Varun Chandola

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 58

Top Topics

Large Deviations

Multivariate Time Series Data

International Workshop

Top Venues

ACM SIGSPATIAL Special

Publications

Suchismit Mahapatra, Varun Chandola
Learning manifolds from non-stationary streams. J. Big Data 11 (1) (2024)
Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola
Physics informed machine learning for chemistry tabulation. J. Comput. Sci. 69 (2023)
Sreelekha Guggilam, Varun Chandola, Abani K. Patra
Large Deviations for Accelerating Neural Networks Training. CoRR (2023)
Sreelekha Guggilam, Varun Chandola, Abani K. Patra
Large Deviations Anomaly Detection (LAD) for collection of multivariate time series data: Applications to COVID-19 data. J. Comput. Sci. 72 (2023)
Syed Mohammed Arshad Zaidi, Varun Chandola, Eun-Hye Enki Yoo
Geo-Adaptive Deep Spatio-Temporal predictive modeling for human mobility. CoRR (2022)
Pranav Sankhe, Seventy F. Hall, Melanie Sage, Maria Y. Rodriguez, Varun Chandola, Kenneth Joseph
Mutual Information Scoring: Increasing Interpretability in Categorical Clustering Tasks with Applications to Child Welfare Data. SBP-BRiMS (2022)
Sreelekha Guggilam, Varun Chandola, Abani K. Patra
Tracking clusters and anomalies in evolving data streams. Stat. Anal. Data Min. 15 (2) (2022)
Amol Salunkhe, Georgios Georgalis, Abani K. Patra, Varun Chandola
An Ensemble-Based Deep Framework for Estimating Thermo-Chemical State Variables from Flamelet Generated Manifolds. CoRR (2022)
Ashwin Shashidharan, Krishna Karthik Gadiraju, Ranga Raju Vatsavai, Varun Chandola
The 10th ACM SIGSPATIAL International Workshop on Analytics for Big Spatial Data (BigSpatial 2022). ACM SIGSPATIAL Special 14 (1) (2022)
Sreelekha Guggilam, Varun Chandola, Abani K. Patra
Classifying Anomalous Members in a Collection of Multivariate Time Series Data Using Large Deviations Principle: An Application to COVID-19 Data. ICCS (1) (2022)
Amol Salunkhe, Dwyer Deighan, Paul DesJardin, Varun Chandola
ChemTab: A Physics Guided Chemistry Modeling Framework. CoRR (2022)
Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola
ChemTab: A Physics Guided Chemistry Modeling Framework. ICCS (1) (2022)
Pranav Sankhe, Seventy F. Hall, Melanie Sage, Maria Y. Rodriguez, Varun Chandola, Kenneth Joseph
Mutual Information Scoring: Increasing Interpretability in Categorical Clustering Tasks with Applications to Child Welfare Data. CoRR (2022)
Amol Salunkhe, Dwyer Deighan, Paul E. DesJardin, Varun Chandola
Physics Informed Machine Learning for Chemistry Tabulation. CoRR (2022)
Namit Juneja, Jaroslaw Zola, Varun Chandola, Olga Wodo
Graph-based Strategy for Establishing Morphology Similarity. SSDBM (2021)
Jialiang Jiang, Sharon Hewner, Varun Chandola
Explainable Deep Learning for Readmission Prediction with Tree-GloVe Embedding. ICHI (2021)
Syed Mohammed Arshad Zaidi, Varun Chandola, Eun-Hye Enki Yoo
DST-Predict: Predicting Individual Mobility Patterns From Mobile Phone GPS Data. IEEE Access 9 (2021)
Marc Böhlen, Varun Chandola, Wawan Sujarwo, Raunaq Jain
From images in the wild to video-informed image classification. CoRR (2021)
Marc Böhlen, Raunaq Jain, Wawan Sujarwo, Varun Chandola
From images in the wild to video-informed image classification. ICMLA (2021)
Sreelekha Guggilam, Varun Chandola, Abani K. Patra
Anomaly Detection for High-Dimensional Data Using Large Deviations Principle. CoRR (2021)
Ashwin Shashidharan, Varun Chandola, Ranga Raju Vatsavai
The 9th ACM SIGSPATIAL International Workshop on Analytics for Big Spatial Data (BigSpatial 2020): November 3, 2020. ACM SIGSPATIAL Special 12 (3) (2020)
Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola
Learning Manifolds from Dynamic Process Data. Algorithms 13 (2) (2020)
Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra
Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data. ICCS (4) (2019)
Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra
Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised). CoRR (2019)
Jialiang Jiang, Sharon Hewner, Varun Chandola
Tree-based Regularization for Interpretable Readmission Prediction. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2019)
Duc Thanh Anh Luong, Varun Chandola
Learning Deep Representations from Clinical Data for Chronic Kidney Disease. ICHI (2019)
Duc Thanh Anh Luong, Prerna Singh, Mahin Ramezani, Varun Chandola
longSil: an Evaluation Metric to Assess Quality of Clustering Longitudinal Clinical Data. J. Heal. Informatics Res. 3 (4) (2019)
Ashwin Shashidharan, Varun Chandola, Ranga Raju Vatsavai
The Eighth ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data: Chicago, IL, USA - November 5, 2019. ACM SIGSPATIAL Special 11 (3) (2019)
Niyazi Sorkunlu, Duc Thanh Anh Luong, Varun Chandola
dynamicMF: A Matrix Factorization Approach to Monitor Resource Usage in High Performance Computing Systems. CoRR (2018)
Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes. CoRR (2018)
Jialiang Jiang, Sharon Hewner, Varun Chandola
Hospital Readmission Prediction - Applying Hierarchical Sparsity Norms for Interpretable Models. CoRR (2018)
Ting Xie, Oliver Kennedy, Varun Chandola
Query Log Compression for Workload Analytics. CoRR (2018)
Arun Sharma, Syed Mohammed Arshad Zaidi, Varun Chandola, Melissa R. Allen, Budhendra L. Bhaduri
WebGIobe - A cloud-based geospatial analysis framework for interacting with climate data. BigSpatial@SIGSPATIAL (2018)
Gökhan Kul, Duc Thanh Anh Luong, Ting Xie, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya
Similarity Metrics for SQL Query Clustering. IEEE Trans. Knowl. Data Eng. 30 (12) (2018)
Ting Xie, Varun Chandola, Oliver Kennedy
Query Log Compression for Workload Analytics. Proc. VLDB Endow. 12 (3) (2018)
Gökhan Kul, Shambhu J. Upadhyaya, Varun Chandola
Detecting Data Leakage from Databases on Android Apps with Concept Drift. CoRR (2018)
Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes. IEEE BigData (2018)
Gökhan Kul, Shambhu J. Upadhyaya, Varun Chandola
Detecting Data Leakage from Databases on Android Apps with Concept Drift. TrustCom/BigDataSE (2018)
Suchismit Mahapatra, Varun Chandola
Learning Manifolds from Non-stationary Streaming Data. CoRR (2018)
Varun Chandola, Ranga Raju Vatsavai
The seventh ACM SIGSPATIAL international workshop on analysis for big spatial data seattle, wa, USA - November 6, 2018. ACM SIGSPATIAL Special 10 (3) (2018)
Niyazi Sorkunlu, Duc Thanh Anh Luong, Varun Chandola
dynamicMF: A Matrix Factorization Approach to Monitor Resource Usage in High Performance Computing Systems. IEEE BigData (2018)
Duc Thanh Anh Luong, Varun Chandola
An Empirical Evaluation of Time-Aware LSTM Autoencoder on Chronic Kidney Disease. CoRR (2018)
Frank Schoeneman, Suchismit Mahapatra, Varun Chandola, Nils Napp, Jaroslaw Zola
Error Metrics for Learning Reliable Manifolds from Streaming Data. SDM (2017)
Niyazi Sorkunlu, Varun Chandola, Abani K. Patra
Tracking System Behaviour from Resource Usage Data. CoRR (2017)
Suchismit Mahapatra, Varun Chandola
S-Isomap++: Multi Manifold Learning from Streaming Data. CoRR (2017)
Suchismit Mahapatra, Varun Chandola
S-Isomap++: Multi manifold learning from streaming data. IEEE BigData (2017)
Suchismit Mahapatra, Varun Chandola
Modeling Graphs Using a Mixture of Kronecker Models. CoRR (2017)
Varun Chandola, Ranga Raju Vatsavai
The Sixth ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data: Redondo Beach, CA, USA - November 7, 2017. ACM SIGSPATIAL Special 9 (3) (2017)
Duc Thanh Anh Luong, Varun Chandola
A K-Means Approach to Clustering Disease Progressions. ICHI (2017)
Marc Böhlen, Varun Chandola, Amol Salunkhe
Server, server in the cloud. Who is the fairest in the crowd? CoRR (2017)
Prerna Singh, Varun Chandola, Chester H. Fox
Automatic Extraction of Deep Phenotypes for Precision Medicine in Chronic Kidney Disease. DH (2017)
Niyazi Sorkunlu, Varun Chandola, Abani K. Patra
Tracking System Behavior from Resource Usage Data. CLUSTER (2017)
Ranga Raju Vatsavai, Varun Chandola
Guest editorial: big spatial data. GeoInformatica 20 (4) (2016)
Gökhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya
Summarizing Large Query Logs in Ettu. CoRR (2016)
Gökhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy, Shambhu J. Upadhyaya
Ettu: Analyzing Query Intents in Corporate Databases. WWW (Companion Volume) (2016)
Suchismit Mahapatra, Varun Chandola
Modeling graphs using a mixture of Kronecker models. IEEE BigData (2015)
Zhi Yang, Varun Chandola
Surface Reconstruction from Intensity Image Using Illumination Model Based Morphable Modeling. ICVS (2015)
Varun Chandola, Ranga Raju Vatsavai
The Third ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data Dallas, Texas, USA - November 4, 2014. ACM SIGSPATIAL Special 7 (2) (2015)
Varun Chandola, Varun Mithal, Vipin Kumar
A reference based analysis framework for understanding anomaly detection techniques for symbolic sequences. Data Min. Knowl. Discov. 28 (3) (2014)
Paul T. Bauman, Varun Chandola, Abani K. Patra, Matthew D. Jones
Development of a computational and data-enabled science and engineering Ph.D. program. EduHPC@SC (2014)
Varun Chandola, Ranga Raju Vatsavai
BigSpatial-2013 workshop report: 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial-2013): Nov 5, 2013, Orlando, Florida, USA. ACM SIGSPATIAL Special 6 (1) (2014)
Varun Chandola, Sreenivas R. Sukumar, Jack C. Schryver
Knowledge discovery from massive healthcare claims data. KDD (2013)
Ranga Raju Vatsavai, Auroop R. Ganguly, Varun Chandola, Anthony Stefanidis, Scott Klasky, Shashi Shekhar
Spatiotemporal data mining in the era of big spatial data: algorithms and applications. BigSpatial@SIGSPATIAL (2012)
Varun Chandola, Arindam Banerjee, Vipin Kumar
Anomaly Detection for Discrete Sequences: A Survey. IEEE Trans. Knowl. Data Eng. 24 (5) (2012)
Jordan Graesser, Anil M. Cheriyadat, Ranga Raju Vatsavai, Varun Chandola, Jordan Long, Eddie A. Bright
Image Based Characterization of Formal and Informal Neighborhoods in an Urban Landscape. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 5 (4) (2012)
Varun Chandola, Ranga Raju Vatsavai
A scalable gaussian process analysis algorithm for biomass monitoring. Stat. Anal. Data Min. 4 (4) (2011)
Ranga Raju Vatsavai, Mark Tuttle, Budhendra L. Bhaduri, Edward Bright, Anil M. Cheriyadat, Varun Chandola, Jordan Graesser
Rapid damage assessment using high-resolution remote sensing imagery: Tools and techniques. IGARSS (2011)
Varun Chandola, Ranga Raju Vatsavai, Budhendra L. Bhaduri
iGlobe: an interactive visualization and analysis framework for geospatial data. COM.Geo (2011)
Ranga Raju Vatsavai, Eddie A. Bright, Varun Chandola, Budhendra L. Bhaduri, Anil M. Cheriyadat, Jordan Graesser
Machine learning approaches for high-resolution urban land cover classification: a comparative study. COM.Geo (2011)
Varun Chandola, Ranga Raju Vatsavai
Implementing a gaussian process learning algorithm in mixed parallel environment. ScalA@SC (2011)
Ranga Raju Vatsavai, Christopher T. Symons, Varun Chandola, Goo Jun
GX-Means: A model-based divide and merge algorithm for geospatial image clustering. ICCS (2011)
Varun Chandola, Ranga Raju Vatsavai
A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series. SDM (2011)
Varun Chandola, Ranga Raju Vatsavai
Scalable Time Series Change Detection for Biomass Monitoring Using Gaussian Process. CIDU (2010)
Varun Chandola, Dafeng Hui, Lianhong Gu, Budhendra L. Bhaduri, Ranga Raju Vatsavai
Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data. ICDM Workshops (2010)
Varun Chandola, Ranga Raju Vatsavai
Multi-temporal remote sensing image classification - A multi-view approach. CIDU (2010)
Varun Chandola, Shyam Boriah, Vipin Kumar
A reference based analysis framework for analyzing system call traces. CSIIRW (2010)
Varun Chandola, Olufemi A. Omitaomu, Auroop R. Ganguly, Ranga Raju Vatsavai, Nitesh V. Chawla, João Gama, Mohamed Medhat Gaber
Knowledge discovery from sensor data (SensorKDD). SIGKDD Explor. 12 (2) (2010)
Varun Chandola, Arindam Banerjee, Vipin Kumar
Anomaly detection: A survey. ACM Comput. Surv. 41 (3) (2009)
Varun Chandola, Shyam Boriah, Vipin Kumar
A Framework for Exploring Categorical Data. SDM (2009)
Varun Chandola, Varun Mithal, Vipin Kumar
Comparative Evaluation of Anomaly Detection Techniques for Sequence Data. ICDM (2008)
Shyam Boriah, Varun Chandola, Vipin Kumar
Similarity Measures for Categorical Data: A Comparative Evaluation. SDM (2008)
Varun Chandola, Vipin Kumar
Summarization - compressing data into an informative representation. Knowl. Inf. Syst. 12 (3) (2007)
Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric Eilertson, Levent Ertöz, György J. Simon, Seonho Kim, Jinoh Kim
DDDAS/ITR: A Data Mining and Exploration Middleware for Grid and Distributed Computing. International Conference on Computational Science (1) (2007)
Varun Chandola, Vipin Kumar
Summarization - Compressing Data into an Informative Representation. ICDM (2005)