Kalyan Veeramachaneni

136 papers A* 6A 10B 27C 2Journal 54Unranked 34

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	CENTS: Generating synthetic electricity consumption time series for rare and unseen scenarios. CoRR Michael Fuest, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2025	J	`jnl`	Single Word Change Is All You Need: Using LLMs to Create Synthetic Training Examples for Text Classifiers. Expert Syst. J. Knowl. Eng. Lei Xu, Sarah Alnegheimish, Laure Berti-Équille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2024	B	`conf`	Can Large Language Models be Anomaly Detectors for Time Series? DSAA Sarah Alnegheimish, Linh Nguyen, Laure Berti-Équille, Kalyan Veeramachaneni
2024	B	`conf`	Explingo: Explaining AI Predictions using Large Language Models. IEEE Big Data Alexandra Zytek, Sara Pidò, Sarah Alnegheimish, Laure Berti-Équille, Kalyan Veeramachaneni
2024	J	`jnl`	Explingo: Explaining AI Predictions using Large Language Models. CoRR Alexandra Zytek, Sara Pidò, Sarah Alnegheimish, Laure Berti-Équille, Kalyan Veeramachaneni
2024	J	`jnl`	LLMs for XAI: Future Directions for Explaining Explanations. CoRR Alexandra Zytek, Sara Pidò, Kalyan Veeramachaneni
2024	J	`jnl`	Large language models can be zero-shot anomaly detectors for time series? CoRR Sarah Alnegheimish, Linh Nguyen, Laure Berti-Équille, Kalyan Veeramachaneni
2024	B	`conf`	OrionBench: Benchmarking Time Series Generative Models in the Service of the End-User. IEEE Big Data Sarah Alnegheimish, Laure Berti-Équille, Kalyan Veeramachaneni
2024	J	`jnl`	Single Word Change is All You Need: Designing Attacks and Defenses for Text Classifiers. CoRR Lei Xu, Sarah Alnegheimish, Laure Berti-Équille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2023	J	`jnl`	Lessons from Usable ML Deployments and Application to Wind Turbine Monitoring. CoRR Alexandra Zytek, Wei-En Wang, Sofia Koukoura, Kalyan Veeramachaneni
2023	J	`jnl`	Making the End-User a Priority in Benchmarking: OrionBench for Unsupervised Time Series Anomaly Detection. CoRR Sarah Alnegheimish, Laure Berti-Équille, Kalyan Veeramachaneni
2023	J	`jnl`	Pyreal: A Framework for Interpretable ML Explanations. CoRR Alexandra Zytek, Wei-En Wang, Dongyu Liu, Laure Berti-Équille, Kalyan Veeramachaneni
2022	B	`conf`	AER: Auto-Encoder with Regression for Time Series Anomaly Detection. IEEE Big Data Lawrence Wong, Dongyu Liu, Laure Berti-Équille, Sarah Alnegheimish, Kalyan Veeramachaneni
2022	J	`jnl`	AER: Auto-Encoder with Regression for Time Series Anomaly Detection. CoRR Lawrence Wong, Dongyu Liu, Laure Berti-Équille, Sarah Alnegheimish, Kalyan Veeramachaneni
2022	J	`jnl`	AutoML to Date and Beyond: Challenges and Opportunities. ACM Comput. Surv. Shubhra Kanti Karmaker Santu, Md. Mahadi Hassan, Micah J. Smith, Lei Xu, ChengXiang Zhai, Kalyan Veeramachaneni
2022	—	`conf`	In Situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers. ICONIP (3) Lei Xu, Laure Berti-Équille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2022	J	`jnl`	MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series. Proc. ACM Hum. Comput. Interact. Dongyu Liu, Sarah Alnegheimish, Alexandra Zytek, Kalyan Veeramachaneni
2022	—	`conf`	R&R: Metric-guided Adversarial Sentence Generation. AACL/IJCNLP (Findings) Lei Xu, Alfredo Cuesta-Infante, Laure Berti-Équille, Kalyan Veeramachaneni
2022	J	`jnl`	Sequential Models in the Synthetic Data Vault. CoRR Kevin Alex Zhang, Neha Patki, Kalyan Veeramachaneni
2022	J	`jnl`	Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making. IEEE Trans. Vis. Comput. Graph. Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan, Kalyan Veeramachaneni
2022	—	`conf`	Sintel: A Machine Learning Framework to Extract Insights from Signals. SIGMOD Conference Sarah Alnegheimish, Dongyu Liu, Carles Sala, Laure Berti-Équille, Kalyan Veeramachaneni
2022	J	`jnl`	Sintel: A Machine Learning Framework to Extract Insights from Signals. CoRR Sarah Alnegheimish, Dongyu Liu, Carles Sala, Laure Berti-Équille, Kalyan Veeramachaneni
2022	J	`jnl`	The Need for Interpretable Features: Motivation and Taxonomy. CoRR Alexandra Zytek, Ignacio Arnaldo, Dongyu Liu, Laure Berti-Équille, Kalyan Veeramachaneni
2022	J	`jnl`	The Need for Interpretable Features: Motivation and Taxonomy. SIGKDD Explor. Alexandra Zytek, Ignacio Arnaldo, Dongyu Liu, Laure Berti-Équille, Kalyan Veeramachaneni
2022	J	`jnl`	VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models. IEEE Trans. Vis. Comput. Graph. Furui Cheng, Dongyu Liu, Fan Du, Yanna Lin, Alexandra Zytek, Haomin Li, Huamin Qu, Kalyan Veeramachaneni
2021	J	`jnl`	AQEyes: Visual Analytics for Anomaly Detection and Examination of Air Quality Data. CoRR Dongyu Liu, Kalyan Veeramachaneni, Alexander Geiger, Victor O. K. Li, Huamin Qu
2021	J	`jnl`	Attacking Text Classifiers via Sentence Rewriting Sampler. CoRR Lei Xu, Kalyan Veeramachaneni
2021	J	`jnl`	Enabling Collaborative Data Science Development with the Ballet Framework. Proc. ACM Hum. Comput. Interact. Micah J. Smith, Jürgen Cito, Kelvin Lu, Kalyan Veeramachaneni
2021	J	`jnl`	MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series. CoRR Dongyu Liu, Sarah Alnegheimish, Alexandra Zytek, Kalyan Veeramachaneni
2021	J	`jnl`	Meeting in the notebook: a notebook-based environment for micro-submissions in data science collaborations. CoRR Micah J. Smith, Jürgen Cito, Kalyan Veeramachaneni
2021	—	`conf`	Sibyl: Explaining Machine Learning Models for High-Stakes Decision Making. CHI Extended Abstracts Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan, Kalyan Veeramachaneni
2021	A*	`conf`	Towards Reducing Biases in Combining Multiple Experts Online. IJCAI Yi Sun, Iván Ramírez Díaz, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2021	J	`jnl`	Understanding the Usability Challenges of Machine Learning In High-Stakes Decision Making. CoRR Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan, Kalyan Veeramachaneni
2021	J	`jnl`	VBridge: Connecting the Dots Between Features, Explanations, and Data for Healthcare Models. CoRR Furui Cheng, Dongyu Liu, Fan Du, Yanna Lin, Alexandra Zytek, Haomin Li, Huamin Qu, Kalyan Veeramachaneni
2020	J	`jnl`	A Level-wise Taxonomic Perspective on Automated Machine Learning to Date and Beyond: Challenges and Opportunities. CoRR Shubhra Kanti Karmaker Santu, Md. Mahadi Hassan, Micah J. Smith, Lei Xu, ChengXiang Zhai, Kalyan Veeramachaneni
2020	B	`conf`	Cardea: An Open Automated Machine Learning Framework for Electronic Health Records. DSAA Sarah Alnegheimish, Najat Alrashed, Faisal Aleissa, Shahad Althobaiti, Dongyu Liu, Mansour Alsaleh, Kalyan Veeramachaneni
2020	J	`jnl`	Cardea: An Open Automated Machine Learning Framework for Electronic Health Records. CoRR Sarah Alnegheimish, Najat Alrashed, Faisal Aleissa, Shahad Althobaiti, Dongyu Liu, Mansour Alsaleh, Kalyan Veeramachaneni
2020	J	`jnl`	Enabling collaborative data science development with the Ballet framework. CoRR Micah J. Smith, Jürgen Cito, Kelvin Lu, Kalyan Veeramachaneni
2020	—	`conf`	TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks. IEEE BigData Alexander Geiger, Dongyu Liu, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2020	J	`jnl`	TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks. CoRR Alexander Geiger, Dongyu Liu, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2020	—	`conf`	The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development. SIGMOD Conference Micah J. Smith, Carles Sala, James Max Kanter, Kalyan Veeramachaneni
2020	—	`conf`	Understanding User-Bot Interactions for Small-Scale Automation in Open-Source Development. CHI Extended Abstracts Dongyu Liu, Micah J. Smith, Kalyan Veeramachaneni
2019	A*	`conf`	ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning. CHI Qianwen Wang, Yao Ming, Zhihua Jin, Qiaomu Shen, Dongyu Liu, Micah J. Smith, Kalyan Veeramachaneni, Huamin Qu
2019	J	`jnl`	ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning. CoRR Qianwen Wang, Yao Ming, Zhihua Jin, Qiaomu Shen, Dongyu Liu, Micah J. Smith, Kalyan Veeramachaneni, Huamin Qu
2019	—	`conf`	Enhancing Image Steganalysis with Adversarially Generated Examples. CSCML Kevin Alex Zhang, Kalyan Veeramachaneni
2019	J	`jnl`	Learning Fair Classifiers in Online Stochastic Settings. CoRR Yi Sun, Iván Ramírez, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2019	A*	`conf`	Learning Vine Copula Models for Synthetic Data Generation. AAAI Yi Sun, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2019	J	`jnl`	MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data. CoRR Lei Xu, Shubhra Kanti Karmaker Santu, Kalyan Veeramachaneni
2019	A*	`conf`	Modeling Tabular data using Conditional GAN. NeurIPS Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2019	J	`jnl`	Modeling Tabular data using Conditional GAN. CoRR Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2019	J	`jnl`	Robust Invisible Video Watermarking with Attention. CoRR Kevin Alex Zhang, Lei Xu, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2019	J	`jnl`	SteganoGAN: High Capacity Image Steganography with GANs. CoRR Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu, Kalyan Veeramachaneni
2019	B	`conf`	TILM: Neural Language Models with Evolving Topical Influence. CoNLL Shubhra Kanti Karmaker Santu, Kalyan Veeramachaneni, ChengXiang Zhai
2019	J	`jnl`	The Holy Grail of "Systems for Machine Learning": Teaming humans and machine learning for detecting cyber threats. SIGKDD Explor. Ignacio Arnaldo, Kalyan Veeramachaneni
2019	J	`jnl`	The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development. CoRR Micah J. Smith, Carles Sala, James Max Kanter, Kalyan Veeramachaneni
2019	—	`conf`	eX2: a framework for interactive anomaly detection. IUI Workshops Ignacio Arnaldo, Kalyan Veeramachaneni, Mei Lam
2018	—	`conf`	Acquire, adapt, and anticipate: continuous learning to block malicious domains. IEEE BigData Ignacio Arnaldo, Ankit Arun, Sumeeth Kyathanahalli, Kalyan Veeramachaneni
2018	—	`conf`	Augmenting Software Project Managers with Predictions from Machine Learning. IEEE BigData Benjamin Schreck, Shankar Mallapur, Sarvesh Damle, Nitin John James, Sanjeev Vohra, Rajendra Prasad, Kalyan Veeramachaneni
2018	J	`jnl`	Learning Vine Copula Models For Synthetic Data Generation. CoRR Yi Sun, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2018	J	`jnl`	Machine learning 2.0 : Engineering Data Driven AI Products. CoRR James Max Kanter, Benjamin Schreck, Kalyan Veeramachaneni
2018	J	`jnl`	Prediction Factory: automated development and collaborative evaluation of predictive models. CoRR Gaurav Sheni, Benjamin Schreck, Roy Wedge, James Max Kanter, Kalyan Veeramachaneni
2018	—	`conf`	Solving the False Positives Problem in Fraud Prediction Using Automated Feature Engineering. ECML/PKDD (3) Roy Wedge, James Max Kanter, Kalyan Veeramachaneni, Santiago Moral-Rubio, Sergio Iglesias Perez
2018	—	`conf`	Summary of evolutionary computation for wind farm layout optimization. GECCO (Companion) Dennis G. Wilson, Silvio Rodrigues, Carlos Segura, Ilya Loshchilov, Frank Hutter, Guillermo López Buenfil, Ahmed Kheiri, Ed Keedwell, Mario Ocampo-Pineda, Ender Özcan, Sergio Ivvan Valdez Peña, Brian Goldman, Salvador Botello Rionda, Arturo Hernández Aguirre, Kalyan Veeramachaneni, Sylvain Cussat-Blanc
2018	J	`jnl`	Synthesizing Tabular Data using Generative Adversarial Networks. CoRR Lei Xu, Kalyan Veeramachaneni
2018	—	`conf`	Towards Building Active Defense Systems for Software Applications. CSCML Zara Perumal, Kalyan Veeramachaneni
2017	—	`conf`	ATM: A distributed, collaborative, scalable system for automated machine learning. IEEE BigData Thomas Swearingen, Will Drevo, Bennett Cyphers, Alfredo Cuesta-Infante, Arun Ross, Kalyan Veeramachaneni
2017	B	`conf`	AnonML: Locally Private Machine Learning over a Network of Peers. DSAA Bennett Cyphers, Kalyan Veeramachaneni
2017	B	`conf`	FeatureHub: Towards Collaborative Data Science. DSAA Micah J. Smith, Roy Wedge, Kalyan Veeramachaneni
2017	—	`conf`	Learning Representations for Log Data in Cybersecurity. CSCML Ignacio Arnaldo, Alfredo Cuesta-Infante, Ankit Arun, Mei Lam, Costas Bassias, Kalyan Veeramachaneni
2017	B	`conf`	Sample, Estimate, Tune: Scaling Bayesian Auto-Tuning of Data Science Pipelines. DSAA Alec Anderson, Sébastien Dubois, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2017	J	`jnl`	Solving the "false positives" problem in fraud prediction. CoRR Roy Wedge, James Max Kanter, Santiago Moral-Rubio, Sergio Iglesias Perez, Kalyan Veeramachaneni
2016	—	`conf`	AI^2: Training a Big Data Machine to Defend. BigDataSecurity/HPSC/IDS Kalyan Veeramachaneni, Ignacio Arnaldo, Vamsi Korrapati, Constantinos Bassias, Ke Li
2016	B	`conf`	Acting the Same Differently: A Cross-Course Comparison of User Behavior in MOOCs. EDM Ben U. Gelman, Matt Revelle, Carlotta Domeniconi, Kalyan Veeramachaneni, Aditya Johri
2016	—	`conf`	DropoutSeer: Visualizing learning patterns in Massive Open Online Courses for dropout reasoning and prediction. VAST Yuanzhe Chen, Qing Chen, Mingqian Zhao, Sebastien Boyer, Kalyan Veeramachaneni, Huamin Qu
2016	B	`conf`	Label, Segment, Featurize: A Cross Domain Framework for Prediction Engineering. DSAA James Max Kanter, Owen Gillespie, Kalyan Veeramachaneni
2016	—	`conf`	Markov Switching Copula Models for Longitudinal Data. ICDM Workshops Alfredo Cuesta-Infante, Kalyan Veeramachaneni
2016	B	`conf`	Robust Predictive Models on MOOCs : Transferring Knowledge across Courses. EDM Sebastien Boyer, Kalyan Veeramachaneni
2016	B	`conf`	The Synthetic Data Vault. DSAA Neha Patki, Roy Wedge, Kalyan Veeramachaneni
2016	B	`conf`	What Would a Data Scientist Ask? Automatically Formulating and Solving Predictive Problems. DSAA Benjamin Schreck, Kalyan Veeramachaneni
2015	A*	`conf`	Autotuning algorithmic choice for input sensitivity. PLDI Yufei Ding, Jason Ansel, Kalyan Veeramachaneni, Xipeng Shen, Una-May O'Reilly, Saman P. Amarasinghe
2015	J	`jnl`	Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning. IEEE Comput. Intell. Mag. Ignacio Arnaldo, Kalyan Veeramachaneni, Andrew Song, Una-May O'Reilly
2015	A	`conf`	Building Predictive Models via Feature Synthesis. GECCO Ignacio Arnaldo, Una-May O'Reilly, Kalyan Veeramachaneni
2015	A*	`conf`	Copula Graphical Models for Wind Resource Estimation. IJCAI Kalyan Veeramachaneni, Alfredo Cuesta-Infante, Una-May O'Reilly
2015	B	`conf`	Data science foundry for MOOCs. DSAA Sebastien Boyer, Ben U. Gelman, Benjamin Schreck, Kalyan Veeramachaneni
2015	B	`conf`	Deep feature synthesis: Towards automating data science endeavors. DSAA James Max Kanter, Kalyan Veeramachaneni
2015	B	`conf`	Feature Factory: Crowd Sourced Feature Discovery. L@S Kalyan Veeramachaneni, Kiarash Adl, Una-May O'Reilly
2015	J	`jnl`	FlexGP - Cloud-Based Ensemble Learning with Genetic Programming for Large Regression Problems. J. Grid Comput. Kalyan Veeramachaneni, Ignacio Arnaldo, Owen Derby, Una-May O'Reilly
2015	—	`ch.`	Fusion, Decision-Level. Encyclopedia of Biometrics Lisa Ann Osadciw, Kalyan Veeramachaneni
2015	B	`conf`	Gaussian Process-Based Feature Selection for Wavelet Parameters: Predicting Acute Hypotensive Episodes from Physiological Signals. CBMS Franck Dernoncourt, Kalyan Veeramachaneni, Una-May O'Reilly
2015	A	`conf`	Transfer Learning for Predictive Models in Massive Open Online Courses. AIED Sebastien Boyer, Kalyan Veeramachaneni
2014	A	`conf`	A continuous developmental model for wind farm layout optimization. GECCO Dennis Wilson, Sylvain Cussat-Blanc, Kalyan Veeramachaneni, Una-May O'Reilly, Hervé Luga
2014	B	`conf`	Flash: A GP-GPU Ensemble Learning System for Handling Large Datasets. EuroGP Ignacio Arnaldo, Kalyan Veeramachaneni, Una-May O'Reilly
2014	J	`jnl`	Likely to stop? Predicting Stopout in Massive Open Online Courses. CoRR Colin Taylor, Kalyan Veeramachaneni, Una-May O'Reilly
2014	J	`jnl`	MOOCdb: Developing Standards and Systems to Support MOOC Data Science. CoRR Kalyan Veeramachaneni, Sherif A. Halawa, Franck Dernoncourt, Una-May O'Reilly, Colin Taylor, Chuong B. Do
2014	B	`conf`	OpenTuner: an extensible framework for program autotuning. PACT Jason Ansel, Shoaib Kamil, Kalyan Veeramachaneni, Jonathan Ragan-Kelley, Jeffrey Bosboom, Una-May O'Reilly, Saman P. Amarasinghe
2014	J	`jnl`	Towards Feature Engineering at Scale for Data from Massive Open Online Courses. CoRR Kalyan Veeramachaneni, Una-May O'Reilly, Colin Taylor
2014	J	`jnl`	Using reinforcement learning to optimize occupant comfort and energy usage in HVAC systems. J. Ambient Intell. Smart Environ. Pedro Fazenda, Kalyan Veeramachaneni, Pedro U. Lima, Una-May O'Reilly
2013	B	`conf`	Cloud Driven Design of a Distributed Genetic Programming Platform. EvoApplications Owen Derby, Kalyan Veeramachaneni, Una-May O'Reilly
2013	B	`conf`	Cloud Scale Distributed Evolutionary Strategies for High Dimensional Problems. EvoApplications Dennis Wilson, Kalyan Veeramachaneni, Una-May O'Reilly
2013	—	`conf`	Developing Data Standards and Systems for MOOC Data Science. AIED Workshops Kalyan Veeramachaneni, Franck Dernoncourt, Colin Taylor, Zachary A. Pardos, Una-May O'Reilly
2013	—	`conf`	Efficient training set use for blood pressure prediction in a large scale learning classifier system. GECCO (Companion) Erik Hemberg, Kalyan Veeramachaneni, Franck Dernoncourt, Mark Wagy, Una-May O'Reilly
2013	—	`conf`	Imprecise selection and fitness approximation in a large-scale evolutionary rule based system for blood pressure prediction. GECCO (Companion) Erik Hemberg, Kalyan Veeramachaneni, Franck Dernoncourt, Mark Wagy, Una-May O'Reilly
2013	A	`conf`	Introducing graphical models to analyze genetic programming dynamics. FOGA Erik Hemberg, Constantin Berzan, Kalyan Veeramachaneni, Una-May O'Reilly
2013	A	`conf`	Learning regression ensembles with genetic programming at scale. GECCO Kalyan Veeramachaneni, Owen Derby, Dylan Sherry, Una-May O'Reilly
2013	B	`conf`	Modeling Service Execution on Data Centers for Energy Efficiency and Quality of Service Monitoring. SMC Monica Vitali, Una-May O'Reilly, Kalyan Veeramachaneni
2013	A	`conf`	On learning to generate wind farm layouts. GECCO Dennis Wilson, Emmanuel Awa, Sylvain Cussat-Blanc, Kalyan Veeramachaneni, Una-May O'Reilly
2013	—	`ch.`	Statistical Approaches for Wind Resource Assessment. Computational Intelligent Data Analysis for Sustainable Development Kalyan Veeramachaneni, Xiang Ye, Una-May O'Reilly
2012	A	`conf`	An investigation of local patterns for estimation of distribution genetic programming. GECCO Erik Hemberg, Kalyan Veeramachaneni, James McDermott, Constantin Berzan, Una-May O'Reilly
2012	B	`conf`	Flex-GP: Genetic Programming on the Cloud. EvoApplications Dylan Sherry, Kalyan Veeramachaneni, James McDermott, Una-May O'Reilly
2012	—	`conf`	Graphical models and what they reveal about GP when it solves a symbolic regression problem. GECCO (Companion) Erik Hemberg, Kalyan Veeramachaneni, Una-May O'Reilly
2012	J	`jnl`	Knowledge mining sensory evaluation data: genetic programming, statistical techniques, and swarm optimization. Genet. Program. Evolvable Mach. Kalyan Veeramachaneni, Ekaterina Vladislavleva, Una-May O'Reilly
2012	B	`conf`	Optimizing energy output and layout costs for large wind farms using particle swarm optimization. IEEE Congress on Evolutionary Computation Kalyan Veeramachaneni, Markus Wagner, Una-May O'Reilly, Frank Neumann
2011	J	`jnl`	Feature extraction from optimization samples via ensemble based symbolic regression. Ann. Math. Artif. Intell. Kalyan Veeramachaneni, Ekaterina Vladislavleva, Una-May O'Reilly
2011	J	`jnl`	Hitoshi Iba, Topon Kumar Paul, Yoshohiko Hasegawa: Applied genetic programming and machine learning - CRC Press, 327 pp, ISBN: 978-1-4398-0369-1. Genet. Program. Evolvable Mach. Kalyan Veeramachaneni
2011	B	`conf`	How Far Is It from Here to There? A Distance That Is Coherent with GP Operators. EuroGP James McDermott, Una-May O'Reilly, Leonardo Vanneschi, Kalyan Veeramachaneni
2010	A	`conf`	Evolutionary optimization of flavors. GECCO Kalyan Veeramachaneni, Katya Vladislavleva, Matt Burland, Jason Parcon, Una-May O'Reilly
2010	—	`conf`	Feature Extraction from Optimization Data via DataModeler's Ensemble Symbolic Regression. LION Kalyan Veeramachaneni, Katya Vladislavleva, Una-May O'Reilly
2010	A	`conf`	Knowledge mining with genetic programming methods for variable selection in flavor design. GECCO Katya Vladislavleva, Kalyan Veeramachaneni, Matt Burland, Jason Parcon, Una-May O'Reilly
2010	B	`conf`	Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data. EuroGP Katya Vladislavleva, Kalyan Veeramachaneni, Una-May O'Reilly, Matt Burland, Jason Parcon
2009	—	`conf`	A novel ultrawide band locationing system using swarm enabled learning approaches. SIS Weihua Gao, Kalyan Veeramachaneni, Ganapathi Kamath, Lisa Ann Osadciw
2009	—	`conf`	A particle swarm optimization based multilateration algorithm for UWB sensor network. CCECE Weihua Gao, Ganapathi Kamath, Kalyan Veeramachaneni, Lisa Ann Osadciw
2009	—	`conf`	Achieving spectrum efficiency through signal design for ultra wide band sensor networks. SIS Weihua Gao, Kalyan Veeramachaneni, Lisa Ann Osadciw
2009	J	`jnl`	Biometric Sensor Management: Tradeoffs in Time, Accuracy and Energy. IEEE Syst. J. Kalyan Veeramachaneni, Lisa Ann Osadciw
2009	C	`conf`	Fusing correlated data from multiple classifiers for improved biometric verification. FUSION Nisha Srinivas, Kalyan Veeramachaneni, Lisa Ann Osadciw
2009	—	`ch.`	Fusion, Decision-Level. Encyclopedia of Biometrics Lisa Ann Osadciw, Kalyan Veeramachaneni
2009	—	`conf`	Information sharing strategy among particles in Particle Swarm Optimization using Laplacian operator. SIS Jagdish Chand Bansal, Kusum Deep, Kalyan Veeramachaneni, Lisa Ann Osadciw
2009	J	`jnl`	Situation assessment and autonomous control and optimisation of biometric sensor network. Int. J. Biom. Kalyan Veeramachaneni, Lisa Ann Osadciw
2009	C	`conf`	Unsupervised learning and fusion for failure detection in wind turbines. FUSION Xiang Ye, Kalyan Veeramachaneni, Yanjun Yan, Lisa Ann Osadciw
2008	—	`conf`	Decision-level fusion strategies for correlated biometric classifiers. CVPR Workshops Kalyan Veeramachaneni, Lisa Ann Osadciw, Arun Ross, Nisha Srinivas
2008	—	`conf`	Swarm intelligence based optimization and control of decentralized serial sensor networks. SIS Kalyan Veeramachaneni, Lisa Ann Osadciw
2007	—	`conf`	Improving Classifier Fusion Using Particle Swarm Optimization. MCDM Kalyan Veeramachaneni, Weizhong Yan, Kai Goebel, Lisa Ann Osadciw
2007	—	`conf`	Probabilistically Driven Particle Swarms for Optimization of Multi Valued Discrete Problems : Design and Analysis. SIS Kalyan Veeramachaneni, Lisa Ann Osadciw, Ganapathi Kamath
2005	J	`jnl`	An adaptive multimodal biometric management algorithm. IEEE Trans. Syst. Man Cybern. Part C Kalyan Veeramachaneni, Lisa Ann Osadciw, Pramod K. Varshney
2004	—	`conf`	An Evolutionary Algorithm Based Approach for Dynamic Thresholding in Multimodal Biometrics. ICBA Kalyan Veeramachaneni, Lisa Ann Osadciw, Pramod K. Varshney
2003	—	`conf`	Fitness-distance-ratio based particle swarm optimization. SIS Thanmaya Peram, Kalyan Veeramachaneni, Chilukuri K. Mohan
2003	A	`conf`	Optimization Using Particle Swarms with Near Neighbor Interactions. GECCO Kalyan Veeramachaneni, Thanmaya Peram, Chilukuri K. Mohan, Lisa Ann Osadciw