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ORCIDGautam Dasarathy
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- affiliation: Arizona State University, Tempe, AZ, USA
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2020 – today
- 2024
[j12]Ankita Shukla, Rishi Dadhich, Rajhans Singh, Anirudh Rayas, Pouria Saidi, Gautam Dasarathy, Visar Berisha, Pavan K. Turaga:
Orthogonality and graph divergence losses promote disentanglement in generative models. Frontiers Comput. Sci. 6 (2024)- [j11]Weizhi Li, Prad Kadambi, Pouria Saidi, Karthikeyan Natesan Ramamurthy, Gautam Dasarathy, Visar Berisha:
Active Sequential Two-Sample Testing. Trans. Mach. Learn. Res. 2024 (2024) - [c35]Abrar Zahin, Weizhi Li, Gautam Dasarathy:
Rapid Change Localization in Dynamic Graphical Models. ICASSP 2024: 7770-7774 - [c34]Parth Thaker, Vineet Gattani, Vignesh Tirukkonda, Pouria Saidi, Gautam Dasarathy:
Non-Stationary Bandits with Periodic Behavior: Harnessing Ramanujan Periodicity Transforms to Conquer Time-Varying Challenges. ICASSP 2024: 7790-7794 - [i30]Sina Arefizadeh, Angelia Nedich, Gautam Dasarathy:
On Characterizations of Potential and Ordinal Potential Games. CoRR abs/2405.06253 (2024) - [i29]Pouria Saidi, Gautam Dasarathy, Visar Berisha:
Unraveling overoptimism and publication bias in ML-driven science. CoRR abs/2405.14422 (2024) - 2023
- [c33]Anirudh Rayas, Rajasekhar Anguluri, Jiajun Cheng, Gautam Dasarathy:
Differential Analysis for Networks Obeying Conservation Laws. ICASSP 2023: 1-5 - [c32]Mohit Malu, Giulia Pedrielli, Gautam Dasarathy, Andreas Spanias:
Class GP: Gaussian Process Modeling for Heterogeneous Functions. LION 2023: 408-423 - [i28]Weizhi Li, Karthikeyan Natesan Ramamurthy, Prad Kadambi, Pouria Saidi, Gautam Dasarathy, Visar Berisha:
Active Sequential Two-Sample Testing. CoRR abs/2301.12616 (2023) - [i27]Anirudh Rayas, Rajasekhar Anguluri, Jiajun Cheng, Gautam Dasarathy:
Differential Analysis for Networks Obeying Conservation Laws. CoRR abs/2302.00002 (2023) - 2022
- [j10]Anguluri Rajasekhar
, Gautam Dasarathy, Oliver Kosut, Lalitha Sankar:
Grid Topology Identification With Hidden Nodes via Structured Norm Minimization. IEEE Control. Syst. Lett. 6: 1244-1249 (2022) - [j9]Sean O. Stalley, Dingyu Wang, Gautam Dasarathy, John Lipor:
A Graph-Based Approach to Boundary Estimation With Mobile Sensors. IEEE Robotics Autom. Lett. 7(2): 4991-4998 (2022) - [j8]Behrouz Azimian, Reetam Sen Biswas, Shiva Moshtagh, Anamitra Pal, Lang Tong, Gautam Dasarathy:
State and Topology Estimation for Unobservable Distribution Systems Using Deep Neural Networks. IEEE Trans. Instrum. Meas. 71: 1-14 (2022) - [j7]Tyler Sypherd, Mario Díaz, John Kevin Cava, Gautam Dasarathy, Peter Kairouz, Lalitha Sankar:
A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization. IEEE Trans. Inf. Theory 68(9): 6021-6051 (2022) - [c31]Anirudh Rayas, Rajasekhar Anguluri, Gautam Dasarathy:
Learning the Structure of Large Networked Systems Obeying Conservation Laws. NeurIPS 2022 - [c30]Parth Thaker, Mohit Malu, Nikhil Rao, Gautam Dasarathy:
Maximizing and Satisficing in Multi-armed Bandits with Graph Information. NeurIPS 2022 - [c29]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
A label efficient two-sample test. UAI 2022: 1168-1177 - [i26]Nima T. Bazargani, Gautam Dasarathy, Lalitha Sankar, Oliver Kosut:
A Machine Learning Framework for Event Identification via Modal Analysis of PMU Data. CoRR abs/2202.06836 (2022) - [i25]Anirudh Rayas, Anguluri Rajasekhar, Gautam Dasarathy:
Learning the Structure of Large Networked Systems Obeying Conservation Laws. CoRR abs/2206.07083 (2022) - [i24]Nafiseh Ghoroghchian, Anguluri Rajasekhar, Gautam Dasarathy, Stark C. Draper:
Controllability of Coarsely Measured Networked Linear Dynamical Systems (Extended Version). CoRR abs/2206.10569 (2022) - [i23]Abrar Zahin, Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar, Gautam Dasarathy:
Robust Model Selection of Non Tree-Structured Gaussian Graphical Models. CoRR abs/2211.05690 (2022) - 2021
- [j6]Visar Berisha, Chelsea Krantsevich, P. Richard Hahn, Shira Hahn, Gautam Dasarathy, Pavan K. Turaga, Julie Liss:
Digital medicine and the curse of dimensionality. npj Digit. Medicine 4 (2021) - [j5]Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Indu Manickam, Gautam Dasarathy, Richard G. Baraniuk, Marcia K. O'Malley:
A Multisensory Approach to Present Phonemes as Language Through a Wearable Haptic Device. IEEE Trans. Haptics 14(1): 188-199 (2021) - [c28]Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper:
Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model. AISTATS 2021: 3619-3627 - [c27]Mohit Malu, Gautam Dasarathy, Andreas Spanias:
Bayesian Optimization in High-Dimensional Spaces: A Brief Survey. IISA 2021: 1-8 - [i22]Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper:
Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model. CoRR abs/2102.13135 (2021) - [i21]Behrouz Azimian, Reetam Sen Biswas, Anamitra Pal, Lang Tong, Gautam Dasarathy:
State and Topology Estimation for Unobservable Distribution Systems using Deep Neural Networks. CoRR abs/2104.07208 (2021) - [i20]Parth K. Thaker, Nikhil Rao, Mohit Malu, Gautam Dasarathy:
Pure Exploration in Multi-armed Bandits with Graph Side Information. CoRR abs/2108.01152 (2021) - [i19]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
A label efficient two-sample test. CoRR abs/2111.08861 (2021) - 2020
- [c26]Weizhi Li, Gautam Dasarathy, Visar Berisha:
Regularization via Structural Label Smoothing. AISTATS 2020: 1453-1463 - [c25]Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk:
Thresholding Graph Bandits with GrAPL. AISTATS 2020: 2476-2485 - [c24]John Janiczek, Parth Thaker, Gautam Dasarathy, Christopher S. Edwards, Philip Christensen, Suren Jayasuriya:
Differentiable Programming for Hyperspectral Unmixing Using a Physics-Based Dispersion Model. ECCV (27) 2020: 649-666 - [c23]Parth K. Thaker, Gautam Dasarathy, Angelia Nedic:
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems. ISIT 2020: 1438-1443 - [c22]Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy:
On the α-loss Landscape in the Logistic Model. ISIT 2020: 2700-2705 - [c21]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
Finding the Homology of Decision Boundaries with Active Learning. NeurIPS 2020 - [i18]Weizhi Li, Gautam Dasarathy, Visar Berisha:
Regularization via Structural Label Smoothing. CoRR abs/2001.01900 (2020) - [i17]Parth Thaker, Gautam Dasarathy, Angelia Nedic:
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems. CoRR abs/2002.01066 (2020) - [i16]Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy:
On the alpha-loss Landscape in the Logistic Model. CoRR abs/2006.12406 (2020) - [i15]John Janiczek, Parth Thaker, Gautam Dasarathy, Christopher S. Edwards, Philip Christensen, Suren Jayasuriya:
Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model. CoRR abs/2007.05996 (2020) - [i14]Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha:
Finding the Homology of Decision Boundaries with Active Learning. CoRR abs/2011.09645 (2020)
2010 – 2019
- 2019
- [j4]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. 66: 151-196 (2019) - [c20]Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk:
IdeoTrace: a framework for ideology tracing with a case study on the 2016 U.S. presidential election. ASONAM 2019: 274-281 - [c19]Dingyu Wang, John Lipor, Gautam Dasarathy:
Distance-Penalized Active Learning via Markov Decision Processes. DSW 2019: 155-159 - [c18]Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk:
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery. ICLR (Poster) 2019 - [c17]Gautam Dasarathy:
Gaussian Graphical Model Selection from Size Constrained Measurements. ISIT 2019: 1302-1306 - [i13]Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk:
IdeoTrace: A Framework for Ideology Tracing with a Case Study on the 2016 U.S. Presidential Election. CoRR abs/1905.08831 (2019) - [i12]Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk:
Thresholding Graph Bandits with GrAPL. CoRR abs/1905.09190 (2019) - [i11]Tyler Sypherd, Mario Díaz, Harshit Laddha, Lalitha Sankar, Peter Kairouz, Gautam Dasarathy:
A Tunable Loss Function for Classification. CoRR abs/1906.02314 (2019) - 2018
- [c16]John Lipor, Gautam Dasarathy:
Quantile Search with Time-Varying Search Parameter. ACSSC 2018: 1016-1018 - [c15]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:
Conveying language through haptics: a multi-sensory approach. UbiComp 2018: 25-32 - [c14]Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk:
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. ICML 2018: 80-88 - [i10]Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk:
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. CoRR abs/1806.04310 (2018) - 2017
- [c13]Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk:
Sketched covariance testing: A compression-statistics tradeoff. ACSSC 2017: 676-680 - [c12]Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk:
DeepCodec: Adaptive sensing and recovery via deep convolutional neural networks. Allerton 2017: 744 - [c11]Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Bayesian Optimisation with Continuous Approximations. ICML 2017: 1799-1808 - [c10]Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk:
Sketched covariance testing: A compression-statistics tradeoff. ISIT 2017: 2268-2272 - [i9]Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk:
DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks. CoRR abs/1707.03386 (2017) - [i8]Gautam Dasarathy, Elchanan Mossel, Robert D. Nowak, Sebastien Roch:
Coalescent-based species tree estimation: a stochastic Farris transform. CoRR abs/1707.04300 (2017) - 2016
- [c9]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. AISTATS 2016: 1356-1364 - [c8]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. NIPS 2016: 992-1000 - [c7]Kirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider:
The Multi-fidelity Multi-armed Bandit. NIPS 2016: 1777-1785 - [i7]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. CoRR abs/1602.00354 (2016) - [i6]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Gaussian Process Bandit Optimisation. CoRR abs/1603.06288 (2016) - [i5]Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos:
The Multi-fidelity Multi-armed Bandit. CoRR abs/1610.09726 (2016) - 2015
- [j3]Gautam Dasarathy, Robert D. Nowak, Sébastien Roch:
Data Requirement for Phylogenetic Inference from Multiple Loci: A New Distance Method. IEEE ACM Trans. Comput. Biol. Bioinform. 12(2): 422-432 (2015) - [j2]Gautam Dasarathy, Parikshit Shah, Badri Narayan Bhaskar, Robert D. Nowak:
Sketching Sparse Matrices, Covariances, and Graphs via Tensor Products. IEEE Trans. Inf. Theory 61(3): 1373-1388 (2015) - [c6]Gautam Dasarathy, Robert D. Nowak, Xiaojin Zhu:
S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification. COLT 2015: 503-522 - [i4]Gautam Dasarathy, Robert D. Nowak, Xiaojin Zhu:
S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification. CoRR abs/1506.08760 (2015) - 2014
- [c5]Gautam Dasarathy, Robert D. Nowak, Sébastien Roch:
New sample complexity bounds for phylogenetic inference from multiple loci. ISIT 2014: 2037-2041 - [i3]Gautam Dasarathy, Robert D. Nowak, Sebastien Roch:
Data Requirement for Phylogenetic Inference from Multiple Loci: A New Distance Method. CoRR abs/1404.7055 (2014) - 2013
- [i2]Gautam Dasarathy, Parikshit Shah, Badri Narayan Bhaskar, Robert D. Nowak:
Sketching Sparse Matrices. CoRR abs/1303.6544 (2013) - 2012
- [j1]Brian Eriksson, Gautam Dasarathy, Paul Barford, Robert D. Nowak:
Efficient Network Tomography for Internet Topology Discovery. IEEE/ACM Trans. Netw. 20(3): 931-943 (2012) - [c4]Gautam Dasarathy, Parikshit Shah, Badri Narayan Bhaskar, Robert D. Nowak:
Covariance sketching. Allerton Conference 2012: 1026-1033 - 2011
- [c3]Gautam Dasarathy, Stark C. Draper:
On reliability of content identification from databases based on noisy queries. ISIT 2011: 1066-1070 - [c2]Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak:
Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities. AISTATS 2011: 260-268 - [i1]Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak:
Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities. CoRR abs/1102.3887 (2011) - 2010
- [c1]Brian Eriksson, Gautam Dasarathy, Paul Barford, Robert D. Nowak:
Toward the Practical Use of Network Tomography for Internet Topology Discovery. INFOCOM 2010: 1532-1540
Coauthor Index
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