Subhro Das

According to our database, Subhro Das authored at least 54 papers between 2013 and 2024.

Collaborative distances:

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

2024

Thermometer: Towards Universal Calibration for Large Language Models.

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

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

One Step Closer to Unbiased Aleatoric Uncertainty Estimation.

Wang Zhang, Ziwen Martin Ma, Subhro Das, Tsui-Wei Lily Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

A Model for Estimating the Economic Costs of Computer Vision Systems That Use Deep Learning.

Neil Thompson, Martin Fleming, Benny J. Tang, Anna M. Pastwa, Nicholas Borge, Brian C. Goehring, Subhro Das

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models.

Farzan Farnia, William W. Wang, Subhro Das, Ali Jadbabaie

SIAM J. Math. Data Sci., March, 2023

Correlated Attention in Transformers for Multivariate Time Series.

Quang Minh Nguyen, Lam M. Nguyen, Subhro Das

CoRR, 2023

Non-asymptotic System Identification for Linear Systems with Nonlinear Policies.

Yingying Li, Tianpeng Zhang, Subhro Das, Jeff S. Shamma, Na Li

CoRR, 2023

Variance-reduced Clipping for Non-convex Optimization.

Amirhossein Reisizadeh, Haochuan Li, Subhro Das, Ali Jadbabaie

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

ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction.

Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

Proceedings of the International Conference on Machine Learning, 2023

Label-free Concept Bottleneck Models.

Tuomas P. Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Attacking c-MARL More Effectively: A Data Driven Approach.

Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng

Proceedings of the IEEE International Conference on Data Mining, 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

2022

Evaluating Robustness of Cooperative MARL: A Model-based Approach.

Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng

CoRR, 2022

An Alternative Approach for Distributed Parameter Estimation Under Gaussian Settings.

Subhro Das

Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity.

Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie

Proceedings of the International Conference on Machine Learning, 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

On Convergence of Gradient Descent Ascent: A Tight Local Analysis.

Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie

Proceedings of the International Conference on Machine Learning, 2022

On observability and optimal gain design for distributed linear filtering and prediction.

Subhro Das

Proceedings of the 30th European Signal Processing Conference, 2022

Learning skills adjacency representations for optimized reskilling recommendations.

Saksham Gandhi, Raj Nagesh, Subhro Das

Proceedings of the IEEE International Conference on Big Data, 2022

Better Skill-based Job Representations, Assessed via Job Transition Data.

Tyler Baldwin, Wyatt Clarke, Maysa M. Garcia de Macedo, Rogério de Paula, Subhro Das

Proceedings of the IEEE International Conference on Big Data, 2022

Practical Skills Demand Forecasting via Representation Learning of Temporal Dynamics.

Maysa Malfiza Garcia de Macedo, Wyatt Clarke, Eli Lucherini, Tyler Baldwin, Dilermando Queiroz Neto, Rogério Abreu de Paula, Subhro Das

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

Safe Adaptive Learning-based Control for Constrained Linear Quadratic Regulators with Regret Guarantees.

Yingying Li, Subhro Das, Jeff S. Shamma, Na Li

CoRR, 2021

On Multisensor Activation Policies for Bernoulli Tracking.

Augustin-Alexandru Saucan, Subhro Das, Moe Z. Win

Proceedings of the 2021 IEEE Military Communications Conference, 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

Verifiably safe exploration for end-to-end reinforcement learning.

Nathan Hunt, Nathan Fulton, Sara Magliacane, Trong Nghia Hoang, Subhro Das, Armando Solar-Lezama

Proceedings of the HSCC '21: 24th ACM International Conference on Hybrid Systems: Computation and Control, 2021

IF: Iterative Fractional Optimization.

Sarthak Chatterjee, Subhro Das, Sérgio Pequito

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Online Optimal Control with Affine Constraints.

Yingying Li, Subhro Das, Na Li

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

2020

Verifiably Safe Exploration for End-to-End Reinforcement Learning.

Nathan Hunt, Nathan Fulton, Sara Magliacane, Nghia Hoang, Subhro Das, Armando Solar-Lezama

CoRR, 2020

A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm.

Orlando Romero, Subhro Das, Pin-Yu Chen, Sérgio Pequito

CoRR, 2020

GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models.

Farzan Farnia, William Wang, Subhro Das, Ali Jadbabaie

CoRR, 2020

Formal Verification of End-to-End Learning in Cyber-Physical Systems: Progress and Challenges.

Nathan Fulton, Nathan Hunt, Nghia Hoang, Subhro Das

CoRR, 2020

Stochastic Optimization with Non-stationary Noise.

Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie

CoRR, 2020

Model adaptation and unsupervised learning with non-stationary batch data under smooth concept drift.

Subhro Das, Prasanth Lade, Soundar Srinivasan

CoRR, 2020

Learning Interpretable Behavioral Engagement for Care Management.

Subhro Das, Chandramouli Maduri, Ching-Hua Chen, Pei-Yun Sabrina Hsueh

Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines.

Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Learning Occupational Task-Shares Dynamics for the Future of Work.

Subhro Das, Sebastian Steffen, Wyatt Clarke, Prabhat Reddy, Erik Brynjolfsson, Martin Fleming

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2019

An Adaptive, Data-Driven Personalized Advisor for Increasing Physical Activity.

Zhiguo Li, Subhro Das, James V. Codella, Tian Hao, Kun Lin, Chandramouli Maduri, Ching-Hua Chen

IEEE J. Biomed. Health Informatics, 2019

Learning Patient Engagement in Care Management: Performance vs. Interpretability.

Subhro Das, Chandramouli Maduri, Ching-Hua Chen, Pei-Yun Sabrina Hsueh

CoRR, 2019

2018

Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records.

Pei-Yun Sabrina Hsueh, Subhro Das, Chandramouli Maduri, Karie Kelly

Proceedings of the AMIA 2018, 2018

2017

Consensus+Innovations Distributed Kalman Filter With Optimized Gains.

Subhro Das, José M. F. Moura

IEEE Trans. Signal Process., 2017

Distributed Estimation of Dynamic Fields over Multi-agent Networks.

Subhro Das, José M. F. Moura

CoRR, 2017

Making Sense of Patient-Generated Health Data for Interpretable Patient-Centered Care: The Transition from "More" to "Better".

Pei-Yun Sabrina Hsueh, Sanjoy Dey, Subhro Das, Thomas Wetter

Proceedings of the MEDINFO 2017: Precision Healthcare through Informatics, 2017

A Personalized Pacing System for Real-Time Physical Activity Advising.

Hung-Yang Chang, Zhiguo Li, Subhro Das, Tian Hao, Chandramouli Maduri, Chohreh Partovian, James V. Codella, Ching-Hua Chen

Proceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, 2017

Interpretable Clustering for Prototypical Patient Understanding: A Case Study of Hypertension and Depression Subgroup Behavioral Profiling in National Health and Nutrition Examination Survey Data.

Pei-Yun Sabrina Hsueh, Subhro Das

Proceedings of the AMIA 2017, 2017

2016

Distributed Linear Filtering and Prediction of Time-varying Random Fields.

Subhro Das

PhD thesis, 2016

2015

Distributed Kalman Filtering With Dynamic Observations Consensus.

Subhro Das, José M. F. Moura

IEEE Trans. Signal Process., 2015

2013

Distributed state estimation in multi-agent networks.

Subhro Das, José M. F. Moura

Proceedings of the IEEE International Conference on Acoustics, 2013

Distributed Kalman filtering.

Subhro Das, José M. F. Moura

Proceedings of the 21st European Signal Processing Conference, 2013

Distributed linear estimation of dynamic random fields.

Subhro Das, José M. F. Moura

Proceedings of the 51st Annual Allerton Conference on Communication, 2013

Distributed Kalman filtering and Network Tracking Capacity.

Subhro Das, José M. F. Moura

Proceedings of the 2013 Asilomar Conference on Signals, 2013