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Aditya Bhaskara
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2020 – today
- 2024
- [c58]Frost Mitchell, Aditya Bhaskara, Jie Wang, Neal Patwari:
Less is More: Improved Path Loss Prediction Using Simple Interpolation Models. DySPAN 2024: 139-144 - [c57]Aarushi Sarbhai, Frost Mitchell, Sneha Kumar Kasera, Aditya Bhaskara, Jacobus E. van der Merwe, Neal Patwari:
Reactive Spectrum Sharing with Radio Dynamic Zones. DySPAN 2024: 429-438 - [c56]Frost Mitchell, Jie Wang, Aditya Bhaskara, Sneha Kumar Kasera:
Utilizing Confidence in Localization Predictions for Improved Spectrum Management. DySPAN 2024: 483-492 - [c55]Christopher Harker, Aditya Bhaskara:
Convergence Guarantees for the DeepWalk Embedding on Block Models. ICML 2024 - [c54]Aditya Bhaskara
, Eric Evert
New Tools for Smoothed Analysis: Least Singular Value Bounds for Random Matrices with Dependent Entries. STOC 2024: 375-386 - [c53]Aditya Bhaskara
Data Exchange Markets via Utility Balancing. WWW 2024: 57-65 - [i32]Aditya Bhaskara, Sreenivas Gollapudi, Sungjin Im, Kostas Kollias, Kamesh Munagala, Govind S. Sankar:
Data Exchange Markets via Utility Balancing. CoRR abs/2401.13053 (2024) - [i31]Aditya Bhaskara, Eric Evert, Vaidehi Srinivas, Aravindan Vijayaraghavan:
New Tools for Smoothed Analysis: Least Singular Value Bounds for Random Matrices with Dependent Entries. CoRR abs/2405.01517 (2024) - [i30]Aditya Bhaskara, Alex Crane, Md. Mumtahin Habib Ullah Mazumder, Blair D. Sullivan, Prasanth Yalamanchili:
Optimizing Information Access in Networks via Edge Augmentation. CoRR abs/2407.02624 (2024) - [i29]Christopher Harker, Aditya Bhaskara:
Convergence Guarantees for the DeepWalk Embedding on Block Models. CoRR abs/2410.20248 (2024) - 2023
- [c52]Christopher Harker, Aditya Bhaskara:
Structure of Nonlinear Node Embeddings in Stochastic Block Models. AISTATS 2023: 6764-6782 - [c51]Aditya Bhaskara, Kamesh Munagala:
Competing against Adaptive Strategies in Online Learning via Hints. AISTATS 2023: 10409-10424 - [c50]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Bandit Online Linear Optimization with Hints and Queries. ICML 2023: 2313-2336 - [c49]Aditya Bhaskara, Sreenivas Gollapudi, Sungjin Im, Kostas Kollias, Kamesh Munagala
Online Learning and Bandits with Queried Hints. ITCS 2023: 16:1-16:24 - [c48]Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian:
Tight Bounds for Volumetric Spanners and Applications. NeurIPS 2023 - [c47]Mary W. Hall
An NSF REU Site Based on Trust and Reproducibility of Intelligent Computation: Experience Report. SC Workshops 2023: 343-349 - [c46]Frost Mitchell, Neal Patwari, Aditya Bhaskara, Sneha Kumar Kasera:
Learning-based Techniques for Transmitter Localization: A Case Study on Model Robustness. SECON 2023: 133-141 - [c45]Frost Mitchell
Exploring Adversarial Attacks on Learning-based Localization. WiseML@WiSec 2023: 15-20 - [i28]Harvey Dam, Vinu Joseph, Aditya Bhaskara, Ganesh Gopalakrishnan, Saurav Muralidharan, Michael Garland:
Understanding the Effect of the Long Tail on Neural Network Compression. CoRR abs/2306.06238 (2023) - [i27]Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian:
Tight Bounds for Volumetric Spanners and Applications. CoRR abs/2310.00175 (2023) - [i26]Benwei Shi, Aditya Bhaskara, Wai Ming Tai, Jeff M. Phillips:
On Mergable Coresets for Polytope Distance. CoRR abs/2311.05651 (2023) - 2022
- [j5]Aditya Bhaskara, Aidao Chen, Aidan Perreault, Aravindan Vijayaraghavan
Smoothed analysis for tensor methods in unsupervised learning. Math. Program. 193(2): 549-599 (2022) - [c44]Frost Mitchell, Aniqua Baset, Neal Patwari, Sneha Kumar Kasera, Aditya Bhaskara:
Deep Learning-based Localization in Limited Data Regimes. WiseML@WiSec 2022: 15-20 - [i25]Aditya Bhaskara, Sreenivas Gollapudi, Sungjin Im, Kostas Kollias, Kamesh Munagala:
Online Learning and Bandits with Queried Hints. CoRR abs/2211.02703 (2022) - 2021
- [c43]Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena:
Principal Component Regression with Semirandom Observations via Matrix Completion. AISTATS 2021: 2665-2673 - [c42]Aditya Bhaskara, Ashok Cutkosky
Power of Hints for Online Learning with Movement Costs. AISTATS 2021: 2818-2826 - [c41]Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian
Fair Clustering via Equitable Group Representations. FAccT 2021: 504-514 - [c40]Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena:
Additive Error Guarantees for Weighted Low Rank Approximation. ICML 2021: 874-883 - [c39]Aditya Bhaskara, Ashok Cutkosky
Logarithmic Regret from Sublinear Hints. NeurIPS 2021: 28222-28232 - [i24]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Logarithmic Regret from Sublinear Hints. CoRR abs/2111.05257 (2021) - 2020
- [c38]Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana:
Robust Algorithms for Online k-means Clustering. ALT 2020: 148-173 - [c37]Aditya Bhaskara, Ashok Cutkosky
Online Learning with Imperfect Hints. ICML 2020: 822-831 - [c36]Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Residual Based Sampling for Online Low Rank Approximation. ITA 2020: 1-19 - [c35]Aditya Bhaskara, Ashok Cutkosky
Online Linear Optimization with Many Hints. NeurIPS 2020 - [c34]Aditya Bhaskara, Sreenivas Gollapudi, Kostas Kollias, Kamesh Munagala:
Adaptive Probing Policies for Shortest Path Routing. NeurIPS 2020 - [c33]Aditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam:
Online MAP Inference of Determinantal Point Processes. NeurIPS 2020 - [c32]Vinu Joseph, Nithin Chalapathi, Aditya Bhaskara, Ganesh Gopalakrishnan, Pavel Panchekha, Mu Zhang
Correctness-preserving Compression of Datasets and Neural Network Models. CORRECTNESS@SC 2020: 1-9 - [c31]Pruthuvi Maheshakya Wijewardena, Aditya Bhaskara, Sneha Kumar Kasera, Syed Ayaz Mahmud, Neal Patwari:
A plug-n-play game theoretic framework for defending against radio window attacks. WISEC 2020: 284-294 - [i23]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Learning with Imperfect Hints. CoRR abs/2002.04726 (2020) - [i22]Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian:
Fair clustering via equitable group representations. CoRR abs/2006.11009 (2020) - [i21]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Linear Optimization with Many Hints. CoRR abs/2010.03082 (2020) - [i20]Vinu Joseph, Shoaib Ahmed Siddiqui, Aditya Bhaskara, Ganesh Gopalakrishnan, Saurav Muralidharan, Michael Garland, Sheraz Ahmed, Andreas Dengel:
Reliable Model Compression via Label-Preservation-Aware Loss Functions. CoRR abs/2012.01604 (2020)
2010 – 2019
- 2019
- [j4]Aditya Bhaskara, Antoine Vigneron:
Approximating a planar convex set using a sparse grid. Inf. Process. Lett. 149: 10-13 (2019) - [c30]Aditya Bhaskara, Wai Ming Tai:
Approximate Guarantees for Dictionary Learning. COLT 2019: 299-317 - [c29]Aditya Bhaskara, Aidao Chen, Aidan Perreault, Aravindan Vijayaraghavan:
Smoothed Analysis in Unsupervised Learning via Decoupling. FOCS 2019: 582-610 - [c28]Aditya Bhaskara, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Residual Based Sampling for Online Low Rank Approximation. FOCS 2019: 1596-1614 - [c27]Aniqua Baset, Christopher Becker, Kurt Derr, Samuel Ramirez, Sneha Kumar Kasera, Aditya Bhaskara:
Towards Wireless Environment Cognizance Through Incremental Learning. MASS 2019: 256-264 - [c26]Aditya Bhaskara, Maheshakya Wijewardena:
On Distributed Averaging for Stochastic k-PCA. NeurIPS 2019: 11024-11033 - [c25]Aditya Bhaskara, Sharvaree Vadgama, Hong Xu:
Greedy Sampling for Approximate Clustering in the Presence of Outliers. NeurIPS 2019: 11146-11155 - [i19]Aditya Bhaskara, Wai Ming Tai:
Approximate Guarantees for Dictionary Learning. CoRR abs/1905.12091 (2019) - 2018
- [c24]Aditya Bhaskara, Srivatsan Kumar:
Low Rank Approximation in the Presence of Outliers. APPROX-RANDOM 2018: 4:1-4:16 - [c23]Aditya Bhaskara, Samira Daruki, Suresh Venkatasubramanian
Sublinear Algorithms for MAXCUT and Correlation Clustering. ICALP 2018: 16:1-16:14 - [c22]Aditya Bhaskara, Maheshakya Wijewardena:
Distributed Clustering via LSH Based Data Partitioning. ICML 2018: 569-578 - [c21]Aditya Bhaskara, Silvio Lattanzi:
Non-Negative Sparse Regression and Column Subset Selection with L1 Error. ITCS 2018: 7:1-7:15 - [c20]Anuj Dimri
Privacy Enabled Noise Free Data Collection in Vehicular Networks. MASS 2018: 1-9 - [c19]Harsimran Singh, Shamik Sarkar, Anuj Dimri
Privacy Enabled Crowdsourced Transmitter Localization Using Adjusted Measurements. PAC 2018: 95-106 - [i18]Aditya Bhaskara, Samira Daruki, Suresh Venkatasubramanian:
Sublinear Algorithms for MAXCUT and Correlation Clustering. CoRR abs/1802.06992 (2018) - [i17]Aditya Bhaskara, Srivatsan Kumar:
Low Rank Approximation in the Presence of Outliers. CoRR abs/1804.10696 (2018) - [i16]Aditya Bhaskara, Aidao Chen, Aidan Perreault, Aravindan Vijayaraghavan:
Smoothed Analysis in Unsupervised Learning via Decoupling. CoRR abs/1811.12361 (2018) - 2017
- [j3]Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang:
On Binary Embedding using Circulant Matrices. J. Mach. Learn. Res. 18: 150:1-150:30 (2017) - 2016
- [c18]Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam:
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. ICML 2016: 2539-2548 - [c17]Aditya Bhaskara, Mehrdad Ghadiri, Vahab S. Mirrokni, Ola Svensson:
Linear Relaxations for Finding Diverse Elements in Metric Spaces. NIPS 2016: 4098-4106 - [c16]Zeyuan Allen Zhu, Aditya Bhaskara, Silvio Lattanzi, Vahab S. Mirrokni, Lorenzo Orecchia:
Expanders via Local Edge Flips. SODA 2016: 259-269 - [i15]Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam:
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. CoRR abs/1605.08795 (2016) - 2015
- [j2]Hyung-Chan An, Aditya Bhaskara, Chandra Chekuri, Shalmoli Gupta, Vivek Madan, Ola Svensson:
Centrality of trees for capacitated k-center. Math. Program. 154(1-2): 29-53 (2015) - [c15]Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam:
Sparse Solutions to Nonnegative Linear Systems and Applications. AISTATS 2015 - [c14]Zeinab Abbassi, Aditya Bhaskara, Vishal Misra:
Optimizing Display Advertising in Online Social Networks. WWW 2015: 1-11 - [i14]Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam:
Sparse Solutions to Nonnegative Linear Systems and Applications. CoRR abs/1501.01689 (2015) - [i13]Zeyuan Allen Zhu, Aditya Bhaskara, Silvio Lattanzi, Vahab S. Mirrokni, Lorenzo Orecchia:
Expanders via Local Edge Flips. CoRR abs/1510.07768 (2015) - [i12]Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang:
On Binary Embedding using Circulant Matrices. CoRR abs/1511.06480 (2015) - 2014
- [c13]Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan:
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability. COLT 2014: 742-778 - [c12]Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan:
Open Problem: Tensor Decompositions: Algorithms up to the Uniqueness Threshold? COLT 2014: 1280-1282 - [c11]Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma:
Provable Bounds for Learning Some Deep Representations. ICML 2014: 584-592 - [c10]Hyung-Chan An, Aditya Bhaskara, Chandra Chekuri, Shalmoli Gupta, Vivek Madan, Ola Svensson:
Centrality of Trees for Capacitated k-Center. IPCO 2014: 52-63 - [c9]MohammadHossein Bateni, Aditya Bhaskara, Silvio Lattanzi, Vahab S. Mirrokni:
Distributed Balanced Clustering via Mapping Coresets. NIPS 2014: 2591-2599 - [c8]Aditya Bhaskara, Moses Charikar
Smoothed analysis of tensor decompositions. STOC 2014: 594-603 - [i11]Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma:
More Algorithms for Provable Dictionary Learning. CoRR abs/1401.0579 (2014) - 2013
- [j1]Aditya Bhaskara, Devendra Desai, Srikanth Srinivasan
Optimal Hitting Sets for Combinatorial Shapes. Theory Comput. 9: 441-470 (2013) - [c7]Aditya Bhaskara, Ravishankar Krishnaswamy, Kunal Talwar, Udi Wieder:
Minimum Makespan Scheduling with Low Rank Processing Times. SODA 2013: 937-947 - [i10]Hyung-Chan An, Aditya Bhaskara, Ola Svensson:
Centrality of Trees for Capacitated k-Center. CoRR abs/1304.2983 (2013) - [i9]Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan:
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability. CoRR abs/1304.8087 (2013) - [i8]Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma:
Provable Bounds for Learning Some Deep Representations. CoRR abs/1310.6343 (2013) - [i7]Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan:
Smoothed Analysis of Tensor Decompositions. CoRR abs/1311.3651 (2013) - 2012
- [b1]Aditya Bhaskara:
Finding Dense Structures in Graphs and Matrices. Princeton University, USA, 2012 - [c6]Aditya Bhaskara, Devendra Desai, Srikanth Srinivasan:
Optimal Hitting Sets for Combinatorial Shapes. APPROX-RANDOM 2012: 423-434 - [c5]Aditya Bhaskara, Moses Charikar
On Quadratic Programming with a Ratio Objective. ICALP (1) 2012: 109-120 - [c4]Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan, Venkatesan Guruswami, Yuan Zhou
Polynomial integrality gaps for strong SDP relaxations of Densest k-subgraph. SODA 2012: 388-405 - [c3]Aditya Bhaskara, Daniel Dadush
Unconditional differentially private mechanisms for linear queries. STOC 2012: 1269-1284 - [i6]Aditya Bhaskara, Devendra Desai, Srikanth Srinivasan:
Optimal Hitting Sets for Combinatorial Shapes. CoRR abs/1211.3439 (2012) - [i5]Aditya Bhaskara, Devendra Desai, Srikanth Srinivasan:
Optimal Hitting Sets for Combinatorial Shapes. Electron. Colloquium Comput. Complex. TR12 (2012) - 2011
- [c2]Aditya Bhaskara, Aravindan Vijayaraghavan:
Approximating Matrix p-norms. SODA 2011: 497-511 - [i4]Aditya Bhaskara, Moses Charikar, Rajsekar Manokaran, Aravindan Vijayaraghavan:
On Quadratic Programming with a Ratio Objective. CoRR abs/1101.1710 (2011) - [i3]Aditya Bhaskara, Moses Charikar, Venkatesan Guruswami, Aravindan Vijayaraghavan, Yuan Zhou:
Polynomial integrality gaps for strong SDP relaxations of Densest k-subgraph. CoRR abs/1110.1360 (2011) - 2010
- [c1]Aditya Bhaskara, Moses Charikar
Detecting high log-densities: an O(n1/4) approximation for densest k-subgraph. STOC 2010: 201-210 - [i2]Aditya Bhaskara, Aravindan Vijayaraghavan:
Computing the Matrix p-norm. CoRR abs/1001.2613 (2010) - [i1]Aditya Bhaskara, Moses Charikar, Eden Chlamtac, Uriel Feige, Aravindan Vijayaraghavan:
Detecting High Log-Densities -- an O(n^1/4) Approximation for Densest k-Subgraph. CoRR abs/1001.2891 (2010)
Coauthor Index
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last updated on 2024-12-10 21:43 CET by the dblp team
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