Varun Chandola

According to our database, Varun Chandola authored at least 76 papers between 2007 and 2024.

Collaborative distances:

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

2024

Learning manifolds from non-stationary streams.

Suchismit Mahapatra, Varun Chandola

J. Big Data, December, 2024

Resource Efficient Bayesian Optimization.

Namit Juneja, Varun Chandola, Jaroslaw Zola, Olga Wodo, Parth Desai

Proceedings of the 17th IEEE International Conference on Cloud Computing, 2024

2023

Large Deviations Anomaly Detection (LAD) for collection of multivariate time series data: Applications to COVID-19 data.

Sreelekha Guggilam, Varun Chandola, Abani K. Patra

J. Comput. Sci., September, 2023

Physics informed machine learning for chemistry tabulation.

Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola

J. Comput. Sci., May, 2023

Large Deviations for Accelerating Neural Networks Training.

Sreelekha Guggilam, Varun Chandola, Abani K. Patra

CoRR, 2023

2022

The 10th ACM SIGSPATIAL International Workshop on Analytics for Big Spatial Data (BigSpatial 2022).

Ashwin Shashidharan, Krishna Karthik Gadiraju, Ranga Raju Vatsavai, Varun Chandola

ACM SIGSPATIAL Special, November, 2022

Tracking clusters and anomalies in evolving data streams.

Sreelekha Guggilam, Varun Chandola, Abani K. Patra

Stat. Anal. Data Min., 2022

Geo-Adaptive Deep Spatio-Temporal predictive modeling for human mobility.

Syed Mohammed Arshad Zaidi, Varun Chandola, Eun-Hye Enki Yoo

CoRR, 2022

An Ensemble-Based Deep Framework for Estimating Thermo-Chemical State Variables from Flamelet Generated Manifolds.

Amol Salunkhe, Georgios Georgalis, Abani K. Patra, Varun Chandola

CoRR, 2022

Mutual Information Scoring: Increasing Interpretability in Categorical Clustering Tasks with Applications to Child Welfare Data.

Pranav Sankhe, Seventy F. Hall, Melanie D. Sage, Maria Y. Rodriguez, Varun Chandola, Kenneth Joseph

Proceedings of the Social, Cultural, and Behavioral Modeling, 2022

ChemTab: A Physics Guided Chemistry Modeling Framework.

Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola

Proceedings of the Computational Science - ICCS 2022, 2022

Classifying Anomalous Members in a Collection of Multivariate Time Series Data Using Large Deviations Principle: An Application to COVID-19 Data.

Sreelekha Guggilam, Varun Chandola, Abani K. Patra

Proceedings of the Computational Science - ICCS 2022, 2022

2021

Anomaly Detection for High-Dimensional Data Using Large Deviations Principle.

Sreelekha Guggilam, Varun Chandola, Abani K. Patra

CoRR, 2021

DST-Predict: Predicting Individual Mobility Patterns From Mobile Phone GPS Data.

Syed Mohammed Arshad Zaidi, Varun Chandola, Eun-Hye Enki Yoo

IEEE Access, 2021

Graph-based Strategy for Establishing Morphology Similarity.

Namit Juneja, Jaroslaw Zola, Varun Chandola, Olga Wodo

Proceedings of the SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, 2021

From images in the wild to video-informed image classification.

Marc Böhlen, Raunaq Jain, Wawan Sujarwo, Varun Chandola

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Explainable Deep Learning for Readmission Prediction with Tree-GloVe Embedding.

Jialiang Jiang, Sharon Hewner, Varun Chandola

Proceedings of the 9th IEEE International Conference on Healthcare Informatics, 2021

2020

The 9th ACM SIGSPATIAL International Workshop on Analytics for Big Spatial Data (BigSpatial 2020): November 3, 2020.

Ashwin Shashidharan, Varun Chandola, Ranga Raju Vatsavai

ACM SIGSPATIAL Special, 2020

Learning Manifolds from Dynamic Process Data.

Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola

Algorithms, 2020

2019

The Eighth ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data: Chicago, IL, USA - November 5, 2019.

Ashwin Shashidharan, Varun Chandola, Ranga Raju Vatsavai

ACM SIGSPATIAL Special, 2019

longSil: an Evaluation Metric to Assess Quality of Clustering Longitudinal Clinical Data.

Duc Thanh Anh Luong, Prerna Singh, Mahin Ramezani, Varun Chandola

J. Heal. Informatics Res., 2019

Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised).

Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra

CoRR, 2019

Learning Deep Representations from Clinical Data for Chronic Kidney Disease.

Duc Thanh Anh Luong, Varun Chandola

Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019

Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data.

Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra

Proceedings of the Computational Science - ICCS 2019, 2019

Tree-based Regularization for Interpretable Readmission Prediction.

Jialiang Jiang, Sharon Hewner, Varun Chandola

Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019) Stanford University, 2019

2018

Similarity Metrics for SQL Query Clustering.

Gökhan Kul, Duc Thanh Anh Luong, Ting Xie, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya

IEEE Trans. Knowl. Data Eng., 2018

The seventh ACM SIGSPATIAL international workshop on analysis for big spatial data seattle, wa, USA - November 6, 2018.

Varun Chandola, Ranga Raju Vatsavai

ACM SIGSPATIAL Special, 2018

Query Log Compression for Workload Analytics.

Ting Xie, Varun Chandola, Oliver Kennedy

Proc. VLDB Endow., 2018

An Empirical Evaluation of Time-Aware LSTM Autoencoder on Chronic Kidney Disease.

Duc Thanh Anh Luong, Varun Chandola

CoRR, 2018

Learning Manifolds from Non-stationary Streaming Data.

Suchismit Mahapatra, Varun Chandola

CoRR, 2018

Hospital Readmission Prediction - Applying Hierarchical Sparsity Norms for Interpretable Models.

Jialiang Jiang, Sharon Hewner, Varun Chandola

CoRR, 2018

Detecting Data Leakage from Databases on Android Apps with Concept Drift.

Gökhan Kul, Shambhu J. Upadhyaya, Varun Chandola

Proceedings of the 17th IEEE International Conference On Trust, 2018

WebGIobe - A cloud-based geospatial analysis framework for interacting with climate data.

Arun Sharma, Syed Mohammed Arshad Zaidi, Varun Chandola, Melissa R. Allen, Budhendra L. Bhaduri

Proceedings of the 7th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, 2018

dynamicMF: A Matrix Factorization Approach to Monitor Resource Usage in High Performance Computing Systems.

Niyazi Sorkunlu, Duc Thanh Anh Luong, Varun Chandola

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

Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes.

Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola

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

2017

Active Learning.

Varun Chandola, Arindam Banerjee, Vipin Kumar

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

The Sixth ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data: Redondo Beach, CA, USA - November 7, 2017.

Varun Chandola, Ranga Raju Vatsavai

ACM SIGSPATIAL Special, 2017

Server, server in the cloud. Who is the fairest in the crowd?

Marc Böhlen, Varun Chandola, Amol Salunkhe

CoRR, 2017

Tracking System Behaviour from Resource Usage Data.

Niyazi Sorkunlu, Varun Chandola, Abani K. Patra

CoRR, 2017

Error Metrics for Learning Reliable Manifolds from Streaming Data.

Frank Schoeneman, Suchismit Mahapatra, Varun Chandola, Nils Napp, Jaroslaw Zola

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

A K-Means Approach to Clustering Disease Progressions.

Duc Thanh Anh Luong, Varun Chandola

Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 2017

Automatic Extraction of Deep Phenotypes for Precision Medicine in Chronic Kidney Disease.

Prerna Singh, Varun Chandola, Chester H. Fox

Proceedings of the 2017 International Conference on Digital Health, 2017

Tracking System Behavior from Resource Usage Data.

Niyazi Sorkunlu, Varun Chandola, Abani K. Patra

Proceedings of the 2017 IEEE International Conference on Cluster Computing, 2017

S-Isomap++: Multi manifold learning from streaming data.

Suchismit Mahapatra, Varun Chandola

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

Guest editorial: big spatial data.

Ranga Raju Vatsavai, Varun Chandola

GeoInformatica, 2016

Summarizing Large Query Logs in Ettu.

Gökhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya

CoRR, 2016

Ettu: Analyzing Query Intents in Corporate Databases.

Gökhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya

Proceedings of the 25th International Conference on World Wide Web, 2016

2015

The Third ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data Dallas, Texas, USA - November 4, 2014.

Varun Chandola, Ranga Raju Vatsavai

ACM SIGSPATIAL Special, 2015

Surface Reconstruction from Intensity Image Using Illumination Model Based Morphable Modeling.

Zhi Yang, Varun Chandola

Proceedings of the Computer Vision Systems - 10th International Conference, 2015

Modeling graphs using a mixture of Kronecker models.

Suchismit Mahapatra, Varun Chandola

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

Fraud Detection in Healthcare.

Varun Chandola, Jack C. Schryver, Sreenivas R. Sukumar

Proceedings of the Healthcare Data Analytics., 2015

2014

BigSpatial-2013 workshop report: 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial-2013): Nov 5, 2013, Orlando, Florida, USA.

Varun Chandola, Ranga Raju Vatsavai

ACM SIGSPATIAL Special, 2014

A reference based analysis framework for understanding anomaly detection techniques for symbolic sequences.

Varun Chandola, Varun Mithal, Vipin Kumar

Data Min. Knowl. Discov., 2014

Development of a computational and data-enabled science and engineering Ph.D. program.

Paul T. Bauman, Varun Chandola, Abani K. Patra, Matthew D. Jones

Proceedings of the Workshop on Education for High-Performance Computing, 2014

2013

Knowledge discovery from massive healthcare claims data.

Varun Chandola, Sreenivas R. Sukumar, Jack C. Schryver

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012

Anomaly Detection for Discrete Sequences: A Survey.

Varun Chandola, Arindam Banerjee, Vipin Kumar

IEEE Trans. Knowl. Data Eng., 2012

Image Based Characterization of Formal and Informal Neighborhoods in an Urban Landscape.

Jordan Graesser, Anil M. Cheriyadat, Ranga Raju Vatsavai, Varun Chandola, Jordan Long, Eddie A. Bright

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2012

Spatiotemporal data mining in the era of big spatial data: algorithms and applications.

Ranga Raju Vatsavai, Auroop R. Ganguly, Varun Chandola, Anthony Stefanidis, Scott Klasky, Shashi Shekhar

Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, 2012

2011

A scalable gaussian process analysis algorithm for biomass monitoring.

Varun Chandola, Ranga Raju Vatsavai

Stat. Anal. Data Min., 2011

GX-Means: A model-based divide and merge algorithm for geospatial image clustering.

Ranga Raju Vatsavai, Christopher T. Symons, Varun Chandola, Goo Jun

Proceedings of the International Conference on Computational Science, 2011

A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series.

Varun Chandola, Ranga Raju Vatsavai

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Implementing a gaussian process learning algorithm in mixed parallel environment.

Varun Chandola, Ranga Raju Vatsavai

Proceedings of the second workshop on Scalable algorithms for large-scale systems, 2011

Rapid damage assessment using high-resolution remote sensing imagery: Tools and techniques.

Ranga Raju Vatsavai, Mark A. Tuttle, Budhendra L. Bhaduri, Edward Bright, Anil M. Cheriyadat, Varun Chandola, Jordan Graesser

Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011

Machine learning approaches for high-resolution urban land cover classification: a comparative study.

Ranga Raju Vatsavai, Eddie A. Bright, Varun Chandola, Budhendra L. Bhaduri, Anil M. Cheriyadat, Jordan Graesser

Proceedings of the 2nd International Conference and Exhibition on Computing for Geospatial Research & Application, 2011

iGlobe: an interactive visualization and analysis framework for geospatial data.

Varun Chandola, Ranga Raju Vatsavai, Budhendra L. Bhaduri

Proceedings of the 2nd International Conference and Exhibition on Computing for Geospatial Research & Application, 2011

2010

Knowledge discovery from sensor data (SensorKDD).

Varun Chandola, Olufemi A. Omitaomu, Auroop R. Ganguly, Ranga Raju Vatsavai, Nitesh V. Chawla, João Gama, Mohamed Medhat Gaber

SIGKDD Explor., 2010

Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data.

Varun Chandola, Dafeng Hui, Lianhong Gu, Budhendra L. Bhaduri, Ranga Raju Vatsavai

Proceedings of the ICDMW 2010, 2010

A reference based analysis framework for analyzing system call traces.

Varun Chandola, Shyam Boriah, Vipin Kumar

Proceedings of the 6th Cyber Security and Information Intelligence Research Workshop, 2010

Multi-temporal remote sensing image classification - A multi-view approach.

Varun Chandola, Ranga Raju Vatsavai

Proceedings of the 2010 Conference on Intelligent Data Understanding, 2010

Scalable Time Series Change Detection for Biomass Monitoring Using Gaussian Process.

Varun Chandola, Ranga Raju Vatsavai

Proceedings of the 2010 Conference on Intelligent Data Understanding, 2010

2009

Anomaly detection: A survey.

Varun Chandola, Arindam Banerjee, Vipin Kumar

ACM Comput. Surv., 2009

A Framework for Exploring Categorical Data.

Varun Chandola, Shyam Boriah, Vipin Kumar

Proceedings of the SIAM International Conference on Data Mining, 2009

2008

Similarity Measures for Categorical Data: A Comparative Evaluation.

Shyam Boriah, Varun Chandola, Vipin Kumar

Proceedings of the SIAM International Conference on Data Mining, 2008

Comparative Evaluation of Anomaly Detection Techniques for Sequence Data.

Varun Chandola, Varun Mithal, Vipin Kumar

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007

Summarization - compressing data into an informative representation.

Varun Chandola, Vipin Kumar

Knowl. Inf. Syst., 2007

DDDAS/ITR: A Data Mining and Exploration Middleware for Grid and Distributed Computing.

Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric Eilertson, Levent Ertöz, György J. Simon, Seonho Kim, Jinoh Kim

Proceedings of the Computational Science, 2007