Kalyan Veeramachaneni

According to our database1, Kalyan Veeramachaneni authored at least 119 papers between 2003 and 2024.

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Bibliography

2024
Large language models can be zero-shot anomaly detectors for time series?
CoRR, 2024

LLMs for XAI: Future Directions for Explaining Explanations.
CoRR, 2024

Single Word Change is All You Need: Designing Attacks and Defenses for Text Classifiers.
CoRR, 2024

Can Large Language Models be Anomaly Detectors for Time Series?
Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

2023
Pyreal: A Framework for Interpretable ML Explanations.
CoRR, 2023

Lessons from Usable ML Deployments and Application to Wind Turbine Monitoring.
CoRR, 2023

Making the End-User a Priority in Benchmarking: OrionBench for Unsupervised Time Series Anomaly Detection.
CoRR, 2023

2022
Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making.
IEEE Trans. Vis. Comput. Graph., 2022

VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models.
IEEE Trans. Vis. Comput. Graph., 2022

The Need for Interpretable Features: Motivation and Taxonomy.
SIGKDD Explor., 2022

MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series.
Proc. ACM Hum. Comput. Interact., 2022

AutoML to Date and Beyond: Challenges and Opportunities.
ACM Comput. Surv., 2022

Sequential Models in the Synthetic Data Vault.
CoRR, 2022

Sintel: A Machine Learning Framework to Extract Insights from Signals.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

R&R: Metric-guided Adversarial Sentence Generation.
Proceedings of the Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022, 2022

In Situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers.
Proceedings of the Neural Information Processing - 29th International Conference, 2022

AER: Auto-Encoder with Regression for Time Series Anomaly Detection.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Enabling Collaborative Data Science Development with the Ballet Framework.
Proc. ACM Hum. Comput. Interact., 2021

VBridge: Connecting the Dots Between Features, Explanations, and Data for Healthcare Models.
CoRR, 2021

Attacking Text Classifiers via Sentence Rewriting Sampler.
CoRR, 2021

Meeting in the notebook: a notebook-based environment for micro-submissions in data science collaborations.
CoRR, 2021

AQEyes: Visual Analytics for Anomaly Detection and Examination of Air Quality Data.
CoRR, 2021

Understanding the Usability Challenges of Machine Learning In High-Stakes Decision Making.
CoRR, 2021

Towards Reducing Biases in Combining Multiple Experts Online.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Sibyl: Explaining Machine Learning Models for High-Stakes Decision Making.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

2020
A Level-wise Taxonomic Perspective on Automated Machine Learning to Date and Beyond: Challenges and Opportunities.
CoRR, 2020

The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development.
Proceedings of the 2020 International Conference on Management of Data, 2020

Cardea: An Open Automated Machine Learning Framework for Electronic Health Records.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

Understanding User-Bot Interactions for Small-Scale Automation in Open-Source Development.
Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
The Holy Grail of "Systems for Machine Learning": Teaming humans and machine learning for detecting cyber threats.
SIGKDD Explor., 2019

Robust Invisible Video Watermarking with Attention.
CoRR, 2019

Learning Fair Classifiers in Online Stochastic Settings.
CoRR, 2019

MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data.
CoRR, 2019

SteganoGAN: High Capacity Image Steganography with GANs.
CoRR, 2019

Modeling Tabular data using Conditional GAN.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

eX2: a framework for interactive anomaly detection.
Proceedings of the Joint Proceedings of the ACM IUI 2019 Workshops co-located with the 24th ACM Conference on Intelligent User Interfaces (ACM IUI 2019), 2019

Enhancing Image Steganalysis with Adversarially Generated Examples.
Proceedings of the Cyber Security Cryptography and Machine Learning, 2019

TILM: Neural Language Models with Evolving Topical Influence.
Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019

ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning.
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Learning Vine Copula Models for Synthetic Data Generation.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Prediction Factory: automated development and collaborative evaluation of predictive models.
CoRR, 2018

Synthesizing Tabular Data using Generative Adversarial Networks.
CoRR, 2018

Machine learning 2.0 : Engineering Data Driven AI Products.
CoRR, 2018

Solving the False Positives Problem in Fraud Prediction Using Automated Feature Engineering.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018


Towards Building Active Defense Systems for Software Applications.
Proceedings of the Cyber Security Cryptography and Machine Learning, 2018

Augmenting Software Project Managers with Predictions from Machine Learning.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Acquire, adapt, and anticipate: continuous learning to block malicious domains.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
Solving the "false positives" problem in fraud prediction.
CoRR, 2017

FeatureHub: Towards Collaborative Data Science.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

AnonML: Locally Private Machine Learning over a Network of Peers.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Sample, Estimate, Tune: Scaling Bayesian Auto-Tuning of Data Science Pipelines.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Learning Representations for Log Data in Cybersecurity.
Proceedings of the Cyber Security Cryptography and Machine Learning, 2017

ATM: A distributed, collaborative, scalable system for automated machine learning.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
DropoutSeer: Visualizing learning patterns in Massive Open Online Courses for dropout reasoning and prediction.
Proceedings of the 11th IEEE Conference on Visual Analytics Science and Technology, 2016

Markov Switching Copula Models for Longitudinal Data.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Acting the Same Differently: A Cross-Course Comparison of User Behavior in MOOCs.
Proceedings of the 9th International Conference on Educational Data Mining, 2016

Robust Predictive Models on MOOCs : Transferring Knowledge across Courses.
Proceedings of the 9th International Conference on Educational Data Mining, 2016

What Would a Data Scientist Ask? Automatically Formulating and Solving Predictive Problems.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

The Synthetic Data Vault.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Label, Segment, Featurize: A Cross Domain Framework for Prediction Engineering.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

AI^2: Training a Big Data Machine to Defend.
Proceedings of the 2nd IEEE International Conference on Big Data Security on Cloud, 2016

2015
Fusion, Decision-Level.
Proceedings of the Encyclopedia of Biometrics, Second Edition, 2015

FlexGP - Cloud-Based Ensemble Learning with Genetic Programming for Large Regression Problems.
J. Grid Comput., 2015

Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning.
IEEE Comput. Intell. Mag., 2015

Autotuning algorithmic choice for input sensitivity.
Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2015

Feature Factory: Crowd Sourced Feature Discovery.
Proceedings of the Second ACM Conference on Learning @ Scale, 2015

Copula Graphical Models for Wind Resource Estimation.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Building Predictive Models via Feature Synthesis.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Deep feature synthesis: Towards automating data science endeavors.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Data science foundry for MOOCs.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Gaussian Process-Based Feature Selection for Wavelet Parameters: Predicting Acute Hypotensive Episodes from Physiological Signals.
Proceedings of the 28th IEEE International Symposium on Computer-Based Medical Systems, 2015

Transfer Learning for Predictive Models in Massive Open Online Courses.
Proceedings of the Artificial Intelligence in Education - 17th International Conference, 2015

2014
Using reinforcement learning to optimize occupant comfort and energy usage in HVAC systems.
J. Ambient Intell. Smart Environ., 2014

Towards Feature Engineering at Scale for Data from Massive Open Online Courses.
CoRR, 2014

MOOCdb: Developing Standards and Systems to Support MOOC Data Science.
CoRR, 2014

Likely to stop? Predicting Stopout in Massive Open Online Courses.
CoRR, 2014

A continuous developmental model for wind farm layout optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Flash: A GP-GPU Ensemble Learning System for Handling Large Datasets.
Proceedings of the Genetic Programming - 17th European Conference, 2014

OpenTuner: an extensible framework for program autotuning.
Proceedings of the International Conference on Parallel Architectures and Compilation, 2014

2013
Modeling Service Execution on Data Centers for Energy Efficiency and Quality of Service Monitoring.
Proceedings of the IEEE International Conference on Systems, 2013

On learning to generate wind farm layouts.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Learning regression ensembles with genetic programming at scale.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Efficient training set use for blood pressure prediction in a large scale learning classifier system.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Imprecise selection and fitness approximation in a large-scale evolutionary rule based system for blood pressure prediction.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Introducing graphical models to analyze genetic programming dynamics.
Proceedings of the Foundations of Genetic Algorithms XII, 2013

Cloud Scale Distributed Evolutionary Strategies for High Dimensional Problems.
Proceedings of the Applications of Evolutionary Computation - 16th European Conference, 2013

Cloud Driven Design of a Distributed Genetic Programming Platform.
Proceedings of the Applications of Evolutionary Computation - 16th European Conference, 2013

Developing Data Standards and Systems for MOOC Data Science.
Proceedings of the Workshops at the 16th International Conference on Artificial Intelligence in Education AIED 2013, 2013

2012
Knowledge mining sensory evaluation data: genetic programming, statistical techniques, and swarm optimization.
Genet. Program. Evolvable Mach., 2012

Graphical models and what they reveal about GP when it solves a symbolic regression problem.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

An investigation of local patterns for estimation of distribution genetic programming.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Flex-GP: Genetic Programming on the Cloud.
Proceedings of the Applications of Evolutionary Computation, 2012

Optimizing energy output and layout costs for large wind farms using particle swarm optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012

2011
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., 2011

Feature extraction from optimization samples via ensemble based symbolic regression.
Ann. Math. Artif. Intell., 2011

How Far Is It from Here to There? A Distance That Is Coherent with GP Operators.
Proceedings of the Genetic Programming - 14th European Conference, 2011

2010
Feature Extraction from Optimization Data via DataModeler's Ensemble Symbolic Regression.
Proceedings of the Learning and Intelligent Optimization, 4th International Conference, 2010

Knowledge mining with genetic programming methods for variable selection in flavor design.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Evolutionary optimization of flavors.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data.
Proceedings of the Genetic Programming, 13th European Conference, 2010

2009
Fusion, Decision-Level.
Proceedings of the Encyclopedia of Biometrics, 2009

Biometric Sensor Management: Tradeoffs in Time, Accuracy and Energy.
IEEE Syst. J., 2009

Situation assessment and autonomous control and optimisation of biometric sensor network.
Int. J. Biom., 2009

Achieving spectrum efficiency through signal design for ultra wide band sensor networks.
Proceedings of the 2009 IEEE Swarm Intelligence Symposium, 2009

A novel ultrawide band locationing system using swarm enabled learning approaches.
Proceedings of the 2009 IEEE Swarm Intelligence Symposium, 2009

Information sharing strategy among particles in Particle Swarm Optimization using Laplacian operator.
Proceedings of the 2009 IEEE Swarm Intelligence Symposium, 2009

Unsupervised learning and fusion for failure detection in wind turbines.
Proceedings of the 12th International Conference on Information Fusion, 2009

Fusing correlated data from multiple classifiers for improved biometric verification.
Proceedings of the 12th International Conference on Information Fusion, 2009

A particle swarm optimization based multilateration algorithm for UWB sensor network.
Proceedings of the 22nd Canadian Conference on Electrical and Computer Engineering, 2009

2008
Swarm intelligence based optimization and control of decentralized serial sensor networks.
Proceedings of the 2008 IEEE Swarm Intelligence Symposium, 2008

Decision-level fusion strategies for correlated biometric classifiers.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008

2007
Probabilistically Driven Particle Swarms for Optimization of Multi Valued Discrete Problems : Design and Analysis.
Proceedings of the 2007 IEEE Swarm Intelligence Symposium, 2007

Improving Classifier Fusion Using Particle Swarm Optimization.
Proceedings of the IEEE Symposium on Computational Intelligence in Multicriteria Decision Making, 2007

2005
An adaptive multimodal biometric management algorithm.
IEEE Trans. Syst. Man Cybern. Part C, 2005

2004
An Evolutionary Algorithm Based Approach for Dynamic Thresholding in Multimodal Biometrics.
Proceedings of the Biometric Authentication, First International Conference, 2004

2003
Fitness-distance-ratio based particle swarm optimization.
Proceedings of the 2003 IEEE Swarm Intelligence Symposium, 2003

Optimization Using Particle Swarms with Near Neighbor Interactions.
Proceedings of the Genetic and Evolutionary Computation, 2003


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