Karthikeyan Natesan Ramamurthy

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 105

Top Venues

Arizona State University, Tempe, USA (PHD)

Education History

Arizona State University, Tempe, USA

PHD

Publications

Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy, Maria Chang, Moninder Singh
Reasoning about concepts with LLMs: Inconsistencies abound. CoRR (2024)
Weizhi Li, Prad Kadambi, Pouria Saidi, Karthikeyan Natesan Ramamurthy, Gautam Dasarathy, Visar Berisha
Active Sequential Two-Sample Testing. Trans. Mach. Learn. Res. 2024 (2024)
Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf, Joan Byamugisha, Maria Chang, Pierre L. Dognin, Eitan Farchi, Ndivhuwo Makondo, Aleksandra Mojsilovic, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Inkit Padhi, Orna Raz, Jesus Rios, Prasanna Sattigeri, Moninder Singh, Siphiwe Thwala, Rosario A. Uceda-Sosa, Kush R. Varshney
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations. CoRR (2024)
Theodore Papamarkou, Tolga Birdal, Michael Bronstein, Gunnar Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR (2024)
Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy
Ranking Large Language Models without Ground Truth. ACL (Findings) (2024)
Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh
Multi-Level Explanations for Generative Language Models. CoRR (2024)
Mustafa Hajij, Mathilde Papillon, Florian Frantzen, Jens Agerberg, Ibrahem AlJabea, Rubén Ballester, Claudio Battiloro, Guillermo Bernárdez, Tolga Birdal, Aiden Brent, Peter Chin, Sergio Escalera, Simone Fiorellino, Odin Hoff Gardaa, Gurusankar Gopalakrishnan, Devendra Govil, Josef Hoppe, Maneel Reddy Karri, Jude Khouja, Manuel Lecha, Neal Livesay, Jan Meißner, Soham Mukherjee, Alexander Nikitin, Theodore Papamarkou, Jaro Prílepok, Karthikeyan Natesan Ramamurthy, Paul Rosen, Aldo Guzmán-Sáenz, Alessandro Salatiello, Shreyas N. Samaga, Simone Scardapane, Michael T. Schaub, Luca Scofano, Indro Spinelli, Lev Telyatnikov, Quang Truong, Robin Walters, Maosheng Yang, Olga Zaghen, Ghada Zamzmi, Ali Zia, Nina Miolane
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains. CoRR (2024)
Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy
Ranking Large Language Models without Ground Truth. CoRR (2024)
Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy
Trust Regions for Explanations via Black-Box Probabilistic Certification. CoRR (2024)
Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. AAAI (2023)
Weizhi Li, Karthikeyan Natesan Ramamurthy, Prad Kadambi, Pouria Saidi, Gautam Dasarathy, Visar Berisha
Active Sequential Two-Sample Testing. CoRR (2023)
Karthikeyan Natesan Ramamurthy, Aldo Guzmán-Sáenz, Mustafa Hajij
Topo-MLP : A Simplicial Network Without Message Passing. CoRR (2023)
Erik Miehling, Rahul Nair, Elizabeth Daly, Karthikeyan Natesan Ramamurthy, Robert Redmond
Cookie Consent Has Disparate Impact on Estimation Accuracy. NeurIPS (2023)
Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML (2023)
Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy
The Impact of Positional Encoding on Length Generalization in Transformers. NeurIPS (2023)
Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy
The Impact of Positional Encoding on Length Generalization in Transformers. CoRR (2023)
Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meisner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.
ICML 2023 Topological Deep Learning Challenge : Design and Results. CoRR (2023)
Karthikeyan Natesan Ramamurthy, Aldo Guzmán-Sáenz, Mustafa Hajij
TOPO-MLP : A Simplicial Network without Message Passing. ICASSP (2023)
Tim Draws, Karthikeyan Natesan Ramamurthy, Ioana Baldini, Amit Dhurandhar, Inkit Padhi, Benjamin Timmermans, Nava Tintarev
Explainable Cross-Topic Stance Detection for Search Results. CHIIR (2023)
Manish Nagireddy, Moninder Singh, Samuel C. Hoffman, Evaline Ju, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions. CoRR (2023)
Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Kartik Ahuja, Vijay Arya
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning. NeurIPS (2023)
Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush Varshney, Amit Dhurandhar, Juan E. Gilbert
Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness. FAccT (2023)
Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang
Uncertainty Quantification 360: A Hands-on Tutorial. COMAD/CODS (2022)
Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. CoRR (2022)
Karthikeyan Natesan Ramamurthy, Amit Dhurandhar, Dennis Wei, Zaid Bin Tariq
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners. CoRR (2022)
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
A label efficient two-sample test. UAI (2022)
Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, Nina Miolane, Aldo Guzmán-Sáenz, Karthikeyan Natesan Ramamurthy
Higher-Order Attention Networks. CoRR (2022)
Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. ICASSP (2022)
Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, Mikhail Yurochkin
Your fairness may vary: Pretrained language model fairness in toxic text classification. ACL (Findings) (2022)
Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam
Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations. NeurIPS (2022)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon
Optimized Score Transformation for Consistent Fair Classification. J. Mach. Learn. Res. 22 (2021)
Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh
Ground-Truth, Whose Truth? - Examining the Challenges with Annotating Toxic Text Datasets. CoRR (2021)
Peng Zheng, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin
Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. Open J. Math. Optim. 2 (2021)
Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang
Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI. CoRR (2021)
Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu
Conditionally independent data generation. UAI (2021)
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
A label efficient two-sample test. CoRR (2021)
Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. CoRR (2021)
Mustafa Hajij, Ghada Zamzmi, Karthikeyan Natesan Ramamurthy, Aldo Guzmán-Sáenz
Data-Centric AI Requires Rethinking Data Notion. CoRR (2021)
Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Mikhail Yurochkin, Moninder Singh
Your fairness may vary: Group fairness of pretrained language models in toxic text classification. CoRR (2021)
Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman
A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications. AAAI (2020)
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
Finding the Homology of Decision Boundaries with Active Learning. NeurIPS (2020)
Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. ICLR (2020)
Anirudh Som, Hongjun Choi, Karthikeyan Natesan Ramamurthy, Matthew P. Buman, Pavan K. Turaga
PI-Net: A Deep Learning Approach to Extract Topological Persistence Images. CVPR Workshops (2020)
Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. CoRR (2020)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon
Optimized Score Transformation for Fair Classification. AISTATS (2020)
Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
Crowd Counting with Decomposed Uncertainty. AAAI (2020)
Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Bhavya Kailkhura
Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions. ACSSC (2020)
Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das
Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. CoRR (2020)
Wael Alghamdi, Shahab Asoodeh, Hao Wang, Flávio P. Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy
Model Projection: Theory and Applications to Fair Machine Learning. ISIT (2020)
Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar
Model Agnostic Multilevel Explanations. NeurIPS (2020)
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
Finding the Homology of Decision Boundaries with Active Learning. CoRR (2020)
Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar
Model Agnostic Multilevel Explanations. CoRR (2020)
Michael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
TED: Teaching AI to Explain its Decisions. AIES (2019)
Anirudh Som, Hongjun Choi, Karthikeyan Natesan Ramamurthy, Matthew P. Buman, Pavan K. Turaga
PI-Net: A Deep Learning Approach to Extract Topological Persistence Images. CoRR (2019)
Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody
Topological Data Analysis of Decision Boundaries with Application to Model Selection. ICML (2019)
Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman
Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies. CoRR (2019)
Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
Crowd Counting with Decomposed Uncertainty. CoRR (2019)
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
Think Your Artificial Intelligence Software Is Fair? Think Again. IEEE Softw. 36 (4) (2019)
Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty
Fair Transfer Learning with Missing Protected Attributes. AIES (2019)
Matthew Arnold, Rachel K. E. Bellamy, Michael Hind, Stephanie Houde, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Alexandra Olteanu, David Piorkowski, Darrell Reimer, John T. Richards, Jason Tsay, Kush R. Varshney
FactSheets: Increasing trust in AI services through supplier's declarations of conformity. IBM J. Res. Dev. 63 (4/5) (2019)
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM J. Res. Dev. 63 (4/5) (2019)
Pranay Kr. Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R. Varshney, Ruchir Puri
Bias Mitigation Post-processing for Individual and Group Fairness. ICASSP (2019)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon
Optimized Score Transformation for Fair Classification. CoRR (2019)
Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
Counting and Segmenting Sorghum Heads. CoRR (2019)
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning. CoRR (2019)
Ming Yu, Karthikeyan Natesan Ramamurthy, Addie M. Thompson, Aurélie C. Lozano
Simultaneous Parameter Learning and Bi-clustering for Multi-Response Models. Frontiers Big Data 2 (2019)
Moninder Singh, Karthikeyan Natesan Ramamurthy
Understanding racial bias in health using the Medical Expenditure Panel Survey data. CoRR (2019)
Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. Comput. Graph. Forum 37 (3) (2018)
Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis. IEEE J. Sel. Top. Signal Process. 12 (5) (2018)
Anirudh Som, Kowshik Thopalli, Karthikeyan Natesan Ramamurthy, Vinay Venkataraman, Ankita Shukla, Pavan K. Turaga
Perturbation Robust Representations of Topological Persistence Diagrams. ECCV (7) (2018)
Pranay Kr. Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R. Varshney, Ruchir Puri
Bias Mitigation Post-processing for Individual and Group Fairness. CoRR (2018)
Anirudh Som, Kowshik Thopalli, Karthikeyan Natesan Ramamurthy, Vinay Venkataraman, Ankita Shukla, Pavan K. Turaga
Perturbation Robust Representations of Topological Persistence Diagrams. CoRR (2018)
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
TED: Teaching AI to Explain its Decisions. CoRR (2018)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Distribution-preserving k-anonymity. Stat. Anal. Data Min. 11 (6) (2018)
Michael Hind, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Alexandra Olteanu, Kush R. Varshney
Increasing Trust in AI Services through Supplier's Declarations of Conformity. CoRR (2018)
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
Teaching Meaningful Explanations. CoRR (2018)
Peder A. Olsen, Karthikeyan Natesan Ramamurthy, Javier Ribera, Yuhao Chen, Addie M. Thompson, Ronny Luss, Mitch Tuinstra, Naoki Abe
Detecting and Counting Panicles in Sorghum Images. DSAA (2018)
Ming Yu, Karthikeyan Natesan Ramamurthy, Addie M. Thompson, Aurélie C. Lozano
Simultaneous Parameter Learning and Bi-Clustering for Multi-Response Models. CoRR (2018)
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias. CoRR (2018)
Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody
Topological Data Analysis of Decision Boundaries with Application to Model Selection. CoRR (2018)
Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier
Distributed Bundle Adjustment. ICCV Workshops (2017)
Samiulla Shaikh, Harit Vishwakarma, Sameep Mehta, Kush R. Varshney, Karthikeyan Natesan Ramamurthy, Dennis Wei
An End-To-End Machine Learning Pipeline That Ensures Fairness Policies. CoRR (2017)
Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier
Distributed Bundle Adjustment. CoRR (2017)
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias
A deep learning approach to multiple kernel fusion. ICASSP (2017)
Karthikeyan Natesan Ramamurthy, Dennis Wei, Emily Ray, Moninder Singh, Vijay S. Iyengar, Dmitriy A. Katz-Rogozhnikov, Jingwei Yang, Kevin N. Tran, Gigi Y. Yuen-Reed
A configurable, big data system for on-demand healthcare cost prediction. IEEE BigData (2017)
Anirudh Som, Narayanan Krishnamurthi, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga
Multiscale evolution of attractor-shape descriptors for assessing Parkinson's disease severity. GlobalSIP (2017)
Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy
Learning Robust Representations for Computer Vision. ICCV Workshops (2017)
Flávio du Pin Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Optimized Data Pre-Processing for Discrimination Prevention. CoRR (2017)
Moninder Singh, Karthikeyan Natesan Ramamurthy, Shrihari Vasudevan
Propensity modeling for employee Re-skilling. GlobalSIP (2017)
Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Optimized Pre-Processing for Discrimination Prevention. NIPS (2017)
Caitlin Kuhlman, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Aurelie C. Lozano, Lei Cao, C. Reddy, Aleksandra Mojsilovic, Kush R. Varshney
How to foster innovation: A data-driven approach to measuring economic competitiveness. IBM J. Res. Dev. 61 (6) (2017)
Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan
Learning Robust Representations for Computer Vision. CoRR (2017)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Distribution-Preserving k-Anonymity. CoRR (2017)
Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. CoRR (2017)
Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Berkay Kanberoglu, David H. Frakes, Kevin Bennett, Andreas Spanias
Measuring glomerular number from kidney MRI images. Medical Imaging: Image Processing (2016)
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias
A Deep Learning Approach To Multiple Kernel Fusion. CoRR (2016)
Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan
Beyond L2-loss functions for learning sparse models. ICASSP (2016)
Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga
Persistent homology of attractors for action recognition. ICIP (2016)
Huan Song, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
Auto-context modeling using multiple Kernel learning. ICIP (2016)
Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura
Robust Local Scaling Using Conditional Quantiles of Graph Similarities. ICDM Workshops (2016)

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Publication Activity (10 Years)

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Karthikeyan Natesan Ramamurthy