Nikunj C. Oza

Ashok N. Srivastava, Nikunj C. Oza, Julienne C. Stroeve, 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

Learning to Improve Earth Observation Flight Planning

Robert A. Morris, Nikunj C. Oza, Anthony W. Strawa, 2008, AAAI.

Input Decimation Ensembles: Decorrelation through Dimensionality Reduction

Kagan Tumer, Nikunj C. Oza, 2001, Multiple Classifier Systems.

Using ADOPT Algorithm and Operational Data to Discover Precursors to Aviation Adverse Events

Nikunj C. Oza, Vijay Manikandan Janakiraman, Bryan Matthews, 2018 .

Multi-label ASRS Dataset Classification Using Semi Supervised Subspace Clustering

Latifur Khan, Mandava Rajeswari, Nikunj C. Oza, 2010, CIDU.

Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework

Vipin Kumar, Ramakrishna R. Nemani, Ankush Khandelwal, 2018, Remote. Sens..

Fast Multivariate Search on Large Aviation Datasets

Qiang Zhu, Kanishka Bhaduri, Ashok N. Srivastava, 2010 .

Applications of ensemble methods

Kagan Tumer, Nikunj C. Oza, Kagan Tumer, 2008, Information Fusion.

Facing the reality of data stream classification: coping with scarcity of labeled data

Latifur Khan, Jiawei Han, Kevin W. Hamlen, 2012, Knowledge and Information Systems.

Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms

Kanishka Bhaduri, Kamalika Das, Santanu Das, 2013, J. Aerosp. Inf. Syst..

On The Use of Network DRAM in LAPACK Programs

Nikunj C. Oza, Giao Nguyen, 1994 .

Multiple Classifier Systems, 6th International Workshop, MCS 2005, Seaside, CA, USA, June 13-15, 2005, Proceedings

Nikunj C. Oza, 2005, Multiple Classifier Systems.

Virtual sensors: using data mining techniques to efficiently estimate remote sensing spectra

Ashok N. Srivastava, Nikunj C. Oza, Julienne C. Stroeve, 2005, IEEE Transactions on Geoscience and Remote Sensing.

Ensemble Data Mining Methods

Nikunj C. Oza, N. Oza, 2009, Encyclopedia of Data Warehousing and Mining.

Classifier ensembles: Select real-world applications

Kagan Tumer, Nikunj C. Oza, Kagan Tumer, 2008, Inf. Fusion.

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

Kamalika Das, Manali Sharma, Mustafa Bilgic, 2016, ECML/PKDD.

Learning Points of Interest for Observation Flight Planning Optimization: A Preliminary Report

Robert A. Morris, Nikunj C. Oza, N. Oza, 2007 .

Fast and Flexible Multivariate Time Series Subsequence Search

Kanishka Bhaduri, Qiang Zhu, Ashok N. Srivastava, 2010, 2010 IEEE International Conference on Data Mining.

Experimental comparisons of online and batch versions of bagging and boosting

Stuart J. Russell, Nikunj C. Oza, N. Oza, 2001, KDD '01.

Dimensionality Reduction Through Classifier Ensembles

Kagan Tumer, Nikunj C. Oza, Peter Norwig, 1999 .

Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring

Mark Schwabacher, Nikunj C. Oza, Bryan Matthews, 2007, Journal of Aerospace Computing Information and Communication.

Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems

Arindam Banerjee, Hamed Valizadegan, Igor Melnyk, 2016, J. Aerosp. Inf. Syst..

Decoding the Black Box: Extracting Explainable Decision Boundary Approximations from Machine Learning Models for Real Time Safety Assurance of the National Airspace

David Miller, Jyotirmaya Nanda, Alexander Grushin, 2019 .

Online bagging and boosting

Stuart J. Russell, Nikunj C. Oza, N. Oza, 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

Anomaly Detection Techniques with Real Test Data from a Spinning Turbine Engine-Like Rotor

Mark R. Woike, Ali Abdul-Aziz, Nikunj C. Oza, 2012 .

Machine Learning for Detecting and Locating Damage in a Rotating Gear

Nikunj C. Oza, Upender K. Kaul, 2005 .

Machine Learning for Earth Observation Flight Planning Optimization

Robert A. Morris, Nikunj C. Oza, N. Oza, 2007 .

Towards Automatic Classification of Exoplanet-Transit-Like Signals: A Case Study on Kepler Mission Data

Hamed Valizadegan, Nikunj C. Oza, Rodney Martin, 2015 .

Lecture Notes in Computer Science: Preface

Fabio Roli, Robi Polikar, Josef Kittler, 2005 .

Discovery of Precursors to Adverse Events using Time Series Data

Nikunj C. Oza, Vijay Manikandan Janakiraman, Bryan L. Matthews, 2016, SDM.

Topic modeling for OLAP on multidimensional text databases: topic cube and its applications

Jiawei Han, ChengXiang Zhai, Duo Zhang, 2009 .

Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems

Kilsoo Kim, Young-Ki Lee, Sehwan Oh, 2020 .

Integrating Parallel and Distributed Data Mining Algorithms into the NASA Earth Exchange (NEX)

Ramakrishna R. Nemani, Kamalika Das, Ankush Khandelwal, 2014 .

Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study

Ashok N. Srivastava, Santanu Das, Nikunj C. Oza, 2010, KDD.

Data Mining R&D (a bit of it) for Earth Science at NASA

Nikunj C. Oza, N. Oza, 2015 .

Maneuver Classification for Aircraft Fault Detection

Irem Y. Tumer, Kagan Tumer, Edward M. Huff, 2003 .

Classification of Aircraft Maneuvers for Fault Detection

Irem Y. Tumer, Kagan Tumer, Edward M. Huff, 2003, Multiple Classifier Systems.

Rotor health monitoring combining spin tests and data-driven anomaly detection methods

Mark R. Woike, Ali Abdul-Aziz, Nikunj C. Oza, 2012 .

Anomaly Detection in a Fleet of Systems

Santanu Das, Nikunj C. Oza, 2016 .

Decimated input ensembles for improved generalization

Nikunj C. Oza, Kagan Turner, N. Oza, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

ν-Anomica: A Fast Support Vector Based Novelty Detection Technique

Kanishka Bhaduri, Ashok N. Srivastava, Santanu Das, 2009, 2009 Ninth IEEE International Conference on Data Mining.

Input decimated ensembles

Kagan Tumer, Nikunj C. Oza, Kagan Tumer, 2003, Pattern Analysis & Applications.

Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams

Charu C. Aggarwal, Latifur Khan, Jiawei Han, 2013, IEEE Transactions on Knowledge and Data Engineering.

Better Boosting with Bandits for Online Learning pdf

Gavin Brown, Joseph Mellor, Nikunj C. Oza, 2020, ArXiv.

Toward Justifiable Trust in Autonomous Systems Incorporating Human Knowledge in Autonomous Systems through Machine Learning

Kamalika Das, Nikunj C. Oza, Vijay Manikandan Janakiraman, 2018 .

Online Ensemble Learning

Nikunj C. Oza, N. Oza, 2000, AAAI/IAAI.

Theoretically Optimal Distributed Anomaly Detection

Ashutosh Tiwari, Jaideep Srivastava, Aleksandar Lazarevic, 2009, 2009 IEEE International Conference on Data Mining Workshops.

AveBoost2: Boosting for Noisy Data

Nikunj C. Oza, N. Oza, 2004, Multiple Classifier Systems.

DiscoveringAnomalousAviationSafetyEventsUsingScalableData Mining Algorithms

Kanishka Bhaduri, Kamalika Das, Santanu Das, 2014 .

Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems

Arindam Banerjee, Igor Melnyk, Nikunj C. Oza, 2016, J. Aerosp. Inf. Syst..

Proceedings of the First International Workshop on Data Mining for Service and Maintenance

R. Bharat Rao, Shipeng Yu, Michal Rosen-Zvi, 2011, KDD 2011.

ExoMiner: A Highly Accurate and Explainable Deep Learning Classifier to Mine Exoplanets pdf

Hamed Valizadegan, Jon M. Jenkins, Stephen T. Bryson, 2021, ArXiv.

ExoMiner: A Highly Accurate and Explainable Deep Learning Classifier That Validates 301 New Exoplanets

Hamed Valizadegan, Jon M. Jenkins, Stephen T. Bryson, 2021, The Astrophysical Journal.

Anomaly Detection, Active Learning, Precursor Identification, and Human Knowledge for Autonomous System Safety

Shawn R. Wolfe, David L. Iverson, Nikunj C. Oza, 2020, AIAA Scitech 2021 Forum.

Knowledge Driven Image Mining with Mixture Density Mercer Kernels

Ashok N. Srivastava, Nikunj C. Oza, 2004 .

A Survey of Robot Architectures

Nikunj C. Oza, 2007 .

Probabilistic Models of Driver Behavior

Nikunj C. Oza, N. Oza, 1999 .

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

Ashok N. Srivastava, Nikunj C. Oza, Julienne C. Stroeve, 2004 .