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2020 – today
- 2024
[j5]Augustin-Alexandru Saucan
, Subhro Das, Moe Z. Win:
Decentralized fused-learner architectures for Bayesian reinforcement learning. Artif. Intell. 331: 104094 (2024)- [c35]Wang Zhang, Ziwen Martin Ma, Subhro Das, Tsui-Wei Lily Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen:
One Step Closer to Unbiased Aleatoric Uncertainty Estimation. AAAI 2024: 16857-16864 - [c34]Neil Thompson, Martin Fleming, Benny J. Tang, Anna M. Pastwa, Nicholas Borge, Brian C. Goehring, Subhro Das:
A Model for Estimating the Economic Costs of Computer Vision Systems That Use Deep Learning. AAAI 2024: 23012-23018 - [c33]Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh:
Thermometer: Towards Universal Calibration for Large Language Models. ICML 2024 - [c32]Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell:
Group Fairness with Uncertain Sensitive Attributes. ISIT 2024: 208-213 - [i33]Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell:
Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions. CoRR abs/2402.06160 (2024) - [i32]Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh:
Thermometer: Towards Universal Calibration for Large Language Models. CoRR abs/2403.08819 (2024) - [i31]Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag:
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers. CoRR abs/2404.02806 (2024) - 2023
- [j4]Farzan Farnia, William W. Wang, Subhro Das, Ali Jadbabaie:
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models. SIAM J. Math. Data Sci. 5(1): 122-146 (2023) - [c31]Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell:
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model. AAAI 2023: 9772-9781 - [c30]Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag:
Who Should Predict? Exact Algorithms For Learning to Defer to Humans. AISTATS 2023: 10520-10545 - [c29]Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell:
Reliable Gradient-free and Likelihood-free Prompt Tuning. EACL (Findings) 2023: 2371-2384 - [c28]Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng:
Attacking c-MARL More Effectively: A Data Driven Approach. ICDM 2023: 1271-1276 - [c27]Tuomas P. Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng:
Label-free Concept Bottleneck Models. ICLR 2023 - [c26]Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen:
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. ICML 2023: 41694-41714 - [c25]Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag:
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding. NeurIPS 2023 - [i30]Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag:
Who Should Predict? Exact Algorithms For Learning to Defer to Humans. CoRR abs/2301.06197 (2023) - [i29]Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen:
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. CoRR abs/2302.05783 (2023) - [i28]Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell:
Group Fairness with Uncertainty in Sensitive Attributes. CoRR abs/2302.08077 (2023) - [i27]Amirhossein Reisizadeh, Haochuan Li, Subhro Das, Ali Jadbabaie:
Variance-reduced Clipping for Non-convex Optimization. CoRR abs/2303.00883 (2023) - [i26]Tuomas P. Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng:
Label-Free Concept Bottleneck Models. CoRR abs/2304.06129 (2023) - [i25]Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell:
Reliable Gradient-free and Likelihood-free Prompt Tuning. CoRR abs/2305.00593 (2023) - [i24]Yingying Li, Tianpeng Zhang, Subhro Das, Jeff S. Shamma, Na Li:
Non-asymptotic System Identification for Linear Systems with Nonlinear Policies. CoRR abs/2306.10369 (2023) - [i23]Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag:
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding. CoRR abs/2311.01007 (2023) - [i22]Quang Minh Nguyen, Lam M. Nguyen, Subhro Das:
Correlated Attention in Transformers for Multivariate Time Series. CoRR abs/2311.11959 (2023) - [i21]Wang Zhang, Ziwen Martin Ma, Subhro Das, Tsui-Wei Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen:
One step closer to unbiased aleatoric uncertainty estimation. CoRR abs/2312.10469 (2023) - 2022
- [c24]Maysa Malfiza Garcia de Macedo, Wyatt Clarke, Eli Lucherini, Tyler Baldwin, Dilermando Queiroz Neto, Rogério Abreu de Paula, Subhro Das:
Practical Skills Demand Forecasting via Representation Learning of Temporal Dynamics. AIES 2022: 285-294 - [c23]Tyler Baldwin, Wyatt Clarke, Maysa M. Garcia de Macedo, Rogério de Paula, Subhro Das:
Better Skill-based Job Representations, Assessed via Job Transition Data. IEEE Big Data 2022: 2182-2185 - [c22]Saksham Gandhi, Raj Nagesh, Subhro Das:
Learning skills adjacency representations for optimized reskilling recommendations. IEEE Big Data 2022: 2253-2258 - [c21]Subhro Das:
On observability and optimal gain design for distributed linear filtering and prediction. EUSIPCO 2022: 1846-1850 - [c20]Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie:
On Convergence of Gradient Descent Ascent: A Tight Local Analysis. ICML 2022: 12717-12740 - [c19]Abhin Shah, Yuheng Bu, Joshua K. Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell:
Selective Regression under Fairness Criteria. ICML 2022: 19598-19615 - [c18]Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie:
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity. ICML 2022: 26347-26361 - [c17]Subhro Das:
An Alternative Approach for Distributed Parameter Estimation Under Gaussian Settings. MLSP 2022: 1-6 - [i20]Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng:
Evaluating Robustness of Cooperative MARL: A Model-based Approach. CoRR abs/2202.03558 (2022) - [i19]Subhro Das:
On observability and optimal gain design for distributed linear filtering and prediction. CoRR abs/2203.03521 (2022) - [i18]Subhro Das:
An alternative approach for distributed parameter estimation under Gaussian settings. CoRR abs/2204.08317 (2022) - [i17]Maysa M. Garcia de Macedo, Wyatt Clarke, Eli Lucherini, Tyler Baldwin, Dilermando Queiroz Neto, Rogério de Paula, Subhro Das:
Practical Skills Demand Forecasting via Representation Learning of Temporal Dynamics. CoRR abs/2205.09508 (2022) - [i16]Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie:
On Convergence of Gradient Descent Ascent: A Tight Local Analysis. CoRR abs/2207.00957 (2022) - [i15]Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell:
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model. CoRR abs/2212.07359 (2022) - 2021
- [c16]Yingying Li, Subhro Das, Na Li:
Online Optimal Control with Affine Constraints. AAAI 2021: 8527-8537 - [c15]Sarthak Chatterjee, Subhro Das, Sérgio Pequito:
IF: Iterative Fractional Optimization. ESANN 2021 - [c14]Nathan Hunt, Nathan Fulton, Sara Magliacane, Trong Nghia Hoang, Subhro Das, Armando Solar-Lezama:
Verifiably safe exploration for end-to-end reinforcement learning. HSCC 2021: 14:1-14:11 - [c13]Joshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell:
Fair Selective Classification Via Sufficiency. ICML 2021: 6076-6086 - [c12]Augustin-Alexandru Saucan, Subhro Das, Moe Z. Win:
On Multisensor Activation Policies for Bernoulli Tracking. MILCOM 2021: 795-801 - [i14]Abhin Shah, Yuheng Bu, Joshua Ka-Wing Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell:
Selective Regression Under Fairness Criteria. CoRR abs/2110.15403 (2021) - [i13]Yingying Li, Subhro Das, Jeff S. Shamma, Na Li:
Safe Adaptive Learning-based Control for Constrained Linear Quadratic Regulators with Regret Guarantees. CoRR abs/2111.00411 (2021) - 2020
- [c11]Subhro Das, Sebastian Steffen, Wyatt Clarke, Prabhat Reddy, Erik Brynjolfsson, Martin Fleming:
Learning Occupational Task-Shares Dynamics for the Future of Work. AIES 2020: 36-42 - [c10]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines. CHIL 2020: 19-29 - [c9]Subhro Das, Chandramouli Maduri, Ching-Hua Chen, Pei-Yun Sabrina Hsueh:
Learning Interpretable Behavioral Engagement for Care Management. MIE 2020: 1006-1010 - [i12]Subhro Das, Prasanth Lade, Soundar Srinivasan:
Model adaptation and unsupervised learning with non-stationary batch data under smooth concept drift. CoRR abs/2002.04094 (2020) - [i11]Subhro Das, Sebastian Steffen, Wyatt Clarke, Prabhat Reddy, Erik Brynjolfsson, Martin Fleming:
Learning Occupational Task-Shares Dynamics for the Future of Work. CoRR abs/2002.05655 (2020) - [i10]Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie:
Stochastic Optimization with Non-stationary Noise. CoRR abs/2006.04429 (2020) - [i9]Nathan Fulton, Nathan Hunt, Nghia Hoang, Subhro Das:
Formal Verification of End-to-End Learning in Cyber-Physical Systems: Progress and Challenges. CoRR abs/2006.09181 (2020) - [i8]Farzan Farnia, William Wang, Subhro Das, Ali Jadbabaie:
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models. CoRR abs/2006.10293 (2020) - [i7]Orlando Romero, Subhro Das, Pin-Yu Chen, Sérgio Pequito:
A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm. CoRR abs/2006.12690 (2020) - [i6]Nathan Hunt, Nathan Fulton, Sara Magliacane, Nghia Hoang, Subhro Das, Armando Solar-Lezama:
Verifiably Safe Exploration for End-to-End Reinforcement Learning. CoRR abs/2007.01223 (2020) - [i5]Yingying Li, Subhro Das, Na Li:
Online Optimal Control with Affine Constraints. CoRR abs/2010.04891 (2020)
2010 – 2019
- 2019
- [j3]Zhiguo Li, Subhro Das, James V. Codella, Tian Hao, Kun Lin, Chandramouli Maduri, Ching-Hua Chen:
An Adaptive, Data-Driven Personalized Advisor for Increasing Physical Activity. IEEE J. Biomed. Health Informatics 23(3): 999-1010 (2019) - [i4]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines. CoRR abs/1905.03297 (2019) - [i3]Subhro Das, Chandramouli Maduri, Ching-Hua Chen, Pei-Yun Sabrina Hsueh:
Learning Patient Engagement in Care Management: Performance vs. Interpretability. CoRR abs/1906.08339 (2019) - 2018
- [c8]Pei-Yun Sabrina Hsueh, Subhro Das, Chandramouli Maduri, Karie Kelly:
Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records. AMIA 2018 - 2017
- [j2]Subhro Das, José M. F. Moura:
Consensus+Innovations Distributed Kalman Filter With Optimized Gains. IEEE Trans. Signal Process. 65(2): 467-481 (2017) - [c7]Pei-Yun Sabrina Hsueh, Subhro Das:
Interpretable Clustering for Prototypical Patient Understanding: A Case Study of Hypertension and Depression Subgroup Behavioral Profiling in National Health and Nutrition Examination Survey Data. AMIA 2017 - [c6]Hung-Yang Chang, Zhiguo Li, Subhro Das, Tian Hao, Chandramouli Maduri, Chohreh Partovian, James V. Codella, Ching-Hua Chen:
A Personalized Pacing System for Real-Time Physical Activity Advising. CHASE 2017: 266-267 - [c5]Pei-Yun Sabrina Hsueh, Sanjoy Dey, Subhro Das, Thomas Wetter:
Making Sense of Patient-Generated Health Data for Interpretable Patient-Centered Care: The Transition from "More" to "Better". MedInfo 2017: 113-117 - [i2]Subhro Das, José M. F. Moura:
Distributed Estimation of Dynamic Fields over Multi-agent Networks. CoRR abs/1701.02710 (2017) - 2016
- [b1]Subhro Das:
Distributed Linear Filtering and Prediction of Time-varying Random Fields. Carnegie Mellon University, USA, 2016 - [i1]Subhro Das, José M. F. Moura:
Consensus+Innovations Distributed Kalman Filter with Optimized Gains. CoRR abs/1605.06096 (2016) - 2015
- [j1]Subhro Das, José M. F. Moura:
Distributed Kalman Filtering With Dynamic Observations Consensus. IEEE Trans. Signal Process. 63(17): 4458-4473 (2015) - 2013
- [c4]Subhro Das, José M. F. Moura:
Distributed Kalman filtering and Network Tracking Capacity. ACSSC 2013: 629-633 - [c3]Subhro Das, José M. F. Moura:
Distributed linear estimation of dynamic random fields. Allerton 2013: 1120-1125 - [c2]Subhro Das, José M. F. Moura:
Distributed Kalman filtering. EUSIPCO 2013: 1-5 - [c1]Subhro Das, José M. F. Moura:
Distributed state estimation in multi-agent networks. ICASSP 2013: 4246-4250
Coauthor Index
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last updated on 2024-10-12 22:54 CEST by the dblp team
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