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ORCIDKarthikeyan Natesan Ramamurthy
Karthikeyan Ramamurthy
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2020 – today
- 2025
[j22]Sanjay Gopi, S. Madesh, Karthikeyan Ramamurthy, Mikhlid H. Almutairi, Bader O. Almutairi, S. Karthick Raja Namasivayam
, Jesu Arockiaraj:
Black seed (Nigella sativa) extract enhances early and late apoptosis through activation of caspase-3 mediated regulatory pathway in LC540 cells: A network pharmacological and molecular docking approach. Comput. Biol. Chem. 118: 108455 (2025)- [c86]Bruce W. Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre L. Dognin, Manish Nagireddy, Amit Dhurandhar:
Programming Refusal with Conditional Activation Steering. ICLR 2025 - [c85]Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Kush R. Varshney, Eitan Farchi, Pierre Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu, Prasanna Sattigeri:
Evaluating the Prompt Steerability of Large Language Models. NAACL (Long Papers) 2025: 7874-7900 - [i68]Jesus Rios, Pierre L. Dognin, Ronny Luss, Karthikeyan Ramamurthy:
Sparsity May Be All You Need: Sparse Random Parameter Adaptation. CoRR abs/2502.15975 (2025) - [i67]Ivoline Ngong, Swanand Kadhe, Hao Wang, Keerthiram Murugesan, Justin D. Weisz, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy:
Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents. CoRR abs/2502.18509 (2025) - [i66]Erik Miehling, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Matthew Riemer, Djallel Bouneffouf, John T. Richards, Amit Dhurandhar, Elizabeth M. Daly, Michael Hind, Prasanna Sattigeri, Dennis Wei, Ambrish Rawat, Jasmina Gajcin, Werner Geyer:
Agentic AI Needs a Systems Theory. CoRR abs/2503.00237 (2025) - [i65]Danielle Villa, Maria D. Chang, Keerthiram Murugesan, Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy:
Cross-Examiner: Evaluating Consistency of Large Language Model-Generated Explanations. CoRR abs/2503.08815 (2025) - 2024
- [j21]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. IEEE Internet Comput. 28(5): 28-36 (2024) - [j20]Weizhi Li, Prad Kadambi, Pouria Saidi, Karthikeyan Natesan Ramamurthy, Gautam Dasarathy, Visar Berisha:
Active Sequential Two-Sample Testing. Trans. Mach. Learn. Res. 2024 (2024) - [c84]Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy:
Ranking Large Language Models without Ground Truth. ACL (Findings) 2024: 2431-2452 - [c83]Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney:
Value Alignment from Unstructured Text. EMNLP (Industry Track) 2024: 1083-1095 - [c82]Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy:
Trust Regions for Explanations via Black-Box Probabilistic Certification. ICML 2024 - [c81]Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, 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: Topological Deep Learning is the New Frontier for Relational Learning. ICML 2024 - [i64]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 abs/2402.02441 (2024) - [i63]Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. 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 abs/2402.08871 (2024) - [i62]Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy:
Trust Regions for Explanations via Black-Box Probabilistic Certification. CoRR abs/2402.11168 (2024) - [i61]Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy:
Ranking Large Language Models without Ground Truth. CoRR abs/2402.14860 (2024) - [i60]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 abs/2403.09704 (2024) - [i59]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 abs/2403.14459 (2024) - [i58]Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy, Maria Chang, Moninder Singh:
Reasoning about concepts with LLMs: Inconsistencies abound. CoRR abs/2405.20163 (2024) - [i57]Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney:
Value Alignment from Unstructured Text. CoRR abs/2408.10392 (2024) - [i56]Bruce W. Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre L. Dognin, Manish Nagireddy, Amit Dhurandhar:
Programming Refusal with Conditional Activation Steering. CoRR abs/2409.05907 (2024) - [i55]Tian Gao, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Dennis Wei:
Identifying Sub-networks in Neural Networks via Functionally Similar Representations. CoRR abs/2410.16484 (2024) - [i54]Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Pierre L. Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu:
Evaluating the Prompt Steerability of Large Language Models. CoRR abs/2411.12405 (2024) - [i53]Dennis Wei, Inkit Padhi, Soumya Ghosh, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Maria Chang:
Final-Model-Only Data Attribution with a Unifying View of Gradient-Based Methods. CoRR abs/2412.03906 (2024) - 2023
- [c80]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: 6788-6796 - [c79]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: 221-235 - [c78]Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Amit Dhurandhar, Juan E. Gilbert:
Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness. FAccT 2023: 736-752 - [c77]Karthikeyan Natesan Ramamurthy, Aldo Guzmán-Sáenz, Mustafa Hajij:
TOPO-MLP : A Simplicial Network without Message Passing. ICASSP 2023: 1-5 - [c76]Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Kartik Ahuja, Vijay Arya:
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning. NeurIPS 2023 - [c75]Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy:
The Impact of Positional Encoding on Length Generalization in Transformers. NeurIPS 2023 - [c74]Erik Miehling, Rahul Nair, Elizabeth Daly, Karthikeyan Natesan Ramamurthy, Robert Redmond:
Cookie Consent Has Disparate Impact on Estimation Accuracy. NeurIPS 2023 - [c73]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: 3-8 - [i52]Weizhi Li, Karthikeyan Natesan Ramamurthy, Prad Kadambi, Pouria Saidi, Gautam Dasarathy, Visar Berisha:
Active Sequential Two-Sample Testing. CoRR abs/2301.12616 (2023) - [i51]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 abs/2302.09190 (2023) - [i50]Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy:
The Impact of Positional Encoding on Length Generalization in Transformers. CoRR abs/2305.19466 (2023) - [i49]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 Meissner, 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 abs/2309.15188 (2023) - [i48]Karthikeyan Natesan Ramamurthy, Aldo Guzmán-Sáenz, Mustafa Hajij:
Topo-MLP : A Simplicial Network Without Message Passing. CoRR abs/2312.11862 (2023) - 2022
- [j19]Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Ramamurthy, Andreas Spanias, Mahesh K. Banavar, Abhinav Dixit, Jie Fan, Mohit Malu, Kristen Jaskie, Sunil Rao, Uday Shankar Shanthamallu, Vivek Sivaraman Narayanaswamy, Sameeksha Katoch:
Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors. Int. J. Virtual Pers. Learn. Environ. 12(1): 1-17 (2022) - [c72]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: 2245-2262 - [c71]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: 333-335 - [c70]Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das:
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. ICASSP 2022: 3783-3787 - [c69]Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam:
Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations. NeurIPS 2022 - [c68]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
A label efficient two-sample test. UAI 2022: 1168-1177 - [i47]Amit Dhurandhar, Karthikeyan Ramamurthy, Kartik Ahuja, Vijay Arya:
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning. CoRR abs/2201.12143 (2022) - [i46]Karthikeyan Natesan Ramamurthy, Amit Dhurandhar, Dennis Wei, Zaid Bin Tariq:
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners. CoRR abs/2202.01153 (2022) - [i45]Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, Nina Miolane, Aldo Guzmán-Sáenz, Karthikeyan Natesan Ramamurthy:
Higher-Order Attention Networks. CoRR abs/2206.00606 (2022) - [i44]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 abs/2210.06475 (2022) - 2021
- [j18]Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio P. Calmon:
Optimized Score Transformation for Consistent Fair Classification. J. Mach. Learn. Res. 22: 258:1-258:78 (2021) - [j17]Peng Zheng, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin:
Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. Open J. Math. Optim. 2: 1-18 (2021) - [c67]Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu:
Conditionally independent data generation. UAI 2021: 2050-2060 - [i43]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 abs/2106.01410 (2021) - [i42]Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das:
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. CoRR abs/2106.04464 (2021) - [i41]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 abs/2108.01250 (2021) - [i40]Mustafa Hajij, Ghada Zamzmi, Karthikeyan Natesan Ramamurthy, Aldo Guzmán-Sáenz:
Data-Centric AI Requires Rethinking Data Notion. CoRR abs/2110.02491 (2021) - [i39]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
A label efficient two-sample test. CoRR abs/2111.08861 (2021) - [i38]Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh:
Ground-Truth, Whose Truth? - Examining the Challenges with Annotating Toxic Text Datasets. CoRR abs/2112.03529 (2021) - 2020
- [c66]Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy:
Crowd Counting with Decomposed Uncertainty. AAAI 2020: 11799-11806 - [c65]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: 13369-13381 - [c64]Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Bhavya Kailkhura:
Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions. ACSSC 2020: 284-288 - [c63]Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio P. Calmon:
Optimized Score Transformation for Fair Classification. AISTATS 2020: 1673-1683 - [c62]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: 3639-3648 - [c61]Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin:
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. ICLR 2020 - [c60]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: 2711-2716 - [c59]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
Finding the Homology of Decision Boundaries with Active Learning. NeurIPS 2020 - [c58]Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar:
Model Agnostic Multilevel Explanations. NeurIPS 2020 - [i37]Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar:
Model Agnostic Multilevel Explanations. CoRR abs/2003.06005 (2020) - [i36]Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin:
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. CoRR abs/2005.00060 (2020) - [i35]Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das:
Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. CoRR abs/2010.08548 (2020) - [i34]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
Finding the Homology of Decision Boundaries with Active Learning. CoRR abs/2011.09645 (2020)
2010 – 2019
- 2019
- [j16]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: 27 (2019) - [j15]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): 4:1-4:15 (2019) - [j14]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): 6:1-6:13 (2019) - [j13]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): 76-80 (2019) - [c57]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: 91-98 - [c56]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: 123-129 - [c55]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: 2847-2851 - [c54]Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody:
Topological Data Analysis of Decision Boundaries with Application to Model Selection. ICML 2019: 5351-5360 - [i33]Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy:
Crowd Counting with Decomposed Uncertainty. CoRR abs/1903.07427 (2019) - [i32]Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy:
Counting and Segmenting Sorghum Heads. CoRR abs/1905.13291 (2019) - [i31]Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon:
Optimized Score Transformation for Fair Classification. CoRR abs/1906.00066 (2019) - [i30]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 abs/1906.01769 (2019) - [i29]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 abs/1906.02299 (2019) - [i28]Moninder Singh, Karthikeyan Natesan Ramamurthy:
Understanding racial bias in health using the Medical Expenditure Panel Survey data. CoRR abs/1911.01509 (2019) - [i27]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 abs/1911.07819 (2019) - 2018
- [j12]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): 241-251 (2018) - [j11]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): 1106-1119 (2018) - [j10]Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Distribution-preserving k-anonymity. Stat. Anal. Data Min. 11(6): 253-270 (2018) - [c53]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: 400-409 - [c52]Anirudh Som, Kowshik Thopalli, Karthikeyan Natesan Ramamurthy, Vinay Venkataraman, Ankita Shukla, Pavan K. Turaga:
Perturbation Robust Representations of Topological Persistence Diagrams. ECCV (7) 2018: 638-659 - [i26]Ming Yu, Karthikeyan Natesan Ramamurthy, Addie M. Thompson, Aurélie C. Lozano:
Simultaneous Parameter Learning and Bi-Clustering for Multi-Response Models. CoRR abs/1804.10961 (2018) - [i25]Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody:
Topological Data Analysis of Decision Boundaries with Application to Model Selection. CoRR abs/1805.09949 (2018) - [i24]Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic:
Teaching Meaningful Explanations. CoRR abs/1805.11648 (2018) - [i23]Anirudh Som, Kowshik Thopalli, Karthikeyan Natesan Ramamurthy, Vinay Venkataraman, Ankita Shukla, Pavan K. Turaga:
Perturbation Robust Representations of Topological Persistence Diagrams. CoRR abs/1807.10400 (2018) - [i22]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 abs/1808.07261 (2018) - [i21]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 abs/1810.01943 (2018) - [i20]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 abs/1811.04896 (2018) - [i19]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 abs/1812.06135 (2018) - 2017
- [j9]Caitlin Kuhlman, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Aurélie 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): 11:1-11:12 (2017) - [c51]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: 1524-1533 - [c50]Moninder Singh, Karthikeyan Natesan Ramamurthy, Shrihari Vasudevan:
Propensity modeling for employee Re-skilling. GlobalSIP 2017: 893-897 - [c49]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: 938-942 - [c48]Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
A deep learning approach to multiple kernel fusion. ICASSP 2017: 2292-2296 - [c47]Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy:
Learning Robust Representations for Computer Vision. ICCV Workshops 2017: 1784-1791 - [c46]Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier:
Distributed Bundle Adjustment. ICCV Workshops 2017: 2146-2154 - [c45]Flávio P. Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Optimized Pre-Processing for Discrimination Prevention. NIPS 2017: 3992-4001 - [i18]Flávio du Pin Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Optimized Data Pre-Processing for Discrimination Prevention. CoRR abs/1704.03354 (2017) - [i17]Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan:
Learning Robust Representations for Computer Vision. CoRR abs/1708.00069 (2017) - [i16]Karthikeyan Natesan Ramamurthy, Chung-Ching Lin, Aleksandr Y. Aravkin, Sharath Pankanti, Raphael Viguier:
Distributed Bundle Adjustment. CoRR abs/1708.07954 (2017) - [i15]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 abs/1710.06876 (2017) - [i14]Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Distribution-Preserving k-Anonymity. CoRR abs/1711.01514 (2017) - [i13]Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer:
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. CoRR abs/1712.07106 (2017) - 2016
- [c44]Rushil Anirudh, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga:
A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams. CVPR Workshops 2016: 1023-1031 - [c43]Huan Song, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias, Pavan K. Turaga:
Consensus inference on mobile phone sensors for activity recognition. ICASSP 2016: 2294-2298 - [c42]Alan Wisler, Visar Berisha, Dennis Wei, Karthikeyan Ramamurthy, Andreas Spanias:
Empirically-estimable multi-class classification bounds. ICASSP 2016: 2594-2598 - [c41]Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan:
Beyond L2-loss functions for learning sparse models. ICASSP 2016: 4692-4696 - [c40]Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura:
Robust Local Scaling Using Conditional Quantiles of Graph Similarities. ICDM Workshops 2016: 762-769 - [c39]Huan Song, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Auto-context modeling using multiple Kernel learning. ICIP 2016: 1868-1872 - [c38]Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga:
Persistent homology of attractors for action recognition. ICIP 2016: 4150-4154 - [c37]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Berkay Kanberoglu, David H. Frakes, Kevin Bennett, Andreas Spanias:
Measuring glomerular number from kidney MRI images. Image Processing 2016: 978412 - [i12]Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga:
Persistent Homology of Attractors For Action Recognition. CoRR abs/1603.05310 (2016) - [i11]Rushil Anirudh, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga:
A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams. CoRR abs/1605.08912 (2016) - [i10]Jayaraman J. Thiagarajan, Bhavya Kailkhura, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy:
TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning. CoRR abs/1611.07429 (2016) - [i9]Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
A Deep Learning Approach To Multiple Kernel Fusion. CoRR abs/1612.09007 (2016) - 2015
- [j8]Kush R. Varshney, Dennis Wei, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic:
Data Challenges in Disease Response: The 2014 Ebola Outbreak and Beyond. ACM J. Data Inf. Qual. 6(2-3): 5:1-5:3 (2015) - [j7]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Learning Stable Multilevel Dictionaries for Sparse Representations. IEEE Trans. Neural Networks Learn. Syst. 26(9): 1913-1926 (2015) - [c36]Chung-Ching Lin, Sharathchandra Pankanti, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin:
Adaptive as-natural-as-possible image stitching. CVPR 2015: 1155-1163 - [c35]Karthikeyan Natesan Ramamurthy, Moninder Singh, Yichong Yu, Jessica Aspis, Matthew Iames, Michael Peran, Qin S. Held:
A talent management tool using propensity to leave analytics. DSAA 2015: 1-10 - [c34]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy:
Subspace learning using consensus on the grassmannian manifold. ICASSP 2015: 2031-2035 - [c33]Alan Wisler, Visar Berisha, Karthikeyan Ramamurthy, Andreas Spanias, Julie Liss:
Removing data with noisy responses in regression analysis. ICASSP 2015: 2066-2070 - [c32]Kush R. Varshney, Karthikeyan Natesan Ramamurthy:
Persistent topology of decision boundaries. ICASSP 2015: 3931-3935 - [c31]Dmitriy A. Katz-Rogozhnikov, Dennis Wei, Gigi Y. Yuen-Reed, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic:
Toward Comprehensive Attribution of Healthcare Cost Changes. ICDM Workshops 2015: 146-155 - [c30]Karthikeyan Natesan Ramamurthy, Moninder Singh, Michael Davis, J. Alex Kevern, Uri Klein, Michael Peran:
Identifying Employees for Re-skilling Using an Analytics-Based Approach. ICDM Workshops 2015: 345-354 - [c29]Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity. SDM 2015: 226-234 - [i8]Suhas Ranganath, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Mahesh K. Banavar, Andreas Spanias:
Undergraduate Signal Processing Laboratories for the Android Operating System. CoRR abs/1502.07026 (2015) - [i7]Stephen Becker, Ban Kawas, Marek Petrik, Karthikeyan Natesan Ramamurthy:
Robust Partially-Compressed Least-Squares. CoRR abs/1510.04905 (2015) - 2014
- [b3]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga, Andreas Spanias:
Image Understanding Using Sparse Representations. Synthesis Lectures on Image, Video, and Multimedia Processing, Morgan & Claypool Publishers 2014, ISBN 978-3-031-01122-1 - [j6]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias:
Recovering non-negative and combined sparse representations. Digit. Signal Process. 26: 21-35 (2014) - [j5]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Andreas Spanias, Anup Puri, David H. Frakes:
Kernel Sparse Models for Automated Tumor Segmentation. Int. J. Artif. Intell. Tools 23(3) (2014) - [j4]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning. IEEE Trans. Image Process. 23(7): 2905-2915 (2014) - [c28]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Rahul Sridhar, Premnishanth Kothandaraman, Ramanathan Nachiappan:
Consensus inference with multilayer graphs for multi-modal data. ACSSC 2014: 1341-1345 - [c27]Prasanna Sattigeri, Jayaraman J. Thiagarajan, Mohit Shah, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
A scalable feature learning and tag prediction framework for natural environment sounds. ACSSC 2014: 1779-1783 - [c26]Jayaraman J. Thiagarajan, Peer-Timo Bremer, Karthikeyan Natesan Ramamurthy:
Multiple kernel interpolation for inverting non-linear dimensionality reduction and dimension estimation. ICASSP 2014: 6751-6755 - [c25]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Peer-Timo Bremer, Andreas Spanias:
Automatic image annotation using inverse maps from semantic embeddings. ICIP 2014: 3107-3111 - [c24]Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Gianluigi Pillonetto:
Kalman smoothing with persistent nuisance parameters. MLSP 2014: 1-6 - [c23]Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Jayaraman J. Thiagarajan:
Computing persistent homology under random projection. SSP 2014: 105-108 - [c22]Dennis Wei, Karthikeyan Natesan Ramamurthy, Dmitriy A. Katz-Rogozhnikov, Aleksandra Mojsilovic:
Multiplicative regression via constrained least squares. SSP 2014: 304-307 - [i6]Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan:
Beyond L2-Loss Functions for Learning Sparse Models. CoRR abs/1403.6706 (2014) - 2013
- [b2]Karthikeyan Natesan Ramamurthy:
New Directions in Sparse Models for Image Analysis and Restoration. Arizona State University, Tempe, USA, 2013 - [j3]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Mixing matrix estimation using discriminative clustering for blind source separation. Digit. Signal Process. 23(1): 9-18 (2013) - [c21]Linda Hinnov, Karthikeyan Natesan Ramamurthy, Huan Song, Mahesh K. Banavar, Louis Spanias:
Interactive tools for global sustainability and Earth systems: Sea level change and temperature. FIE 2013: 1965-1970 - [c20]Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Moninder Singh:
Quantile regression for workforce analytics. GlobalSIP 2013: 1134 - [c19]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias, Prasanna Sattigeri:
Boosted dictionaries for image restoration based on sparse representations. ICASSP 2013: 1583-1587 - [c18]Rushil Anirudh, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Pavan K. Turaga, Andreas Spanias:
A heterogeneous dictionary model for representation and recognition of human actions. ICASSP 2013: 3472-3476 - [c17]DongPing Fang, Kush R. Varshney, Jun Wang, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic, John H. Bauer:
Quantifying and Recommending Expertise When New Skills Emerge. ICDM Workshops 2013: 672-679 - [i5]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias:
Ensemble Sparse Models for Image Analysis. CoRR abs/1302.6957 (2013) - [i4]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Learning Stable Multilevel Dictionaries for Sparse Representation of Images. CoRR abs/1303.0448 (2013) - [i3]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning. CoRR abs/1303.0582 (2013) - [i2]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Anup Puri, David H. Frakes, Andreas Spanias:
Kernel Sparse Models for Automated Tumor Segmentation. CoRR abs/1303.2610 (2013) - [i1]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias:
Recovering Non-negative and Combined Sparse Representations. CoRR abs/1303.4694 (2013) - 2012
- [c16]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias:
Learning dictionaries with graph embedding constraints. ACSCC 2012: 1974-1978 - [c15]Jayaraman J. Thiagarajan, Deepta Rajan, Karthikeyan Natesan Ramamurthy, David H. Frakes, Andreas Spanias:
Automated tumor segmentation using kernel sparse representations. BIBE 2012: 401-406 - [c14]Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Implementation of a fast image coding and retrieval system using a GPU. ESPA 2012: 5-8 - [c13]Linda Hinnov, Andreas Spanias, Karthikeyan Natesan Ramamurthy, Girish Kalyanasundaram:
Workshop: Interactive education tools for earth systems and sustainability applications. FIE 2012: 1-2 - [c12]Suhas Ranganath, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Mahesh K. Banavar, Andreas Spanias:
Work in progress: Performing signal analysis laboratories using Android devices. FIE 2012: 1-2 - [c11]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Andreas Spanias:
Supervised local sparse coding of sub-image features for image retrieval. ICIP 2012: 3117-3120 - [c10]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias, Panos Nasiopoulos:
Learning Multilevel Dictionaries for Compressed Sensing Using Discriminative Clustering. IIH-MSP 2012: 494-497 - 2011
- [j2]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Michael Goryll, Andreas Spanias, Trevor Thornton, Stephen M. Phillips:
Transform domain features for ion-channel signal classification. Biomed. Signal Process. Control. 6(3): 219-224 (2011) - [j1]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Optimality and stability of the K-hyperline clustering algorithm. Pattern Recognit. Lett. 32(9): 1299-1304 (2011) - [c9]Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Optimized measurements for kernel compressive sensing. ACSCC 2011: 1443-1446 - [c8]Jinru Liu, Andreas Spanias, Mahesh K. Banavar, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Xue Zhang:
Work in progress - Interactive signal-processing labs and simulations on iOS devices. FIE 2011: 2 - [c7]Linda Hinnov, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Work in progress: The J-DSP/ESE software for analyzing Earth systems signals. FIE 2011: 3 - [c6]Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Michael Goryll, Andreas Spanias, Trevor Thornton:
Analyte detection using an ion-channel sensor array. DSP 2011: 1-6 - [c5]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias:
Improved sparse coding using manifold projections. ICIP 2011: 1237-1240 - 2010
- [b1]Karthikeyan Natesan Ramamurthy, Andreas Spanias:
MATLAB Software for the Code Excited Linear Prediction Algorithm: The Federal Standard-1016. Synthesis Lectures on Algorithms and Software in Engineering, Morgan & Claypool Publishers 2010, ISBN 978-3-031-00386-8 - [c4]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Dimensionality Reduction for Distance Based Video Clustering. AIAI 2010: 270-277
2000 – 2009
- 2009
- [c3]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias:
Fast image registration with non-stationary Gauss-Markov random field templates. ICIP 2009: 185-188 - [c2]Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias:
Template Learning using Wavelet Domain Statistical Models. SGAI Conf. 2009: 179-192 - 2008
- [c1]Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias:
Sparse Representations for Pattern Classification using Learned Dictionaries. SGAI Conf. 2008: 33-45
Coauthor Index
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