Gautam Dasarathy

92 papers A* 7A 6B 8Misc 7Journal 52Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Advanced Tutorial: Label-Efficient Two-Sample Tests. CoRR Weizhi Li, Visar Berisha, Gautam Dasarathy
2025	J	`jnl`	High dimensional Bayesian optimization for circuit design. Intell. Decis. Technol. Mohit Malu, Diann Dow, Prateek Sharma, Alexis Cottam, Mat Binggeli, Gautam Dasarathy, Giulia Pedrielli, Andreas Spanias
2025	J	`jnl`	Learning Networks From Wide-Sense Stationary Stochastic Processes. IEEE Trans. Signal Inf. Process. over Networks Anirudh Rayas, Jiajun Cheng, Rajasekhar Anguluri, Deepjyoti Deka, Gautam Dasarathy
2025	J	`jnl`	Matched-Pair Experimental Design with Active Learning. CoRR Weizhi Li, Gautam Dasarathy, Visar Berisha
2025	J	`jnl`	Robust Model Selection of Gaussian Graphical Models. Trans. Mach. Learn. Res. Abrar Zahin, Rajasekhar Anguluri, Lalitha Sankar, Oliver Kosut, Gautam Dasarathy
2025	J	`jnl`	Statistically Valid Post-Deployment Monitoring Should Be Standard for AI-Based Digital Health. CoRR Pavel Dolin, Weizhi Li, Gautam Dasarathy, Visar Berisha
2025	B	`conf`	Structure Learning in Gaussian Graphical Models from Glauber Dynamics. ISIT Vignesh Tirukkonda, Anirudh Rayas, Gautam Dasarathy
2025	J	`jnl`	Unraveling overoptimism and publication bias in ML-driven science. Patterns Pouria Saidi, Gautam Dasarathy, Visar Berisha
2024	J	`jnl`	Active Sequential Two-Sample Testing. Trans. Mach. Learn. Res. Weizhi Li, Prad Kadambi, Pouria Saidi, Karthikeyan Natesan Ramamurthy, Gautam Dasarathy, Visar Berisha
2024	Misc	`conf`	Advanced Tutorial: Label-Efficient Two-Sample Tests. WSC Weizhi Li, Visar Berisha, Gautam Dasarathy
2024	—	`conf`	ClassBO: Bayesian Optimization for Heterogeneous Functions. LION Mohit Malu, Giulia Pedrielli, Gautam Dasarathy, Andreas Spanias
2024	J	`jnl`	Communication-Efficient Federated Learning over Wireless Channels via Gradient Sketching. CoRR Vineet Sunil Gattani, Junshan Zhang, Gautam Dasarathy
2024	—	`conf`	Computationally Efficient Active Learning of Gaussian Graphical Models. IEEECONF Abrar Zahin, Gautam Dasarathy
2024	J	`jnl`	Learning Networks from Wide-Sense Stationary Stochastic Processes. CoRR Anirudh Rayas, Jiajun Cheng, Rajasekhar Anguluri, Deepjyoti Deka, Gautam Dasarathy
2024	Misc	`conf`	Non-Stationary Bandits with Periodic Behavior: Harnessing Ramanujan Periodicity Transforms to Conquer Time-Varying Challenges. ICASSP Parth Thaker, Vineet Sunil Gattani, Vignesh Tirukkonda, Pouria Saidi, Gautam Dasarathy
2024	J	`jnl`	On Characterizations of Potential and Ordinal Potential Games. CoRR Sina Arefizadeh, Angelia Nedich, Gautam Dasarathy
2024	J	`jnl`	Orthogonality and graph divergence losses promote disentanglement in generative models. Frontiers Comput. Sci. Ankita Shukla, Rishi Dadhich, Rajhans Singh, Anirudh Rayas, Pouria Saidi, Gautam Dasarathy, Visar Berisha, Pavan K. Turaga
2024	Misc	`conf`	Rapid Change Localization in Dynamic Graphical Models. ICASSP Abrar Zahin, Weizhi Li, Gautam Dasarathy
2024	J	`jnl`	Structure Learning in Gaussian Graphical Models from Glauber Dynamics. CoRR Vignesh Tirukkonda, Anirudh Rayas, Gautam Dasarathy
2024	—	`conf`	The Sample Complexity of Differential Analysis for Networks that Obey Conservation Laws. IEEECONF Jiajun Cheng, Anirudh Rayas, Rajasekhar Anguluri, Gautam Dasarathy
2024	J	`jnl`	Unraveling overoptimism and publication bias in ML-driven science. CoRR Pouria Saidi, Gautam Dasarathy, Visar Berisha
2023	J	`jnl`	Active Sequential Two-Sample Testing. CoRR Weizhi Li, Karthikeyan Natesan Ramamurthy, Prad Kadambi, Pouria Saidi, Gautam Dasarathy, Visar Berisha
2023	—	`conf`	Class GP: Gaussian Process Modeling for Heterogeneous Functions. LION Mohit Malu, Giulia Pedrielli, Gautam Dasarathy, Andreas Spanias
2023	Misc	`conf`	Differential Analysis for Networks Obeying Conservation Laws. ICASSP Anirudh Rayas, Rajasekhar Anguluri, Jiajun Cheng, Gautam Dasarathy
2023	J	`jnl`	Differential Analysis for Networks Obeying Conservation Laws. CoRR Anirudh Rayas, Rajasekhar Anguluri, Jiajun Cheng, Gautam Dasarathy
2022	J	`jnl`	A Graph-Based Approach to Boundary Estimation With Mobile Sensors. IEEE Robotics Autom. Lett. Sean O. Stalley, Dingyu Wang, Gautam Dasarathy, John Lipor
2022	J	`jnl`	A Machine Learning Framework for Event Identification via Modal Analysis of PMU Data. CoRR Nima T. Bazargani, Gautam Dasarathy, Lalitha Sankar, Oliver Kosut
2022	J	`jnl`	A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization. IEEE Trans. Inf. Theory Tyler Sypherd, Mario Díaz, John Kevin Cava, Gautam Dasarathy, Peter Kairouz, Lalitha Sankar
2022	A	`conf`	A label efficient two-sample test. UAI Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
2022	J	`jnl`	Controllability of Coarsely Measured Networked Linear Dynamical Systems (Extended Version). CoRR Nafiseh Ghoroghchian, Anguluri Rajasekhar, Gautam Dasarathy, Stark C. Draper
2022	J	`jnl`	Grid Topology Identification With Hidden Nodes via Structured Norm Minimization. IEEE Control. Syst. Lett. Anguluri Rajasekhar, Gautam Dasarathy, Oliver Kosut, Lalitha Sankar
2022	A*	`conf`	Learning the Structure of Large Networked Systems Obeying Conservation Laws. NeurIPS Anirudh Rayas, Rajasekhar Anguluri, Gautam Dasarathy
2022	J	`jnl`	Learning the Structure of Large Networked Systems Obeying Conservation Laws. CoRR Anirudh Rayas, Anguluri Rajasekhar, Gautam Dasarathy
2022	A*	`conf`	Maximizing and Satisficing in Multi-armed Bandits with Graph Information. NeurIPS Parth Thaker, Mohit Malu, Nikhil Rao, Gautam Dasarathy
2022	J	`jnl`	Robust Model Selection of Non Tree-Structured Gaussian Graphical Models. CoRR Abrar Zahin, Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar, Gautam Dasarathy
2022	J	`jnl`	State and Topology Estimation for Unobservable Distribution Systems Using Deep Neural Networks. IEEE Trans. Instrum. Meas. Behrouz Azimian, Reetam Sen Biswas, Shiva Moshtagh, Anamitra Pal, Lang Tong, Gautam Dasarathy
2021	J	`jnl`	A Multisensory Approach to Present Phonemes as Language Through a Wearable Haptic Device. IEEE Trans. Haptics Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Indu Manickam, Gautam Dasarathy, Richard G. Baraniuk, Marcia K. O'Malley
2021	J	`jnl`	A label efficient two-sample test. CoRR Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
2021	—	`conf`	Bayesian Optimization in High-Dimensional Spaces: A Brief Survey. IISA Mohit Malu, Gautam Dasarathy, Andreas Spanias
2021	J	`jnl`	Digital medicine and the curse of dimensionality. npj Digit. Medicine Visar Berisha, Chelsea Krantsevich, P. Richard Hahn, Shira Hahn, Gautam Dasarathy, Pavan K. Turaga, Julie Liss
2021	A	`conf`	Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model. AISTATS Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper
2021	J	`jnl`	Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model. CoRR Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper
2021	J	`jnl`	Pure Exploration in Multi-armed Bandits with Graph Side Information. CoRR Parth K. Thaker, Nikhil Rao, Mohit Malu, Gautam Dasarathy
2021	J	`jnl`	State and Topology Estimation for Unobservable Distribution Systems using Deep Neural Networks. CoRR Behrouz Azimian, Reetam Sen Biswas, Anamitra Pal, Lang Tong, Gautam Dasarathy
2020	—	`conf`	Differentiable Programming for Hyperspectral Unmixing Using a Physics-Based Dispersion Model. ECCV (27) John Janiczek, Parth Thaker, Gautam Dasarathy, Christopher S. Edwards, Philip Christensen, Suren Jayasuriya
2020	J	`jnl`	Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model. CoRR John Janiczek, Parth Thaker, Gautam Dasarathy, Christopher S. Edwards, Philip Christensen, Suren Jayasuriya
2020	A*	`conf`	Finding the Homology of Decision Boundaries with Active Learning. NeurIPS Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
2020	J	`jnl`	Finding the Homology of Decision Boundaries with Active Learning. CoRR Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
2020	B	`conf`	On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems. ISIT Parth K. Thaker, Gautam Dasarathy, Angelia Nedic
2020	J	`jnl`	On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems. CoRR Parth Thaker, Gautam Dasarathy, Angelia Nedic
2020	J	`jnl`	On the alpha-loss Landscape in the Logistic Model. CoRR Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy
2020	B	`conf`	On the α-loss Landscape in the Logistic Model. ISIT Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy
2020	A	`conf`	Regularization via Structural Label Smoothing. AISTATS Weizhi Li, Gautam Dasarathy, Visar Berisha
2020	J	`jnl`	Regularization via Structural Label Smoothing. CoRR Weizhi Li, Gautam Dasarathy, Visar Berisha
2020	A	`conf`	Thresholding Graph Bandits with GrAPL. AISTATS Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk
2019	—	`conf`	A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery. ICLR (Poster) Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
2019	J	`jnl`	A Tunable Loss Function for Classification. CoRR Tyler Sypherd, Mario Díaz, Harshit Laddha, Lalitha Sankar, Peter Kairouz, Gautam Dasarathy
2019	—	`conf`	Distance-Penalized Active Learning via Markov Decision Processes. DSW Dingyu Wang, John Lipor, Gautam Dasarathy
2019	B	`conf`	Gaussian Graphical Model Selection from Size Constrained Measurements. ISIT Gautam Dasarathy
2019	J	`jnl`	IdeoTrace: A Framework for Ideology Tracing with a Case Study on the 2016 U.S. Presidential Election. CoRR Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk
2019	B	`conf`	IdeoTrace: a framework for ideology tracing with a case study on the 2016 U.S. presidential election. ASONAM Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk
2019	J	`jnl`	Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2019	J	`jnl`	Thresholding Graph Bandits with GrAPL. CoRR Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk
2018	Misc	`conf`	Conveying language through haptics: a multi-sensory approach. UbiComp Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Nickolas P. Walling, Indu Manickam, Gautam Dasarathy, Ali Israr, Frances W. Y. Lau, Keith Klumb, Brian Knott, Freddy Abnousi, Richard G. Baraniuk, Marcia K. O'Malley
2018	A*	`conf`	MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. ICML Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk
2018	J	`jnl`	MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. CoRR Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk
2018	Misc	`conf`	Quantile Search with Time-Varying Search Parameter. ACSSC John Lipor, Gautam Dasarathy
2017	J	`jnl`	Coalescent-based species tree estimation: a stochastic Farris transform. CoRR Gautam Dasarathy, Elchanan Mossel, Robert D. Nowak, Sebastien Roch
2017	J	`jnl`	DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks. CoRR Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
2017	—	`conf`	DeepCodec: Adaptive sensing and recovery via deep convolutional neural networks. Allerton Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
2017	A*	`conf`	Multi-fidelity Bayesian Optimisation with Continuous Approximations. ICML Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
2017	Misc	`conf`	Sketched covariance testing: A compression-statistics tradeoff. ACSSC Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk
2017	B	`conf`	Sketched covariance testing: A compression-statistics tradeoff. ISIT Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk
2016	A	`conf`	Active Learning Algorithms for Graphical Model Selection. AISTATS Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park
2016	J	`jnl`	Active Learning Algorithms for Graphical Model Selection. CoRR Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park
2016	—	`conf`	Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. NIPS Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2016	J	`jnl`	Multi-fidelity Gaussian Process Bandit Optimisation. CoRR Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2016	—	`conf`	The Multi-fidelity Multi-armed Bandit. NIPS Kirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider
2016	J	`jnl`	The Multi-fidelity Multi-armed Bandit. CoRR Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
2015	J	`jnl`	Data Requirement for Phylogenetic Inference from Multiple Loci: A New Distance Method. IEEE ACM Trans. Comput. Biol. Bioinform. Gautam Dasarathy, Robert D. Nowak, Sébastien Roch
2015	A*	`conf`	S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification. COLT Gautam Dasarathy, Robert D. Nowak, Xiaojin Zhu
2015	J	`jnl`	S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification. CoRR Gautam Dasarathy, Robert D. Nowak, Xiaojin Zhu
2015	J	`jnl`	Sketching Sparse Matrices, Covariances, and Graphs via Tensor Products. IEEE Trans. Inf. Theory Gautam Dasarathy, Parikshit Shah, Badri Narayan Bhaskar, Robert D. Nowak
2014	J	`jnl`	Data Requirement for Phylogenetic Inference from Multiple Loci: A New Distance Method. CoRR Gautam Dasarathy, Robert D. Nowak, Sebastien Roch
2014	B	`conf`	New sample complexity bounds for phylogenetic inference from multiple loci. ISIT Gautam Dasarathy, Robert D. Nowak, Sébastien Roch
2013	J	`jnl`	Sketching Sparse Matrices CoRR Gautam Dasarathy, Parikshit Shah, Badri Narayan Bhaskar, Robert D. Nowak
2012	—	`conf`	Covariance sketching. Allerton Conference Gautam Dasarathy, Parikshit Shah, Badri Narayan Bhaskar, Robert D. Nowak
2012	J	`jnl`	Efficient Network Tomography for Internet Topology Discovery. IEEE/ACM Trans. Netw. Brian Eriksson, Gautam Dasarathy, Paul Barford, Robert D. Nowak
2011	J	`jnl`	Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities CoRR Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak
2011	A	`conf`	Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities. AISTATS Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak
2011	B	`conf`	On reliability of content identification from databases based on noisy queries. ISIT Gautam Dasarathy, Stark C. Draper
2010	A*	`conf`	Toward the Practical Use of Network Tomography for Internet Topology Discovery. INFOCOM Brian Eriksson, Gautam Dasarathy, Paul Barford, Robert D. Nowak