Kishor Datta Gupta, Deepak Venugopal, Nirman Kumar
CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space. CoRR (2020)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks. IEEE BigData (2020)
Saikat Das, Deepak Venugopal, Sajjan G. Shiva, Frederick T. Sheldon
Empirical Evaluation of the Ensemble Framework for Feature Selection in DDoS Attack. CSCloud/EdgeCom (2020)
Ahmed M. Mahfouz, Abdullah Abuhussein, Deepak Venugopal, Sajjan G. Shiva
Ensemble Classifiers for Network Intrusion Detection Using a Novel Network Attack Dataset. Future Internet 12 (11) (2020)
Anik Khan, Kishor Datta Gupta, Deepak Venugopal, Nirman Kumar
CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space. IJCNN (2020)
Saikat Das, Namita Agarwal, Deepak Venugopal, Frederick T. Sheldon, Sajjan G. Shiva
Taxonomy and Survey of Interpretable Machine Learning Method. SSCI (2020)
Craig Kelly, Somdeb Sarkhel, Deepak Venugopal
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models. AISTATS (2019)
Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal
Fine-Grained Explanations Using Markov Logic. ECML/PKDD (2) (2019)
Naveen Kumar, Deepak Venugopal, Liangfei Qiu, Subodha Kumar
Detecting Anomalous Online Reviewers: An Unsupervised Approach Using Mixture Models. J. Manag. Inf. Syst. 36 (4) (2019)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
On Lifted Inference Using Neural Embeddings. AAAI (2019)
Saikat Das, Ahmed M. Mahfouz, Deepak Venugopal, Sajjan G. Shiva
DDoS Intrusion Detection Through Machine Learning Ensemble. QRS Companion (2019)
Ahmed M. Mahfouz, Deepak Venugopal, Sajjan G. Shiva
Comparative Analysis of ML Classifiers for Network Intrusion Detection. ICICT (2) (2019)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
Learning Mixtures of MLNs. AAAI (2018)
Naveen Kumar, Deepak Venugopal, Liangfei Qiu, Subodha Kumar
Detecting Review Manipulation on Online Platforms with Hierarchical Supervised Learning. J. Manag. Inf. Syst. 35 (1) (2018)
Christopher Kent, Deepak Venugopal
Fine-Grained Crime Prediction in an Urban Neighborhood. ISC2 (2018)
Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal
Efficient Weight Learning in High-Dimensional Untied MLNs. AISTATS (2018)
Mohammad Maminur Islam, Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal
Scaling up Inference in MLNs with Spark. IEEE BigData (2018)
Mohammad Maminur Islam, Mohammad Khan Al Farabi, Deepak Venugopal
Adaptive blocked Gibbs sampling for inference in probabilistic graphical models. IJCNN (2017)
Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate
Efficient Inference for Untied MLNs. IJCAI (2017)
Deepak Venugopal
Advances in Inference Methods for Markov Logic Networks. IEEE Intell. Informatics Bull. 18 (2) (2017)
Deepak Venugopal, Vasile Rus
Joint Inference for Mode Identification in Tutorial Dialogues. COLING (2016)
Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla, Vibhav Gogate
Scalable Training of Markov Logic Networks Using Approximate Counting. AAAI (2016)
Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry
Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. UAI (2016)
Jing Lu, Deepak Venugopal, Vibhav Gogate, Vincent Ng
Joint Inference for Event Coreference Resolution. COLING (2016)
Deepak Venugopal, Somdeb Sarkhel, Vibhav Gogate
Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs. AAAI (2015)
Deepak Venugopal
Scaling-Up Inference in Markov Logic. AAAI (2015)
Deepak Venugopal, Chen Chen, Vibhav Gogate, Vincent Ng
Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features. EMNLP (2014)
Deepak Venugopal, Vibhav Gogate
Evidence-Based Clustering for Scalable Inference in Markov Logic. ECML/PKDD (3) (2014)
Deepak Venugopal, Vibhav Gogate
Evidence-Based Clustering for Scalable Inference in Markov Logic. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate
An Integer Polynomial Programming Based Framework for Lifted MAP Inference. NIPS (2014)
Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate
Lifted MAP Inference for Markov Logic Networks. AISTATS (2014)
Deepak Venugopal, Vibhav Gogate
Scaling-up Importance Sampling for Markov Logic Networks. NIPS (2014)
Deepak Venugopal, Vibhav Gogate
GiSS: Combining Gibbs Sampling and SampleSearch for Inference in Mixed Probabilistic and Deterministic Graphical Models. AAAI (2013)
Deepak Venugopal, Vibhav Gogate
Dynamic Blocking and Collapsing for Gibbs Sampling. UAI (2013)
Deepak Venugopal, Vibhav Gogate
Dynamic Blocking and Collapsing for Gibbs Sampling. CoRR (2013)
Deepak Venugopal, Vibhav Gogate
On Lifting the Gibbs Sampling Algorithm. NIPS (2012)
Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal
Advances in Lifted Importance Sampling. AAAI (2012)
Deepak Venugopal, Vibhav Gogate
On Lifting the Gibbs Sampling Algorithm. StarAI@UAI (2012)
Deepak Venugopal, Guoning Hu
Efficient signature based malware detection on mobile devices. Mob. Inf. Syst. 4 (1) (2008)
Guoning Hu, Deepak Venugopal
A Malware Signature Extraction and Detection Method Applied to Mobile Networks. IPCCC (2007)
Deepak Venugopal
An efficient signature representation and matching method for mobile devices. WICON (2006)
Deepak Venugopal, Guoning Hu, Nicoleta Roman
Intelligent virus detection on mobile devices. PST (2006)