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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 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, Vaidehi Srinivas, Aravindan Vijayaraghavan:
New Tools for Smoothed Analysis: Least Singular Value Bounds for Random Matrices with Dependent Entries. STOC 2024: 375-386 - [c53]Aditya Bhaskara, Sreenivas Gollapudi, Sungjin Im, Kostas Kollias, Kamesh Munagala, Govind S. Sankar:
Data Exchange Markets via Utility Balancing. WWW 2024: 57-65 - [i31]Aditya Bhaskara, Sreenivas Gollapudi, Sungjin Im, Kostas Kollias, Kamesh Munagala, Govind S. Sankar:
Data Exchange Markets via Utility Balancing. CoRR abs/2401.13053 (2024) - [i30]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) - [i29]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) - 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, Ganesh Gopalakrishnan, Eric Eide, Johanna Cohoon, Jeff M. Phillips, Mu Zhang, Shireen Y. Elhabian, Aditya Bhaskara, Harvey Dam, Artem Yadrov, Tushar Kataria, Amir Mohammad Tavakkoli, Sameeran Joshi, Mokshagna Sai Teja Karanam:
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, Phillip Smith, Aditya Bhaskara, Sneha Kumar Kasera:
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, Ravi Kumar, Manish Purohit:
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, Ravi Kumar, Manish Purohit:
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, Ravi Kumar, Manish Purohit:
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, Ravi Kumar, Manish Purohit:
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, Harsimran Singh, Shamik Sarkar, Sneha Kumar Kasera, Neal Patwari, Aditya Bhaskara, Kurt Derr, Samuel Ramirez:
Privacy Enabled Noise Free Data Collection in Vehicular Networks. MASS 2018: 1-9 - [c19]Harsimran Singh, Shamik Sarkar, Anuj Dimri, Aditya Bhaskara, Neal Patwari, Sneha Kumar Kasera, Samuel Ramirez, Kurt Derr:
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, Ankur Moitra, Aravindan Vijayaraghavan:
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, Rajsekar Manokaran, Aravindan Vijayaraghavan:
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, Ravishankar Krishnaswamy, Kunal Talwar:
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, Eden Chlamtac, Uriel Feige, Aravindan Vijayaraghavan:
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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