Understanding the Dynamics of Crop Problems by Analyzing Farm Advisory Data in eSagu TM . - R. Uday Kiran; P. Krishna Reddy (DNIS, 2007)

An improved multiple minimum support based approach to mine rare association rules. - R. Uday Kiran; P. Krishna Reddy (CIDM, 2009)

Mining Rare Periodic-Frequent Patterns Using Multiple Minimum Supports. - R. Uday Kiran; P. Krishna Reddy (COMAD, 2009)

An Improved Frequent Pattern-growth Approach to Discover Rare Association Rules. - R. Uday Kiran; P. Krishna Reddy (KDIR, 2009)

An Efficient Approach to Mine Rare Association Rules Using Maximum Items' Support Constraints. - R. Uday Kiran; Krishna Reddy Polepalli (BNCOD, 2010)

Selecting a Right Interestingness Measure for Rare Association Rules. - Akshat Surana; R. Uday Kiran; P. Krishna Reddy (COMAD, 2010)

Mining periodic-frequent patterns with maximum items' support constraints. - R. Uday Kiran; P. Krishna Reddy (Bangalore Compute Conf., 2010)

Mining Rare Association Rules in the Datasets with Widely Varying Items' Frequencies. - R. Uday Kiran; P. Krishna Reddy (DASFAA (1), 2010)

Towards Efficient Mining of Periodic-Frequent Patterns in Transactional Databases. - R. Uday Kiran; P. Krishna Reddy (DEXA (2), 2010)

Interface Tailoring by Exploiting Temporality of Attributes for Small Screens. - Mittapally Kumara Swamy; P. Krishna Reddy; R. Uday Kiran; M. Venugopal Reddy (DNIS, 2010)

Analysing dynamics of crop problems by applying text analysis methods on farm advisory data of eSaguTM. - R. Uday Kiran; P. Krishna Reddy; Mittapally Kumara Swamy; G. Syamasundar Reddy (Int. J. Comput. Sci. Eng., 2010)

Discovering Diverse-Frequent Patterns in Transactional Databases. - Somya Srivastava; R. Uday Kiran; P. Krishna Reddy (COMAD, 2011)

An Alternative Interestingness Measure for Mining Periodic-Frequent Patterns. - R. Uday Kiran; P. Krishna Reddy (DASFAA (1), 2011)

Improving the Performance of Recommender System by Exploiting the Categories of Products. - Mohak Sharma; P. Krishna Reddy; R. Uday Kiran; Thirumalaisamy Ragunathan (DNIS, 2011)

Novel techniques to reduce search space in multiple minimum supports-based frequent pattern mining algorithms. - R. Uday Kiran; P. Krishna Reddy (EDBT, 2011)

An Efficient Approach to Mine Periodic-Frequent Patterns in Transactional Databases. - Akshat Surana; R. Uday Kiran; P. Krishna Reddy (PAKDD Workshops, 2011)

Coverage patterns for efficient banner advertisement placement. - Bhargav Sripada; Krishna Reddy Polepalli; Rage Uday Kiran (WWW (Companion Volume), 2011)

Towards Efficient Discovery of Frequent Patterns with Relative Support. - R. Uday Kiran; Masaru Kitsuregawa (COMAD, 2012)

A robust neural network classifier to model the compressive strength of high performance concrete using feature subset selection. - M. Venu; R. Uday Kiran; R. Kiranmai (COMPUTE, 2012)

Efficient Discovery of Correlated Patterns in Transactional Databases Using Items' Support Intervals. - R. Uday Kiran; Masaru Kitsuregawa (DEXA (1), 2012)

Discovering Coverage Patterns for Banner Advertisement Placement. - P. Gowtham Srinivas; P. Krishna Reddy; Bhargav Sripada; R. Uday Kiran; D. Satheesh Kumar (PAKDD (2), 2012)

Temporality-based user interface design approaches for desktop and small screen environment. - Mittapally Kumara Swamy; P. Krishna Reddy; R. Uday Kiran; M. Venugopal Reddy (Int. J. Comput. Sci. Eng., 2012)

An Improved Neighborhood-Restricted Association Rule-based Recommender System. - R. Uday Kiran; Masaru Kitsuregawa (ADC, 2013)

Discovering Quasi-Periodic-Frequent Patterns in Transactional Databases. - R. Uday Kiran; Masaru Kitsuregawa (BDA, 2013)

Towards Addressing the Coverage Problem in Association Rule-Based Recommender Systems. - R. Uday Kiran; Masaru Kitsuregawa (DEXA (2), 2013)

Mining Correlated Patterns with Multiple Minimum All-Confidence Thresholds. - R. Uday Kiran; Masaru Kitsuregawa (PAKDD Workshops, 2013)

Towards efficient discovery of coverage patterns in transactional databases. - R. Uday Kiran; Masashi Toyoda; Masaru Kitsuregawa (SSDBM, 2013)

Novel Techniques to Reduce Search Space in Periodic-Frequent Pattern Mining. - R. Uday Kiran; Masaru Kitsuregawa (DASFAA (2), 2014)

Finding Periodic Patterns in Big Data. - R. Uday Kiran; Masaru Kitsuregawa (BDA, 2015)

Towards Scale-out Capability on Social Graphs. - Haichuan Shang; Xiang Zhao 002; R. Uday Kiran; Masaru Kitsuregawa (CIKM, 2015)

Discovering Chronic-Frequent Patterns in Transactional Databases. - R. Uday Kiran; Masaru Kitsuregawa (DNIS, 2015)

Discovering Recurring Patterns in Time Series. - R. Uday Kiran; Haichuan Shang; Masashi Toyoda; Masaru Kitsuregawa (EDBT, 2015)

Efficient discovery of correlated patterns using multiple minimum all-confidence thresholds. - Rage Uday Kiran; Masaru Kitsuregawa (J. Intell. Inf. Syst., 2015)

Mining coverage patterns from transactional databases. - P. Gowtham Srinivas; P. Krishna Reddy; A. V. Trinath; Bhargav Sripada; R. Uday Kiran (J. Intell. Inf. Syst., 2015)

Discovering Periodic-Frequent Patterns in Transactional Databases Using All-Confidence and Periodic-All-Confidence. - J. N. Venkatesh; R. Uday Kiran; P. Krishna Reddy; Masaru Kitsuregawa (DEXA (1), 2016)

Memory efficient mining of periodic-frequent patterns in transactional databases. - Alampally Anirudh; R. Uday Kiran; P. Krishna Reddy; Masaru Kitsuregawa (SSCI, 2016)

Efficient discovery of periodic-frequent patterns in very large databases. - R. Uday Kiran; Masaru Kitsuregawa; P. Krishna Reddy (J. Syst. Softw., 2016)

An Efficient Map-Reduce Framework to Mine Periodic Frequent Patterns. - Alampally Anirudh; R. Uday Kiran; P. Krishna Reddy; Masashi Toyoda; Masaru Kitsuregawa (DaWaK, 2017)

Discovering Periodic Patterns in Non-uniform Temporal Databases. - R. Uday Kiran; J. N. Venkatesh; Philippe Fournier-Viger; Masashi Toyoda; P. Krishna Reddy; Masaru Kitsuregawa (PAKDD (2), 2017)

Discovering Partial Periodic Itemsets in Temporal Databases. - R. Uday Kiran; Haichuan Shang; Masashi Toyoda; Masaru Kitsuregawa (SSDBM, 2017)

Discovering partial periodic-frequent patterns in a transactional database. - R. Uday Kiran; J. N. Venkatesh; Masashi Toyoda; Masaru Kitsuregawa; P. Krishna Reddy (J. Syst. Softw., 2017)

Efficient Discovery of Weighted Frequent Itemsets in Very Large Transactional Databases: A Re-visit. - R. Uday Kiran; Amulya Kotni; P. Krishna Reddy; Masashi Toyoda; Subhash Bhalla; Masaru Kitsuregawa (IEEE BigData, 2018)

Discovering Periodic Patterns Common to Multiple Sequences. - Philippe Fournier-Viger; Zhitian Li; Jerry Chun-Wei Lin; Rage Uday Kiran; Hamido Fujita (DaWaK, 2018)

Novel Data Segmentation Techniques for Efficient Discovery of Correlated Patterns Using Parallel Algorithms. - Amulya Kotni; R. Uday Kiran; Masashi Toyoda; P. Krishna Reddy; Masaru Kitsuregawa (DaWaK, 2018)

A Story Coherence based Neural Network Model for Predicting Story Ending. - Qian Li 016; Ziwei Li; Jin-Mao Wei 001; Zhenglu Yang; Yanhui Gu; R. Uday Kiran (WWW (Companion Volume), 2018)

Discovering Periodic-Correlated Patterns in Temporal Databases. - J. N. Venkatesh; R. Uday Kiran; P. Krishna Reddy; Masaru Kitsuregawa (Trans. Large Scale Data Knowl. Centered Syst., 2018)

TKG: Efficient Mining of Top-K Frequent Subgraphs. - Philippe Fournier-Viger; Chao Cheng; Jerry Chun-Wei Lin; Unil Yun; R. Uday Kiran (BDA, 2019)

Discovering Spatial High Utility Frequent Itemsets in Spatiotemporal Databases. - P. P. C. Reddy; R. Uday Kiran; Koji Zettsu; Masashi Toyoda; P. Krishna Reddy; Masaru Kitsuregawa (BDA, 2019)

Discovering Partial Periodic Spatial Patterns in Spatiotemporal Databases. - R. Uday Kiran; C. Saideep; Koji Zettsu; Masashi Toyoda; Masaru Kitsuregawa; P. Krishna Reddy (IEEE BigData, 2019)

Discovering Partial Periodic High Utility Itemsets in Temporal Databases. - T. Yashwanth Reddy; R. Uday Kiran; Masashi Toyoda; P. Krishna Reddy; Masaru Kitsuregawa (DEXA (2), 2019)

Discovering Spatial Weighted Frequent Itemsets in Spatiotemporal Databases. - Rage Uday Kiran; P. P. C. Reddy; Koji Zettsu; Masashi Toyoda; Masaru Kitsuregawa; P. Krishna Reddy (ICDM Workshops, 2019)

Discovering Periodic Patterns in Irregular Time Series. - C. Saideep; Rage Uday Kiran; Koji Zettsu; Philippe Fournier-Viger; Masaru Kitsuregawa; P. Krishna Reddy (ICDM Workshops, 2019)

Discovering Stable Periodic-Frequent Patterns in Transactional Data. - Philippe Fournier-Viger; Peng Yang; Jerry Chun-Wei Lin; Rage Uday Kiran (IEA/AIE, 2019)

Efficiently Finding High Utility-Frequent Itemsets Using Cutoff and Suffix Utility. - R. Uday Kiran; T. Yashwanth Reddy; Philippe Fournier-Viger; Masashi Toyoda; P. Krishna Reddy; Masaru Kitsuregawa (PAKDD (2), 2019)

Discovering Spatial High Utility Itemsets in Spatiotemporal Databases. - R. Uday Kiran; Koji Zettsu; Masashi Toyoda; Philippe Fournier-Viger; P. Krishna Reddy; Masaru Kitsuregawa (SSDBM, 2019)

Efficient algorithms to identify periodic patterns in multiple sequences. - Philippe Fournier-Viger; Zhitian Li; Jerry Chun-Wei Lin; Rage Uday Kiran; Hamido Fujita (Inf. Sci., 2019)

Fusion-3DCNN-max3P: A dynamic system for discovering patterns of predicted congestion. - Minh-Son Dao; Ngoc-Thanh Nguyen; R. Uday Kiran; Koji Zettsu (IEEE BigData, 2020)

Distributed Mining of Spatial High Utility Itemsets in Very Large Spatiotemporal Databases using Spark In-Memory Computing Architecture. - R. Uday Kiran; Sadanori Ito; Minh-Son Dao; Koji Zettsu; Cheng-Wei Wu; Yutaka Watanobe; Incheon Paik; Truong Cong Thang (IEEE BigData, 2020)

Discovering Closed Periodic-Frequent Patterns in Very Large Temporal Databases. - Palla Likhitha; Penugonda Ravikumar; R. Uday Kiran; Yuto Hayamizu; Kazuo Goda; Masashi Toyoda; Koji Zettsu; Sourabh Shrivastava (IEEE BigData, 2020)

Discovering Maximal Periodic-Frequent Patterns in Very Large Temporal Databases. - R. Uday Kiran; Yutaka Watanobe; Bhaskar Chaudhury; Koji Zettsu; Masashi Toyoda; Masaru Kitsuregawa (DSAA, 2020)

Discovering Fuzzy Periodic-Frequent Patterns in Quantitative Temporal Databases. - R. Uday Kiran; C. Saideep; Penugonda Ravikumar; Koji Zettsu; Masashi Toyoda; Masaru Kitsuregawa; P. Krishna Reddy (FUZZ-IEEE, 2020)

Discovering Frequent Spatial Patterns in Very Large Spatiotemporal Databases. - R. Uday Kiran; Sourabh Shrivastava; Philippe Fournier-Viger; Koji Zettsu; Masashi Toyoda; Masaru Kitsuregawa (SIGSPATIAL/GIS, 2020)

Insights From Urban Sensing Data: From Chaos to Predicted Congestion Patterns. - Minh-Son Dao; Ngoc-Thanh Nguyen; R. Uday Kiran; Koji Zettsu (ICDM (Workshops), 2020)

Parallel Mining of Partial Periodic Itemsets in Big Data. - C. Saideep; R. Uday Kiran; Koji Zettsu; Cheng-Wei Wu; P. Krishna Reddy; Masashi Toyoda; Masaru Kitsuregawa (IEA/AIE, 2020)

Efficient Discovery of Weighted Frequent Neighborhood Itemsets in Very Large Spatiotemporal Databases. - R. Uday Kiran; P. P. C. Reddy; Koji Zettsu; Masashi Toyoda; Masaru Kitsuregawa; P. Krishna Reddy (IEEE Access, 2020)

Discovering rare correlated periodic patterns in multiple sequences. - Philippe Fournier-Viger; Peng Yang; Zhitian Li; Jerry Chun-Wei Lin; Rage Uday Kiran (Data Knowl. Eng., 2020)

Mining cost-effective patterns in event logs. - Philippe Fournier-Viger; Jiaxuan Li; Jerry Chun-Wei Lin; Tin Truong-Chi; R. Uday Kiran (Knowl. Based Syst., 2020)

Discovering Relative High Utility Itemsets in Very Large Transactional Databases Using Null-Invariant Measure. - R. Uday Kiran; Pradeep Pallikila; José María Luna; Philippe Fournier-Viger; Masashi Toyoda; P. Krishna Reddy (IEEE BigData, 2021)

Improving the Awareness of Sustainable Smart Cities by Analyzing Lifelog Images and IoT Air Pollution Data. - Tuan-Vinh La; Minh-Son Dao; Kazuki Tejima; Rage Uday Kiran; Koji Zettsu (IEEE BigData, 2021)

Discovering Maximal Partial Periodic Patterns in Very Large Temporal Databases. - Palla Likhitha; Pamalla Veena; R. Uday Kiran; Yutaka Watanobe; Koji Zettsu (IEEE BigData, 2021)

Discovering Top-k Spatial High Utility Itemsets in Very Large Quantitative Spatiotemporal databases. - Pradeep Pallikila; Pamalla Veena; R. Uday Kiran; Ram Avatar; Sadanori Ito; Koji Zettsu; P. Krishna Reddy (IEEE BigData, 2021)

Efficient Discovery of Partial Periodic-Frequent Patterns in Temporal Databases. - So Nakamura; R. Uday Kiran; Palla Likhitha; Penugonda Ravikumar; Yutaka Watanobe; Minh-Son Dao; Koji Zettsu; Masashi Toyoda (DEXA (1), 2021)

A Novel Parameter-Free Energy Efficient Fuzzy Nearest Neighbor Classifier for Time Series Data. - Penugonda Ravikumar; R. Uday Kiran; Narendra Babu Unnam; Yutaka Watanobe; Kazuo Goda; V. Susheela Devi; P. Krishna Reddy (FUZZ-IEEE, 2021)

Discovering Fuzzy Frequent Spatial Patterns in Large Quantitative Spatiotemporal databases. - Pamalla Veena; Sai Chithra Bommisetty; R. Uday Kiran; Sonali Agarwal; Koji Zettsu (FUZZ-IEEE, 2021)

Discovering Periodic-Frequent Patterns in Uncertain Temporal Databases. - R. Uday Kiran; Palla Likhitha; Minh-Son Dao; Koji Zettsu; Ji Zhang 001 (ICONIP (5), 2021)

Discovering Spatial High Utility Itemsets in High-Dimensional Spatiotemporal Databases. - Sai Chithra Bommisetty; Penugonda Ravikumar; Rage Uday Kiran; Minh-Son Dao; Koji Zettsu (IEA/AIE (1), 2021)

IMAGE-2-AQI: Aware of the Surrounding Air Qualification by a Few Images. - Minh-Son Dao; Koji Zettsu; Rage Uday Kiran (IEA/AIE (2), 2021)

A Novel Rule-Based Online Judge Recommender System to Promote Computer Programming Education. - Md. Mostafizer Rahman; Yutaka Watanobe; Rage Uday Kiran; Keita Nakamura (IEA/AIE (2), 2021)

Towards Efficient Discovery of Periodic-Frequent Patterns in Columnar Temporal Databases. - Penugonda Ravikumar; Likhitha Palla; Rage Uday Kiran; Yutaka Watanobe; Koji Zettsu (IEA/AIE (1), 2021)

Online Automatic Assessment System for Program Code: Architecture and Experiences. - Yutaka Watanobe; Md. Mostafizer Rahman; Rage Uday Kiran; Penugonda Ravikumar (IEA/AIE (2), 2021)

Fruit classification using deep feature maps in the presence of deceptive similar classes. - Mohit Dandekar; Narinder Singh Punn; Sanjay Kumar Sonbhadra; Sonali Agarwal; Rage Uday Kiran (IJCNN, 2021)

A Unified Framework to Discover Partial Periodic-Frequent Patterns in Row and Columnar Temporal Databases. - Pamalla Veena; So Nakamura; Palla Likhitha; R. Uday Kiran; Yutaka Watanobe; Koji Zettsu (ICDM (Workshops), 2021)

Discovering Knowledge Hidden in Raster Images using RasterMiner. - R. Uday Kiran (ICDAR@ICMR, 2021)

Learning Probabilistic Latent Structure for Outlier Detection from Multi-view Data. - Zhen Wang 037; Ji Zhang 001; Yizheng Chen 003; Chenhao Lu; Jerry Chun-Wei Lin; Jing Xiao 005; Rage Uday Kiran (PAKDD (1), 2021)

A Stacked Bidirectional LSTM Model for Classifying Source Codes Built in MPLs. - Md. Mostafizer Rahman; Yutaka Watanobe; Rage Uday Kiran; Raihan Kabir (PKDD/ECML Workshops (2), 2021)

Challenges and Exit Strategies for Adapting Interactive Online Education Amid the Pandemic and its Aftermath. - Md. Mostafizer Rahman; Yutaka Watanobe; Rage Uday Kiran; Truong Cong Thang; Incheon Paik (TALE, 2021)

Impact of Practical Skills on Academic Performance: A Data-Driven Analysis. - Md. Mostafizer Rahman; Yutaka Watanobe; Rage Uday Kiran; Truong Cong Thang; Incheon Paik (IEEE Access, 2021)

Mining local periodic patterns in a discrete sequence. - Philippe Fournier-Viger; Peng Yang; Rage Uday Kiran; Sebastián Ventura; José María Luna (Inf. Sci., 2021)

Towards Efficient Discovery of Partial Periodic Patterns in Columnar Temporal Databases. - Penugonda Ravikumar; Bathala Venus Vikranth Raj; Palla Likhitha; Rage Uday Kiran; Yutaka Watanobe; Sadanori Ito; Koji Zettsu; Masashi Toyoda (ACIIDS (2), 2022)

Discovering Top-k Periodic-Frequent Patterns in Very Large Temporal Databases. - Palla Likhitha; Penugonda Ravikumar; Rage Uday Kiran; Yutaka Watanobe (BDA, 2022)

A Novel GPU-Accelerated Algorithm to Discover Periodic-Frequent Patterns in Temporal Databases. - Sreepada Tarun; Rage Uday Kiran; Yutaka Watanobe; Kazuo Goda (IEEE Big Data, 2022)

A Novel Null-Invariant Temporal Measure to Discover Partial Periodic Patterns in Non-uniform Temporal Databases. - R. Uday Kiran; Vipul Chhabra; Saideep Chennupati; P. Krishna Reddy; Minh-Son Dao; Koji Zettsu (DASFAA (1), 2022)

Effective and Robust Boundary-Based Outlier Detection Using Generative Adversarial Networks. - Qiliang Liang; Ji Zhang 001; Mohamed Jaward Bah; Hongzhou Li; Liang Chang 003; Rage Uday Kiran (DEXA (2), 2022)

Towards Efficient Discovery of Periodic-Frequent Patterns in Dense Temporal Databases Using Complements. - Pamalla Veena; Sreepada Tarun; R. Uday Kiran; Minh-Son Dao; Koji Zettsu; Yutaka Watanobe; Ji Zhang 001 (DEXA (2), 2022)

Discovering Geo-referenced Periodic-Frequent Patterns in Geo-referenced Time Series Databases. - Penugonda Ravikumar; R. Uday Kiran; Palla Likhitha; T. Chandrasekhar; Yutaka Watanobe; Koji Zettsu (DSAA, 2022)

Discovering Fuzzy Geo-referenced Periodic-Frequent Patterns in Geo-referenced Time Series Databases. - Pamalla Veena; Penugonda Ravikumar; Kundai Kwangwari; R. Uday Kiran; Kazuo Goda; Yutaka Watanobe; Koji Zettsu (FUZZ-IEEE, 2022)

Towards developing energy efficient algorithms to discover partial periodic patterns in big temporal databases. - Palla Likhitha; Rage Uday Kiran (SIGSPATIAL/GIS, 2022)

UPFP-growth++: An Efficient Algorithm to Find Periodic-Frequent Patterns in Uncertain Temporal Databases. - Palla Likhitha; Rage Veena; Rage Uday Kiran; Koji Zettsu; Masashi Toyoda; Philippe Fournier-Viger (ICONIP (5), 2022)

A Spatiotemporal Image Fusion Method for Predicting High-Resolution Satellite Images. - Vipul Chhabra; R. Uday Kiran; Juan Xiao; P. Krishna Reddy; Ram Avtar (IEA/AIE, 2022)

Towards Efficient Discovery of Stable Periodic Patterns in Big Columnar Temporal Databases. - Hong N. Dao; Penugonda Ravikumar; Palla Likhitha; Bathala Venus Vikranth Raj; R. Uday Kiran; Yutaka Watanobe; Incheon Paik (IEA/AIE, 2022)

Towards QoE Management for Post-Pandemic Online Learning : Invited Paper. - Truong Cong Thang; Yutaka Watanobe; Rage Uday Kiran; Incheon Paik (KSE, 2022)

Educational Data Mining to Support Programming Learning Using Problem-Solving Data. - Md. Mostafizer Rahman; Yutaka Watanobe; Taku Matsumoto; Rage Uday Kiran; Keita Nakamura (IEEE Access, 2022)

TSPIN: mining top-k stable periodic patterns. - Philippe Fournier-Viger; Ying Wang; Peng Yang; Jerry Chun-Wei Lin; Unil Yun; Rage Uday Kiran (Appl. Intell., 2022)

Online Judge System: Requirements, Architecture, and Experiences. - Yutaka Watanobe; Md. Mostafizer Rahman; Taku Matsumoto; Rage Uday Kiran; Penugonda Ravikumar (Int. J. Softw. Eng. Knowl. Eng., 2022)

Discovering Top-K Partial Periodic Patterns in Big Temporal Databases. - Palla Likhitha; Rage Uday Kiran (DEXA (1), 2023)

Discovering Fuzzy Partial Periodic Patterns in Quantitative Irregular Multiple Time Series. - Pamalla Veena; Palla Likhitha; R. Uday Kiran; José María Luna; Philippe Fournier-Viger; Koji Zettsu (FUZZ, 2023)

Efficient Parallel Mining of High-utility Itemsets on Multicore Processors. - Genki Kimura; Yuto Hayamizu; Rage Uday Kiran; Masaru Kitsuregawa; Kazuo Goda (ICDE, 2023)

A Novel Parallel Spatiotemporal Image Fusion Method for Predicting High-Resolution Satellite Images. - Vipul Chhabra; Rage Uday Kiran; Abinash Maharana; Juan Xiao; Krishna Reddy Polepalli; Ram Avtar; Yoshiko Ogawa; Makiko Ohtake (IEA/AIE (1), 2023)

A Novel Explainable Link Forecasting Framework for Temporal Knowledge Graphs Using Time-Relaxed Cyclic and Acyclic Rules. - Rage Uday Kiran; Abinash Maharana; Krishna Reddy Polepalli (PAKDD (1), 2023)

Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases. - Palla Likhitha; Pamalla Veena; Rage Uday Kiran; Koji Zettsu (PAKDD (3), 2023)

Towards Efficient Discovery of Spatially Interesting Patterns in Geo-referenced Sequential Databases. - Shota Suzuki; Rage Uday Kiran (SSDBM, 2023)

Finding Stable Periodic-Frequent Itemsets in Big Columnar Databases. - Hong N. Dao; Penugonda Ravikumar; Palla Likhitha; Rage Uday Kiran; Yutaka Watanobe; Incheon Paik (IEEE Access, 2023)

k-PFPMiner: Top-k Periodic Frequent Patterns in Big Temporal Databases. - Palla Likhitha; Penugonda Ravikumar; Deepika Saxena; Rage Uday Kiran; Yutaka Watanobe (IEEE Access, 2023)

Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Complements. - Pamalla Veena; Sreepada Tarun; Rage Uday Kiran; Minh-Son Dao; Koji Zettsu; Yutaka Watanobe; Ji Zhang 001 (IEEE Access, 2023)

Deep Learning-Based Spatiotemporal Fusion of Unmanned Aerial Vehicle and Satellite Reflectance Images for Crop Monitoring. - Juan Xiao; Ashwani Kumar Aggarwal; Rage Uday Kiran; Vaibhav Katiyar; Ram Avtar (IEEE Access, 2023)

Training Performance Indications for Amateur Athletes Based on Nutrition and Activity Lifelogs. - Phuc-Thinh Nguyen; Minh-Son Dao; Michael A. Riegler; Rage Uday Kiran; Thai-Thinh Dang; Duy-Dong Le; Kieu-Chinh Nguyen-Ly; Thanh-Qui Pham; Van-Luong Nguyen (Algorithms, 2023)

HDSHUI-miner: a novel algorithm for discovering spatial high-utility itemsets in high-dimensional spatiotemporal databases. - Rage Uday Kiran; Pamalla Veena; Penugonda Ravikumar; Bathala Venus Vikranth Raj; Minh-Son Dao; Koji Zettsu; Sai Chithra Bommisetti (Appl. Intell., 2023)

Efficient mining of top-k high utility itemsets through genetic algorithms. - José María Luna; Rage Uday Kiran; Philippe Fournier-Viger; Sebastián Ventura (Inf. Sci., 2023)

A fundamental approach to discover closed periodic-frequent patterns in very large temporal databases. - Pamalla Veena; Rage Uday Kiran; Penugonda Ravikumar; Likhitha Palla; Yuto Hayamizu; Kazuo Goda; Masashi Toyoda; Koji Zettsu; Sourabh Shrivastava (Appl. Intell., 2023)

A Novel Multi-scale Spatiotemporal Graph Neural Network for Epidemic Prediction. - Zenghui Xu; Mingzhang Li; Ting Yu 004; Linlin Hou; Peng Zhang 001; Rage Uday Kiran; Zhao Li 007; Ji Zhang 001 (DEXA (2), 2024)

Towards Addressing an Open Problem in Coupled Matrix Tensor Factorization for Satellite Imagery Data Using Human-in-Loop. - R. Uday Kiran; Abinash Maharana; Makiko Ohtake; Yoshiko Ogawa (IEA/AIE, 2024)

A Novel Multi-task Single-Step Traffic Congestion Forecasting Framework for Large-Scale Road Networks. - Kazuki Tejima; Deepika Saxena; Rage Uday Kiran (IEA/AIE, 2024)

ICDAR 24: Intelligent Cross-Data Analysis and Retrieval. - Minh-Son Dao; Michael Alexander Riegler; Duc-Tien Dang-Nguyen; Hanh-Nhi Tran; Rage Uday Kiran; Takahiro Komamizu (ICMR, 2024)

Discovering Spatially Interesting Patterns in Big Geo-Referenced Sequential Databases. - Vanitha Kattumuri; Rage Uday Kiran; Shota Suzuki (IEEE Access, 2024)

PAMI: An Open-Source Python Library for Pattern Mining. - Rage Uday Kiran; Pamalla Veena; Masashi Toyoda; Masaru Kitsuregawa (J. Mach. Learn. Res., 2024)

3P-ECLAT: mining partial periodic patterns in columnar temporal databases. - Pamalla Veena; Rage Uday Kiran; Penugonda Ravikumar; Likhitha Palla; Yutaka Watanobe; Sadanori Ito; Koji Zettsu; Masashi Toyoda; Bathala Venus Vikranth Raj (Appl. Intell., 2024)

Discriminative boundary generation for effective outlier detection. - Ji Zhang 001; Qiliang Liang; Mohamed Jaward Bah; Hongzhou Li; Liang Chang 003; Rage Uday Kiran (Knowl. Inf. Syst., 2024)

HAMAMBA: Hierarchical Adaptive Mixtures of Attention with Mamba for Robust Time Series Anomaly Detection. - Saisai Hu; Ji Zhang 001; Zhao Li 007; Liang Liao; Yuquan Gan; Rage Uday Kiran (ICIC (8), 2025)

Beyond Air Pollution Prediction: A Step to Pollution Pattern Discovery with a Novel Binary Neuro-Symbolic AI Framework. - Yerragolla Hareesh Kumar; Rage Uday Kiran (IEA/AIE (2), 2025)

A Novel Depth-First Search Algorithm for Partial Periodic-Frequent Pattern Mining in Temporal Databases. - Pamalla Veena; Vanitha Kattumuri; Yutaka Watanobe; Rage Uday Kiran; So Nakamura; Palla Likhitha; Koji Zettsu (IEEE Access, 2025)

Periodic-confidence: a null-invariant measure to discover partial periodic patterns in non-uniform temporal databases. - Rage Uday Kiran; Vipul Chhabra; Saideep Chennupati; Krishna Reddy Polipalli; Minh-Son Dao; Koji Zettsu (Int. J. Data Sci. Anal., 2025)