Dasarathy, Gautam

20 publications

TMLR 2025 Robust Model Selection of Gaussian Graphical Models Abrar Zahin, Rajasekhar Anguluri, Lalitha Sankar, Oliver Kosut, Gautam Dasarathy

NeurIPS 2025 Statistically Valid Post-Deployment Monitoring Should Be Standard for AI-Based Digital Health Pavel Dolin, Weizhi Li, Gautam Dasarathy, Visar Berisha

TMLR 2024 Active Sequential Two-Sample Testing Weizhi Li, Prad Kadambi, Pouria Saidi, Karthikeyan Natesan Ramamurthy, Gautam Dasarathy, Visar Berisha

UAI 2022 A Label Efficient Two-Sample Test Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha

NeurIPS 2022 Learning the Structure of Large Networked Systems Obeying Conservation Laws Anirudh Rayas, Rajasekhar Anguluri, Gautam Dasarathy

NeurIPS 2022 Maximizing and Satisficing in Multi-Armed Bandits with Graph Information Parth Thaker, Mohit Malu, Nikhil Rao, Gautam Dasarathy

AISTATS 2021 Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model Nafiseh Ghoroghchian, Gautam Dasarathy, Stark Draper

ECCV 2020 Differentiable Programming for Hyperspectral Unmixing Using a Physics-Based Dispersion Model John Janiczek, Parth Thaker, Gautam Dasarathy, Christopher S. Edwards, Philip Christensen, Suren Jayasuriya

NeurIPS 2020 Finding the Homology of Decision Boundaries with Active Learning Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha

AISTATS 2020 Regularization via Structural Label Smoothing Weizhi Li, Gautam Dasarathy, Visar Berisha

AISTATS 2020 Thresholding Graph Bandits with GrAPL Daniel LeJeune, Gautam Dasarathy, Richard Baraniuk

ICLR 2019 A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk

JAIR 2019 Multi-Fidelity Gaussian Process Bandit Optimisation Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos

ICML 2018 MISSION: Ultra Large-Scale Feature Selection Using Count-Sketches Amirali Aghazadeh, Ryan Spring, Daniel Lejeune, Gautam Dasarathy, Anshumali Shrivastava, Baraniuk

ICML 2017 Multi-Fidelity Bayesian Optimisation with Continuous Approximations Kirthevasan Kandasamy, Gautam Dasarathy, Jeff Schneider, Barnabás Póczos

AISTATS 2016 Active Learning Algorithms for Graphical Model Selection Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park

NeurIPS 2016 Gaussian Process Bandit Optimisation with Multi-Fidelity Evaluations Kirthevasan Kandasamy, Gautam Dasarathy, Junier B Oliva, Jeff Schneider, Barnabas Poczos

NeurIPS 2016 The Multi-Fidelity Multi-Armed Bandit Kirthevasan Kandasamy, Gautam Dasarathy, Barnabas Poczos, Jeff Schneider

COLT 2015 S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification Gautam Dasarathy, Robert D. Nowak, Xiaojin Zhu

AISTATS 2011 Active Clustering: Robust and Efficient Hierarchical Clustering Using Adaptively Selected Similarities Brian Eriksson, Gautam Dasarathy, Aarti Singh, Rob Nowak