Prasanna Sattigeri

According to our database, Prasanna Sattigeri authored at least 111 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Separability Analysis for Causal Discovery in Mixture of DAGs.

Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer

Trans. Mach. Learn. Res., 2024

Graph-based Uncertainty Metrics for Long-form Language Model Outputs.

Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori Hashimoto

CoRR, 2024

Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI.

Ambrish Rawat, Stefan Schoepf, Giulio Zizzo, Giandomenico Cornacchia, Muhammad Zaid Hameed, Kieran Fraser, Erik Miehling, Beat Buesser, Elizabeth M. Daly, Mark Purcell, Prasanna Sattigeri, Pin-Yu Chen, Kush R. Varshney

CoRR, 2024

When in Doubt, Cascade: Towards Building Efficient and Capable Guardrails.

Manish Nagireddy, Inkit Padhi, Soumya Ghosh, Prasanna Sattigeri

CoRR, 2024

WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia.

Yufang Hou, Alessandra Pascale, Javier Carnerero-Cano, Tigran T. Tchrakian, Radu Marinescu, Elizabeth Daly, Inkit Padhi, Prasanna Sattigeri

CoRR, 2024

Interventional Causal Discovery in a Mixture of DAGs.

Burak Varici, Dmitriy A. Katz-Rogozhnikov, Dennis Wei, Prasanna Sattigeri, Ali Tajer

CoRR, 2024

Large Language Model Confidence Estimation via Black-Box Access.

Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri

CoRR, 2024

Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions.

Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer

CoRR, 2024

The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers.

Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag

CoRR, 2024

Multi-Level Explanations for Generative Language Models.

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

CoRR, 2024

Contextual Moral Value Alignment Through Context-Based Aggregation.

Pierre L. Dognin, Jesus Rios, Ronny Luss, Inkit Padhi, Matthew D. Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf

CoRR, 2024

Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.

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

CoRR, 2024

Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations.

Swapnaja Achintalwar, Adriana Alvarado Garcia, Ateret Anaby-Tavor, Ioana Baldini, Sara E. Berger, Bishwaranjan Bhattacharjee, Djallel Bouneffouf, Subhajit Chaudhury, Pin-Yu Chen, Lamogha Chiazor, Elizabeth M. Daly, Rogério Abreu de Paula, Pierre L. Dognin, Eitan Farchi, Soumya Ghosh, Michael Hind, Raya Horesh, George Kour, Ja Young Lee, Erik Miehling, Keerthiram Murugesan, Manish Nagireddy, Inkit Padhi, David Piorkowski, Ambrish Rawat, Orna Raz, Prasanna Sattigeri, Hendrik Strobelt, Sarathkrishna Swaminathan, Christoph Tillmann, Aashka Trivedi, Kush R. Varshney, Dennis Wei, Shalisha Witherspoon, Marcel Zalmanovici

CoRR, 2024

Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions.

Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell

CoRR, 2024

Group Fairness with Uncertain Sensitive Attributes.

Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell

Proceedings of the IEEE International Symposium on Information Theory, 2024

ComVas: Contextual Moral Values Alignment System.

Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Thermometer: Towards Universal Calibration for Large Language Models.

Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Value Alignment from Unstructured Text.

Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

Language Models in Dialogue: Conversational Maxims for Human-AI Interactions.

Erik Miehling, Manish Nagireddy, Prasanna Sattigeri, Elizabeth Daly, David Piorkowski, John T. Richards

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Causal Bandits with General Causal Models and Interventions.

Zirui Yan, Dennis Wei, Dmitriy A. Katz, Prasanna Sattigeri, Ali Tajer

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

The incentive gap in data work in the era of large models.

Katy Ilonka Gero, Payel Das, Pierre L. Dognin, Inkit Padhi, Prasanna Sattigeri, Kush R. Varshney

Nat. Mac. Intell., June, 2023

Causal Bandits for Linear Structural Equation Models.

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

J. Mach. Learn. Res., 2023

Assessment of Prediction Intervals Using Uncertainty Characteristics Curves.

Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri

CoRR, 2023

Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling.

Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick

CoRR, 2023

Equivariant Few-Shot Learning from Pretrained Models.

Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Rose Driggs-Campbell, Payel Das, Lav R. Varshney

CoRR, 2023

Group Fairness with Uncertainty in Sensitive Attributes.

Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell

CoRR, 2023

Effective Human-AI Teams via Learned Natural Language Rules and Onboarding.

Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Equivariant Transfer Learning from Pretrained Models.

Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs Campbell, Payel Das, Lav R. Varshney

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness.

Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Amit Dhurandhar, Juan E. Gilbert

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Reliable Gradient-free and Likelihood-free Prompt Tuning.

Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Who Should Predict? Exact Algorithms For Learning to Defer to Humans.

Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model.

Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models.

Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors.

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

Int. J. Virtual Pers. Learn. Environ., 2022

A Maximal Correlation Framework for Fair Machine Learning.

Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Schmidt Feris

Entropy, 2022

Generating physically-consistent high-resolution climate data with hard-constrained neural networks.

Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri, Alex Hernández-García, Campbell D. Watson, Daniela Szwarcman, David S. Rolnick

CoRR, 2022

Causal Graphs Underlying Generative Models: Path to Learning with Limited Data.

Samuel C. Hoffman, Kahini Wadhawan, Payel Das, Prasanna Sattigeri, Karthikeyan Shanmugam

CoRR, 2022

Intervention target estimation in the presence of latent variables.

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Causal Feature Selection for Algorithmic Fairness.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting.

Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Selective Regression under Fairness Criteria.

Abhin Shah, Yuheng Bu, Joshua K. Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell

Proceedings of the International Conference on Machine Learning, 2022

A Maximal Correlation Approach to Imposing Fairness in Machine Learning.

Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Feris

Proceedings of the IEEE International Conference on Acoustics, 2022

Uncertainty Quantification 360: A Hands-on Tutorial.

Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang

Proceedings of the CODS-COMAD 2022: 5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD), Bangalore, India, January 8, 2022

AI Explainability 360: Impact and Design.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Interventional Fairness with Indirect Knowledge of Unobserved Protected Attributes.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

Entropy, 2021

Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI.

Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang

CoRR, 2021

Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals.

Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri

CoRR, 2021

Conditionally independent data generation.

Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Scalable Intervention Target Estimation in Linear Models.

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Leveraging Latent Features for Local Explanations.

Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Fair Selective Classification Via Sufficiency.

Joshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell

Proceedings of the 38th International Conference on Machine Learning, 2021

AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition.

Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogério Feris

Proceedings of the 9th International Conference on Learning Representations, 2021

Detector-Free Weakly Supervised Grounding by Separation.

Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

AI Explainability 360 Toolkit.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

Umang Bhatt, Javier Antorán, Yunfeng Zhang, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Madhulika Srikumar, Adrian Weller, Alice Xiang

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

StarNet: towards Weakly Supervised Few-Shot Object Detection.

Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Feris, Alex M. Bronstein, Raja Giryes

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

J. Mach. Learn. Res., 2020

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

Umang Bhatt, Yunfeng Zhang, Javier Antorán, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Adrian Weller, Alice Xiang

CoRR, 2020

Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling.

Akash Srivastava, Yamini Bansal, Yukun Ding, Cole L. Hurwitz, Kai Xu, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund

CoRR, 2020

not-so-BigGAN: Generating High-Fidelity Images on a Small Compute Budget.

Seungwook Han, Akash Srivastava, Cole L. Hurwitz, Prasanna Sattigeri, David D. Cox

CoRR, 2020

Fair Data Integration.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

CoRR, 2020

Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models.

Jayaraman J. Thiagarajan, Prasanna Sattigeri, Deepta Rajan, Bindya Venkatesh

CoRR, 2020

StarNet: towards weakly supervised few-shot detection and explainable few-shot classification.

Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Schmidt Feris, Alexander M. Bronstein, Raja Giryes

CoRR, 2020

Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration.

Bindya Venkatesh, Jayaraman J. Thiagarajan, Kowshik Thopalli, Prasanna Sattigeri

CoRR, 2020

Optimizing Mode Connectivity via Neuron Alignment.

N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improving Reliability of Clinical Models Using Prediction Calibration.

Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 2020

Fairness of Classifiers Across Skin Tones in Dermatology.

Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

AI explainability 360: hands-on tutorial.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Proceedings of the FAT* '20: Conference on Fairness, 2020

AR-Net: Adaptive Frame Resolution for Efficient Action Recognition.

Yue Meng, Chung-Ching Lin, Rameswar Panda, Prasanna Sattigeri, Leonid Karlinsky, Aude Oliva, Kate Saenko, Rogério Feris

Proceedings of the Computer Vision - ECCV 2020, 2020

TAFSSL: Task-Adaptive Feature Sub-Space Learning for Few-Shot Classification.

Moshe Lichtenstein, Prasanna Sattigeri, Rogério Feris, Raja Giryes, Leonid Karlinsky

Proceedings of the Computer Vision - ECCV 2020, 2020

OnlineAugment: Online Data Augmentation with Less Domain Knowledge.

Zhiqiang Tang, Yunhe Gao, Leonid Karlinsky, Prasanna Sattigeri, Rogério Feris, Dimitris N. Metaxas

Proceedings of the Computer Vision - ECCV 2020, 2020

Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions.

Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Bhavya Kailkhura

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors.

Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications.

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

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Think Your Artificial Intelligence Software Is Fair? Think Again.

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

IEEE Softw., 2019

Fairness GAN: Generating datasets with fairness properties using a generative adversarial network.

Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney

IBM J. Res. Dev., 2019

AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias.

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

IBM J. Res. Dev., 2019

Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies.

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

CoRR, 2019

Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets.

Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney

CoRR, 2019

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

CoRR, 2019

Generating Contrastive Explanations with Monotonic Attribute Functions.

Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Karthikeyan Shanmugam, Chun-Chen Tu

CoRR, 2019

Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks.

Joshua K. Lee, Prasanna Sattigeri, Gregory W. Wornell

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Optimizing Kernel Machines Using Deep Learning.

Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias

IEEE Trans. Neural Networks Learn. Syst., 2018

Understanding Unequal Gender Classification Accuracy from Face Images.

Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney

CoRR, 2018

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias.

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

CoRR, 2018

Can Deep Clinical Models Handle Real-World Domain Shifts?

Jayaraman J. Thiagarajan, Deepta Rajan, Prasanna Sattigeri

CoRR, 2018

Fairness GAN.

Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney

CoRR, 2018

Co-regularized Alignment for Unsupervised Domain Adaptation.

Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogério Schmidt Feris, Bill Freeman, Gregory W. Wornell

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Variational Inference of Disentangled Latent Concepts from Unlabeled Observations.

Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan

Proceedings of the 6th International Conference on Learning Representations, 2018

Data Driven Techniques for Organizing Scientific Articles Relevant to Biomimicry.

Yuanshuo Zhao, Ioana Baldini, Prasanna Sattigeri, Inkit Padhi, Yoong Keok Lee, Ethan Smith

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017

Real-time understanding of humanitarian crises via targeted information retrieval.

Kien Pham, Prasanna Sattigeri, Amit Dhurandhar, A. C. Jacob, M. Vukovic, P. Chataigner, Juliana Freire, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

How to foster innovation: A data-driven approach to measuring economic competitiveness.

Caitlin Kuhlman, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Aurélie C. Lozano, Lei Cao, C. Reddy, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

Improved Semi-supervised Learning with GANs using Manifold Invariances.

Abhishek Kumar, Prasanna Sattigeri, P. Thomas Fletcher

CoRR, 2017

Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference.

Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A deep learning approach to multiple kernel fusion.

Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning.

Jayaraman J. Thiagarajan, Bhavya Kailkhura, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy

CoRR, 2016

Understanding Innovation to Drive Sustainable Development.

Prasanna Sattigeri, Aurélie C. Lozano, Aleksandra Mojsilovic, Kush R. Varshney, Mahmoud Naghshineh

CoRR, 2016

Sparsifying Word Representations for Deep Unordered Sentence Modeling.

Prasanna Sattigeri, Jayaraman J. Thiagarajan

Proceedings of the 1st Workshop on Representation Learning for NLP, 2016

Robust Local Scaling Using Conditional Quantiles of Graph Similarities.

Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Stable estimation of Granger-causal factors of country-level innovation.

Aurélie C. Lozano, Prasanna Sattigeri, Aleksandra Mojsilovic, Kush R. Varshney

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2014

Exploring Latent Structure in Data: Algorithms and Implementations.

Prasanna Sattigeri

PhD thesis, 2014

Automatic image annotation using inverse maps from semantic embeddings.

Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Peer-Timo Bremer, Andreas Spanias

Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

A scalable feature learning and tag prediction framework for natural environment sounds.

Prasanna Sattigeri, Jayaraman J. Thiagarajan, Mohit Shah, Karthikeyan Natesan Ramamurthy, Andreas Spanias

Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013

Ensemble Sparse Models for Image Analysis

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias

CoRR, 2013

Boosted dictionaries for image restoration based on sparse representations.

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias, Prasanna Sattigeri

Proceedings of the IEEE International Conference on Acoustics, 2013

2012

Supervised local sparse coding of sub-image features for image retrieval.

Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Andreas Spanias

Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Implementation of a fast image coding and retrieval system using a GPU.

Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias

Proceedings of the 2012 IEEE International Conference on Emerging Signal Processing Applications, 2012

Learning dictionaries with graph embedding constraints.

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias

Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012

2011

Transform domain features for ion-channel signal classification.

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Michael Goryll, Andreas Spanias, Trevor Thornton, Stephen M. Phillips

Biomed. Signal Process. Control., 2011

Analyte detection using an ion-channel sensor array.

Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Michael Goryll, Andreas Spanias, Trevor Thornton

Proceedings of the 17th International Conference on Digital Signal Processing, 2011

2009

Acquiring and Classifying Signals from Nanopores and Ion-Channels.

Bharatan Konnanath, Prasanna Sattigeri, Trupthi Mathew, Andreas Spanias, Shalini Prasad, Michael Goryll, Trevor Thornton, Peter Knee

Proceedings of the Artificial Neural Networks, 2009