![](https://dblp.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
default search action
Kalyan Veeramachaneni
Person information
Refine list
![note](https://dblp.uni-trier.de/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
Journal Articles
- 2022
- [j16]Shubhra Kanti Karmaker Santu, Md. Mahadi Hassan, Micah J. Smith, Lei Xu, Chengxiang Zhai, Kalyan Veeramachaneni:
AutoML to Date and Beyond: Challenges and Opportunities. ACM Comput. Surv. 54(8): 175:1-175:36 (2022) - [j15]Dongyu Liu
, Sarah Alnegheimish, Alexandra Zytek, Kalyan Veeramachaneni:
MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series. Proc. ACM Hum. Comput. Interact. 6(CSCW1): 103:1-103:30 (2022) - [j14]Alexandra Zytek, Ignacio Arnaldo, Dongyu Liu
, Laure Berti-Équille, Kalyan Veeramachaneni:
The Need for Interpretable Features: Motivation and Taxonomy. SIGKDD Explor. 24(1): 1-13 (2022) - [j13]Furui Cheng
, Dongyu Liu
, Fan Du, Yanna Lin
, Alexandra Zytek, Haomin Li
, Huamin Qu, Kalyan Veeramachaneni:
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models. IEEE Trans. Vis. Comput. Graph. 28(1): 378-388 (2022) - [j12]Alexandra Zytek, Dongyu Liu
, Rhema Vaithianathan, Kalyan Veeramachaneni:
Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making. IEEE Trans. Vis. Comput. Graph. 28(1): 1161-1171 (2022) - 2021
- [j11]Micah J. Smith, Jürgen Cito, Kelvin Lu, Kalyan Veeramachaneni:
Enabling Collaborative Data Science Development with the Ballet Framework. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 431:1-431:39 (2021) - 2019
- [j10]Ignacio Arnaldo, Kalyan Veeramachaneni:
The Holy Grail of "Systems for Machine Learning": Teaming humans and machine learning for detecting cyber threats. SIGKDD Explor. 21(2): 39-47 (2019) - 2015
- [j9]Ignacio Arnaldo, Kalyan Veeramachaneni, Andrew Song, Una-May O'Reilly:
Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning. IEEE Comput. Intell. Mag. 10(1): 20-32 (2015) - [j8]Kalyan Veeramachaneni, Ignacio Arnaldo, Owen Derby, Una-May O'Reilly:
FlexGP - Cloud-Based Ensemble Learning with Genetic Programming for Large Regression Problems. J. Grid Comput. 13(3): 391-407 (2015) - 2014
- [j7]Pedro Fazenda
, Kalyan Veeramachaneni, Pedro U. Lima
, Una-May O'Reilly:
Using reinforcement learning to optimize occupant comfort and energy usage in HVAC systems. J. Ambient Intell. Smart Environ. 6(6): 675-690 (2014) - 2012
- [j6]Kalyan Veeramachaneni, Ekaterina Vladislavleva, Una-May O'Reilly:
Knowledge mining sensory evaluation data: genetic programming, statistical techniques, and swarm optimization. Genet. Program. Evolvable Mach. 13(1): 103-133 (2012) - 2011
- [j5]Kalyan Veeramachaneni, Ekaterina Vladislavleva, Una-May O'Reilly:
Feature extraction from optimization samples via ensemble based symbolic regression. Ann. Math. Artif. Intell. 61(2): 105-123 (2011) - [j4]Kalyan Veeramachaneni:
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. 12(2): 179-180 (2011) - 2009
- [j3]Kalyan Veeramachaneni, Lisa Ann Osadciw:
Situation assessment and autonomous control and optimisation of biometric sensor network. Int. J. Biom. 1(4): 495-524 (2009) - [j2]Kalyan Veeramachaneni, Lisa Ann Osadciw:
Biometric Sensor Management: Tradeoffs in Time, Accuracy and Energy. IEEE Syst. J. 3(4): 389-397 (2009) - 2005
- [j1]Kalyan Veeramachaneni, Lisa Ann Osadciw, Pramod K. Varshney:
An adaptive multimodal biometric management algorithm. IEEE Trans. Syst. Man Cybern. Part C 35(3): 344-356 (2005)
Conference and Workshop Papers
- 2022
- [c76]Lawrence Wong, Dongyu Liu
, Laure Berti-Équille, Sarah Alnegheimish, Kalyan Veeramachaneni:
AER: Auto-Encoder with Regression for Time Series Anomaly Detection. IEEE Big Data 2022: 1152-1161 - [c75]Lei Xu, Laure Berti-Équille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
In Situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers. ICONIP (3) 2022: 485-496 - [c74]Lei Xu, Alfredo Cuesta-Infante, Laure Berti-Équille, Kalyan Veeramachaneni:
R&R: Metric-guided Adversarial Sentence Generation. AACL/IJCNLP (Findings) 2022: 438-452 - [c73]Sarah Alnegheimish, Dongyu Liu
, Carles Sala, Laure Berti-Équille, Kalyan Veeramachaneni:
Sintel: A Machine Learning Framework to Extract Insights from Signals. SIGMOD Conference 2022: 1855-1865 - 2021
- [c72]Alexandra Zytek, Dongyu Liu
, Rhema Vaithianathan, Kalyan Veeramachaneni:
Sibyl: Explaining Machine Learning Models for High-Stakes Decision Making. CHI Extended Abstracts 2021: 315:1-315:6 - [c71]Yi Sun, Iván Ramírez Díaz, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
Towards Reducing Biases in Combining Multiple Experts Online. IJCAI 2021: 3024-3030 - 2020
- [c70]Alexander Geiger, Dongyu Liu
, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks. IEEE BigData 2020: 33-43 - [c69]Dongyu Liu
, Micah J. Smith, Kalyan Veeramachaneni:
Understanding User-Bot Interactions for Small-Scale Automation in Open-Source Development. CHI Extended Abstracts 2020: 1-8 - [c68]Sarah Alnegheimish, Najat Alrashed, Faisal Aleissa, Shahad Althobaiti, Dongyu Liu
, Mansour Alsaleh, Kalyan Veeramachaneni:
Cardea: An Open Automated Machine Learning Framework for Electronic Health Records. DSAA 2020: 536-545 - [c67]Micah J. Smith, Carles Sala, James Max Kanter, Kalyan Veeramachaneni:
The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development. SIGMOD Conference 2020: 785-800 - 2019
- [c66]Yi Sun, Alfredo Cuesta-Infante
, Kalyan Veeramachaneni:
Learning Vine Copula Models for Synthetic Data Generation. AAAI 2019: 5049-5057 - [c65]Qianwen Wang
, Yao Ming, Zhihua Jin
, Qiaomu Shen
, Dongyu Liu
, Micah J. Smith, Kalyan Veeramachaneni, Huamin Qu:
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning. CHI 2019: 681 - [c64]Shubhra Kanti Karmaker Santu, Kalyan Veeramachaneni, Chengxiang Zhai:
TILM: Neural Language Models with Evolving Topical Influence. CoNLL 2019: 778-788 - [c63]Kevin Alex Zhang, Kalyan Veeramachaneni:
Enhancing Image Steganalysis with Adversarially Generated Examples. CSCML 2019: 169-177 - [c62]Ignacio Arnaldo, Kalyan Veeramachaneni, Mei Lam:
eX2: a framework for interactive anomaly detection. IUI Workshops 2019 - [c61]Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante
, Kalyan Veeramachaneni:
Modeling Tabular data using Conditional GAN. NeurIPS 2019: 7333-7343 - 2018
- [c60]Ignacio Arnaldo, Ankit Arun, Sumeeth Kyathanahalli, Kalyan Veeramachaneni:
Acquire, adapt, and anticipate: continuous learning to block malicious domains. IEEE BigData 2018: 1891-1898 - [c59]Benjamin Schreck, Shankar Mallapur, Sarvesh Damle, Nitin John James, Sanjeev Vohra, Rajendra Prasad, Kalyan Veeramachaneni:
Augmenting Software Project Managers with Predictions from Machine Learning. IEEE BigData 2018: 2004-2011 - [c58]Zara Perumal, Kalyan Veeramachaneni:
Towards Building Active Defense Systems for Software Applications. CSCML 2018: 144-161 - [c57]Dennis G. Wilson, Silvio Rodrigues, Carlos Segura
, Ilya Loshchilov, Frank Hutter, Guillermo López Buenfil, Ahmed Kheiri
, Ed Keedwell, Mario Ocampo-Pineda, Ender Özcan
, Sergio Iwan Valdez Pea, Brian Goldman, Salvador Botello Rionda, Arturo Hernández Aguirre, Kalyan Veeramachaneni, Sylvain Cussat-Blanc:
Summary of evolutionary computation for wind farm layout optimization. GECCO (Companion) 2018: 31-32 - [c56]Roy Wedge, James Max Kanter, Kalyan Veeramachaneni, Santiago Moral-Rubio, Sergio Iglesias Perez:
Solving the False Positives Problem in Fraud Prediction Using Automated Feature Engineering. ECML/PKDD (3) 2018: 372-388 - 2017
- [c55]Thomas Swearingen, Will Drevo, Bennett Cyphers, Alfredo Cuesta-Infante
, Arun Ross, Kalyan Veeramachaneni:
ATM: A distributed, collaborative, scalable system for automated machine learning. IEEE BigData 2017: 151-162 - [c54]Ignacio Arnaldo, Alfredo Cuesta-Infante
, Ankit Arun, Mei Lam, Costas Bassias, Kalyan Veeramachaneni:
Learning Representations for Log Data in Cybersecurity. CSCML 2017: 250-268 - [c53]Alec Anderson, Sébastien Dubois, Alfredo Cuesta-Infante
, Kalyan Veeramachaneni:
Sample, Estimate, Tune: Scaling Bayesian Auto-Tuning of Data Science Pipelines. DSAA 2017: 361-372 - [c52]Bennett Cyphers, Kalyan Veeramachaneni:
AnonML: Locally Private Machine Learning over a Network of Peers. DSAA 2017: 549-560 - [c51]Micah J. Smith, Roy Wedge, Kalyan Veeramachaneni:
FeatureHub: Towards Collaborative Data Science. DSAA 2017: 590-600 - 2016
- [c50]Kalyan Veeramachaneni, Ignacio Arnaldo, Vamsi Korrapati, Constantinos Bassias, Ke Li:
AI^2: Training a Big Data Machine to Defend. BigDataSecurity/HPSC/IDS 2016: 49-54 - [c49]Neha Patki, Roy Wedge, Kalyan Veeramachaneni:
The Synthetic Data Vault. DSAA 2016: 399-410 - [c48]James Max Kanter, Owen Gillespie, Kalyan Veeramachaneni:
Label, Segment, Featurize: A Cross Domain Framework for Prediction Engineering. DSAA 2016: 430-439 - [c47]Benjamin Schreck, Kalyan Veeramachaneni:
What Would a Data Scientist Ask? Automatically Formulating and Solving Predictive Problems. DSAA 2016: 440-451 - [c46]Sebastien Boyer, Kalyan Veeramachaneni:
Robust Predictive Models on MOOCs : Transferring Knowledge across Courses. EDM 2016: 298-305 - [c45]Ben U. Gelman, Matt Revelle, Carlotta Domeniconi, Kalyan Veeramachaneni, Aditya Johri:
Acting the Same Differently: A Cross-Course Comparison of User Behavior in MOOCs. EDM 2016: 376-381 - [c44]Alfredo Cuesta-Infante
, Kalyan Veeramachaneni:
Markov Switching Copula Models for Longitudinal Data. ICDM Workshops 2016: 1104-1109 - [c43]Yuanzhe Chen, Qing Chen
, Mingqian Zhao, Sebastien Boyer, Kalyan Veeramachaneni, Huamin Qu:
DropoutSeer: Visualizing learning patterns in Massive Open Online Courses for dropout reasoning and prediction. VAST 2016: 111-120 - 2015
- [c42]Sebastien Boyer, Kalyan Veeramachaneni:
Transfer Learning for Predictive Models in Massive Open Online Courses. AIED 2015: 54-63 - [c41]Franck Dernoncourt, Kalyan Veeramachaneni, Una-May O'Reilly:
Gaussian Process-Based Feature Selection for Wavelet Parameters: Predicting Acute Hypotensive Episodes from Physiological Signals. CBMS 2015: 145-150 - [c40]Sebastien Boyer, Ben U. Gelman, Benjamin Schreck, Kalyan Veeramachaneni:
Data science foundry for MOOCs. DSAA 2015: 1-10 - [c39]James Max Kanter, Kalyan Veeramachaneni:
Deep feature synthesis: Towards automating data science endeavors. DSAA 2015: 1-10 - [c38]Ignacio Arnaldo, Una-May O'Reilly, Kalyan Veeramachaneni:
Building Predictive Models via Feature Synthesis. GECCO 2015: 983-990 - [c37]Kalyan Veeramachaneni, Alfredo Cuesta-Infante, Una-May O'Reilly:
Copula Graphical Models for Wind Resource Estimation. IJCAI 2015: 2646-2654 - [c36]Kalyan Veeramachaneni, Kiarash Adl, Una-May O'Reilly:
Feature Factory: Crowd Sourced Feature Discovery. L@S 2015: 373-376 - [c35]Yufei Ding, Jason Ansel, Kalyan Veeramachaneni, Xipeng Shen
, Una-May O'Reilly, Saman P. Amarasinghe
:
Autotuning algorithmic choice for input sensitivity. PLDI 2015: 379-390 - 2014
- [c34]Jason Ansel, Shoaib Kamil, Kalyan Veeramachaneni, Jonathan Ragan-Kelley, Jeffrey Bosboom
, Una-May O'Reilly, Saman P. Amarasinghe
:
OpenTuner: an extensible framework for program autotuning. PACT 2014: 303-316 - [c33]Ignacio Arnaldo, Kalyan Veeramachaneni, Una-May O'Reilly:
Flash: A GP-GPU Ensemble Learning System for Handling Large Datasets. EuroGP 2014: 13-24 - [c32]Dennis Wilson, Sylvain Cussat-Blanc, Kalyan Veeramachaneni, Una-May O'Reilly, Hervé Luga
:
A continuous developmental model for wind farm layout optimization. GECCO 2014: 745-752 - 2013
- [c31]Kalyan Veeramachaneni, Franck Dernoncourt, Colin Taylor, Zachary A. Pardos, Una-May O'Reilly:
Developing Data Standards and Systems for MOOC Data Science. AIED Workshops 2013 - [c30]Owen Derby, Kalyan Veeramachaneni, Una-May O'Reilly:
Cloud Driven Design of a Distributed Genetic Programming Platform. EvoApplications 2013: 509-518 - [c29]Dennis Wilson, Kalyan Veeramachaneni, Una-May O'Reilly:
Cloud Scale Distributed Evolutionary Strategies for High Dimensional Problems. EvoApplications 2013: 519-528 - [c28]Erik Hemberg, Constantin Berzan, Kalyan Veeramachaneni, Una-May O'Reilly:
Introducing graphical models to analyze genetic programming dynamics. FOGA 2013: 75-86 - [c27]Erik Hemberg, Kalyan Veeramachaneni, Franck Dernoncourt, Mark Wagy, Una-May O'Reilly:
Imprecise selection and fitness approximation in a large-scale evolutionary rule based system for blood pressure prediction. GECCO (Companion) 2013: 153-154 - [c26]Dennis Wilson, Emmanuel Awa, Sylvain Cussat-Blanc, Kalyan Veeramachaneni, Una-May O'Reilly:
On learning to generate wind farm layouts. GECCO 2013: 767-774 - [c25]Kalyan Veeramachaneni, Owen Derby, Dylan Sherry, Una-May O'Reilly:
Learning regression ensembles with genetic programming at scale. GECCO 2013: 1117-1124 - [c24]Erik Hemberg, Kalyan Veeramachaneni, Franck Dernoncourt, Mark Wagy, Una-May O'Reilly:
Efficient training set use for blood pressure prediction in a large scale learning classifier system. GECCO (Companion) 2013: 1267-1274 - [c23]Monica Vitali
, Una-May O'Reilly, Kalyan Veeramachaneni:
Modeling Service Execution on Data Centers for Energy Efficiency and Quality of Service Monitoring. SMC 2013: 103-108 - 2012
- [c22]Kalyan Veeramachaneni, Markus Wagner
, Una-May O'Reilly, Frank Neumann
:
Optimizing energy output and layout costs for large wind farms using particle swarm optimization. IEEE Congress on Evolutionary Computation 2012: 1-7 - [c21]Dylan Sherry, Kalyan Veeramachaneni, James McDermott, Una-May O'Reilly:
Flex-GP: Genetic Programming on the Cloud. EvoApplications 2012: 477-486 - [c20]Erik Hemberg, Kalyan Veeramachaneni, Una-May O'Reilly:
Graphical models and what they reveal about GP when it solves a symbolic regression problem. GECCO (Companion) 2012: 493-494 - [c19]Erik Hemberg, Kalyan Veeramachaneni, James McDermott, Constantin Berzan, Una-May O'Reilly:
An investigation of local patterns for estimation of distribution genetic programming. GECCO 2012: 767-774 - 2011
- [c18]James McDermott, Una-May O'Reilly, Leonardo Vanneschi
, Kalyan Veeramachaneni:
How Far Is It from Here to There? A Distance That Is Coherent with GP Operators. EuroGP 2011: 190-202 - 2010
- [c17]Katya Vladislavleva, Kalyan Veeramachaneni, Una-May O'Reilly, Matt Burland, Jason Parcon:
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data. EuroGP 2010: 244-255 - [c16]Katya Vladislavleva, Kalyan Veeramachaneni, Matt Burland, Jason Parcon, Una-May O'Reilly:
Knowledge mining with genetic programming methods for variable selection in flavor design. GECCO 2010: 941-948 - [c15]Kalyan Veeramachaneni, Katya Vladislavleva, Matt Burland, Jason Parcon, Una-May O'Reilly:
Evolutionary optimization of flavors. GECCO 2010: 1291-1298 - [c14]Kalyan Veeramachaneni, Katya Vladislavleva, Una-May O'Reilly:
Feature Extraction from Optimization Data via DataModeler's Ensemble Symbolic Regression. LION 2010: 251-265 - 2009
- [c13]Weihua Gao, Ganapathi Kamath
, Kalyan Veeramachaneni, Lisa Ann Osadciw:
A particle swarm optimization based multilateration algorithm for UWB sensor network. CCECE 2009: 950-953 - [c12]Xiang Ye, Kalyan Veeramachaneni, Yanjun Yan, Lisa Ann Osadciw:
Unsupervised learning and fusion for failure detection in wind turbines. FUSION 2009: 1497-1503 - [c11]Nisha Srinivas, Kalyan Veeramachaneni, Lisa Ann Osadciw:
Fusing correlated data from multiple classifiers for improved biometric verification. FUSION 2009: 1504-1511 - [c10]Jagdish Chand Bansal
, Kusum Deep
, Kalyan Veeramachaneni, Lisa Ann Osadciw:
Information sharing strategy among particles in Particle Swarm Optimization using Laplacian operator. SIS 2009: 30-36 - [c9]Weihua Gao, Kalyan Veeramachaneni, Lisa Ann Osadciw:
Achieving spectrum efficiency through signal design for ultra wide band sensor networks. SIS 2009: 122-128 - [c8]Weihua Gao, Kalyan Veeramachaneni, Ganapathi Kamath
, Lisa Ann Osadciw:
A novel ultrawide band locationing system using swarm enabled learning approaches. SIS 2009: 129-136 - 2008
- [c7]Kalyan Veeramachaneni, Lisa Ann Osadciw, Arun Ross, Nisha Srinivas:
Decision-level fusion strategies for correlated biometric classifiers. CVPR Workshops 2008: 1-6 - [c6]Kalyan Veeramachaneni, Lisa Ann Osadciw:
Swarm intelligence based optimization and control of decentralized serial sensor networks. SIS 2008: 1-8 - 2007
- [c5]Kalyan Veeramachaneni, Weizhong Yan, Kai Goebel, Lisa Ann Osadciw:
Improving Classifier Fusion Using Particle Swarm Optimization. MCDM 2007: 128-135 - [c4]Kalyan Veeramachaneni, Lisa Ann Osadciw, Ganapathi Kamath
:
Probabilistically Driven Particle Swarms for Optimization of Multi Valued Discrete Problems : Design and Analysis. SIS 2007: 141-149 - 2004
- [c3]Kalyan Veeramachaneni, Lisa Ann Osadciw, Pramod K. Varshney:
An Evolutionary Algorithm Based Approach for Dynamic Thresholding in Multimodal Biometrics. ICBA 2004: 671-677 - 2003
- [c2]Kalyan Veeramachaneni, Thanmaya Peram, Chilukuri K. Mohan, Lisa Ann Osadciw:
Optimization Using Particle Swarms with Near Neighbor Interactions. GECCO 2003: 110-121 - [c1]Thanmaya Peram, Kalyan Veeramachaneni, Chilukuri K. Mohan:
Fitness-distance-ratio based particle swarm optimization. SIS 2003: 174-181
Reference Works
- 2015
- [r2]Lisa Ann Osadciw, Kalyan Veeramachaneni:
Fusion, Decision-Level. Encyclopedia of Biometrics 2015: 747-751 - 2009
- [r1]Lisa Ann Osadciw, Kalyan Veeramachaneni:
Fusion, Decision-Level. Encyclopedia of Biometrics 2009: 593-597
Informal and Other Publications
- 2024
- [i35]Lei Xu, Sarah Alnegheimish, Laure Berti-Équille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
Single Word Change is All You Need: Designing Attacks and Defenses for Text Classifiers. CoRR abs/2401.17196 (2024) - [i34]Alexandra Zytek, Sara Pidò, Kalyan Veeramachaneni:
LLMs for XAI: Future Directions for Explaining Explanations. CoRR abs/2405.06064 (2024) - [i33]Sarah Alnegheimish, Linh Nguyen, Laure Berti-Équille, Kalyan Veeramachaneni:
Large language models can be zero-shot anomaly detectors for time series? CoRR abs/2405.14755 (2024) - 2023
- [i32]Sarah Alnegheimish, Laure Berti-Équille, Kalyan Veeramachaneni:
Making the End-User a Priority in Benchmarking: OrionBench for Unsupervised Time Series Anomaly Detection. CoRR abs/2310.17748 (2023) - [i31]Alexandra Zytek, Wei-En Wang, Sofia Koukoura, Kalyan Veeramachaneni:
Lessons from Usable ML Deployments and Application to Wind Turbine Monitoring. CoRR abs/2312.02859 (2023) - [i30]Alexandra Zytek, Wei-En Wang, Dongyu Liu
, Laure Berti-Équille, Kalyan Veeramachaneni:
Pyreal: A Framework for Interpretable ML Explanations. CoRR abs/2312.13084 (2023) - 2022
- [i29]Alexandra Zytek, Ignacio Arnaldo, Dongyu Liu, Laure Berti-Équille, Kalyan Veeramachaneni:
The Need for Interpretable Features: Motivation and Taxonomy. CoRR abs/2202.11748 (2022) - [i28]Sarah Alnegheimish, Dongyu Liu, Carles Sala, Laure Berti-Équille, Kalyan Veeramachaneni:
Sintel: A Machine Learning Framework to Extract Insights from Signals. CoRR abs/2204.09108 (2022) - [i27]Kevin Alex Zhang, Neha Patki, Kalyan Veeramachaneni:
Sequential Models in the Synthetic Data Vault. CoRR abs/2207.14406 (2022) - [i26]Lawrence Wong, Dongyu Liu, Laure Berti-Équille, Sarah Alnegheimish, Kalyan Veeramachaneni:
AER: Auto-Encoder with Regression for Time Series Anomaly Detection. CoRR abs/2212.13558 (2022) - 2021
- [i25]Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan, Kalyan Veeramachaneni:
Understanding the Usability Challenges of Machine Learning In High-Stakes Decision Making. CoRR abs/2103.02071 (2021) - [i24]Dongyu Liu, Kalyan Veeramachaneni, Alexander Geiger, Victor O. K. Li, Huamin Qu:
AQEyes: Visual Analytics for Anomaly Detection and Examination of Air Quality Data. CoRR abs/2103.12910 (2021) - [i23]Micah J. Smith, Jürgen Cito, Kalyan Veeramachaneni:
Meeting in the notebook: a notebook-based environment for micro-submissions in data science collaborations. CoRR abs/2103.15787 (2021) - [i22]Lei Xu, Kalyan Veeramachaneni:
Attacking Text Classifiers via Sentence Rewriting Sampler. CoRR abs/2104.08453 (2021) - [i21]Furui Cheng, Dongyu Liu, Fan Du, Yanna Lin, Alexandra Zytek, Haomin Li, Huamin Qu, Kalyan Veeramachaneni:
VBridge: Connecting the Dots Between Features, Explanations, and Data for Healthcare Models. CoRR abs/2108.02550 (2021) - [i20]Dongyu Liu, Sarah Alnegheimish, Alexandra Zytek, Kalyan Veeramachaneni:
MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series. CoRR abs/2112.05734 (2021) - 2020
- [i19]Alexander Geiger, Dongyu Liu, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks. CoRR abs/2009.07769 (2020) - [i18]Sarah Alnegheimish, Najat Alrashed, Faisal Aleissa, Shahad Althobaiti, Dongyu Liu, Mansour Alsaleh, Kalyan Veeramachaneni:
Cardea: An Open Automated Machine Learning Framework for Electronic Health Records. CoRR abs/2010.00509 (2020) - [i17]Shubhra Kanti Karmaker Santu, Md. Mahadi Hassan, Micah J. Smith, Lei Xu, ChengXiang Zhai, Kalyan Veeramachaneni:
A Level-wise Taxonomic Perspective on Automated Machine Learning to Date and Beyond: Challenges and Opportunities. CoRR abs/2010.10777 (2020) - [i16]Micah J. Smith, Jürgen Cito, Kelvin Lu, Kalyan Veeramachaneni:
Enabling collaborative data science development with the Ballet framework. CoRR abs/2012.07816 (2020) - 2019
- [i15]Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu, Kalyan Veeramachaneni:
SteganoGAN: High Capacity Image Steganography with GANs. CoRR abs/1901.03892 (2019) - [i14]Qianwen Wang, Yao Ming, Zhihua Jin, Qiaomu Shen, Dongyu Liu, Micah J. Smith, Kalyan Veeramachaneni, Huamin Qu:
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning. CoRR abs/1902.05009 (2019) - [i13]Micah J. Smith, Carles Sala, James Max Kanter, Kalyan Veeramachaneni:
The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development. CoRR abs/1905.08942 (2019) - [i12]Lei Xu, Shubhra Kanti Karmaker Santu, Kalyan Veeramachaneni:
MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data. CoRR abs/1906.12348 (2019) - [i11]Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
Modeling Tabular data using Conditional GAN. CoRR abs/1907.00503 (2019) - [i10]Yi Sun, Iván Ramírez, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
Learning Fair Classifiers in Online Stochastic Settings. CoRR abs/1908.07009 (2019) - [i9]Kevin Alex Zhang, Lei Xu, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
Robust Invisible Video Watermarking with Attention. CoRR abs/1909.01285 (2019) - 2018
- [i8]James Max Kanter, Benjamin Schreck, Kalyan Veeramachaneni:
Machine learning 2.0 : Engineering Data Driven AI Products. CoRR abs/1807.00401 (2018) - [i7]Lei Xu, Kalyan Veeramachaneni:
Synthesizing Tabular Data using Generative Adversarial Networks. CoRR abs/1811.11264 (2018) - [i6]Gaurav Sheni, Benjamin Schreck, Roy Wedge, James Max Kanter, Kalyan Veeramachaneni:
Prediction Factory: automated development and collaborative evaluation of predictive models. CoRR abs/1811.11960 (2018) - [i5]Yi Sun, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
Learning Vine Copula Models For Synthetic Data Generation. CoRR abs/1812.01226 (2018) - 2017
- [i4]Roy Wedge, James Max Kanter, Santiago Moral-Rubio, Sergio Iglesias Perez, Kalyan Veeramachaneni:
Solving the "false positives" problem in fraud prediction. CoRR abs/1710.07709 (2017) - 2014
- [i3]Kalyan Veeramachaneni, Sherif A. Halawa, Franck Dernoncourt, Una-May O'Reilly, Colin Taylor, Chuong B. Do:
MOOCdb: Developing Standards and Systems to Support MOOC Data Science. CoRR abs/1406.2015 (2014) - [i2]Kalyan Veeramachaneni, Una-May O'Reilly, Colin Taylor:
Towards Feature Engineering at Scale for Data from Massive Open Online Courses. CoRR abs/1407.5238 (2014) - [i1]Colin Taylor, Kalyan Veeramachaneni, Una-May O'Reilly:
Likely to stop? Predicting Stopout in Massive Open Online Courses. CoRR abs/1408.3382 (2014)
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-06-20 21:32 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint