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Gautam 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
Grid Topology Identification With Hidden Nodes via Structured Norm Minimization. IEEE Control. Syst. Lett. 6: 1244-1249 (2022) - [j9]Sean O. Stalley
A Graph-Based Approach to Boundary Estimation With Mobile Sensors. IEEE Robotics Autom. Lett. 7(2): 4991-4998 (2022) - [j8]Behrouz Azimian
State and Topology Estimation for Unobservable Distribution Systems Using Deep Neural Networks. IEEE Trans. Instrum. Meas. 71: 1-14 (2022) - [j7]Tyler Sypherd
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
Digital medicine and the curse of dimensionality. npj Digit. Medicine 4 (2021) - [j5]Nathan Dunkelberger
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
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
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
Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. 66: 151-196 (2019) - [c20]Indu Manickam, Andrew S. Lan, Gautam Dasarathy
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
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
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. CoRR abs/1806.04310 (2018) - 2017
- [c13]Gautam Dasarathy
Sketched covariance testing: A compression-statistics tradeoff. ACSSC 2017: 676-680 - [c12]Ali Mousavi, Gautam Dasarathy
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
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
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
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
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
Efficient Network Tomography for Internet Topology Discovery. IEEE/ACM Trans. Netw. 20(3): 931-943 (2012) - [c4]Gautam Dasarathy
Covariance sketching. Allerton Conference 2012: 1026-1033 - 2011
- [c3]Gautam Dasarathy
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
Toward the Practical Use of Network Tomography for Internet Topology Discovery. INFOCOM 2010: 1532-1540
Coauthor Index
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last updated on 2024-08-10 01:22 CEST by the dblp team
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