Arnab Bhattacharyya

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 90

Top Venues

CoRR

Electron. Colloquium Comput. Complex.

AISTATS

NeurIPS

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Davin Choo, Joy Qiping Yang, Arnab Bhattacharyya, Clément L. Canonne
Learning bounded-degree polytrees with known skeleton. ALT (2024)
Yuhao Wang, Ming Gao, Wai Ming Tai, Bryon Aragam, Arnab Bhattacharyya
Optimal estimation of Gaussian (poly)trees. CoRR (2024)
Arnab Bhattacharyya, Davin Choo, Sutanu Gayen, Dimitrios Myrisiotis
Learnability of Parameter-Bounded Bayes Nets. CoRR (2024)
Davin Choo, Themis Gouleakis, Chun Kai Ling, Arnab Bhattacharyya
Online bipartite matching with imperfect advice. CoRR (2024)
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran
Total Variation Distance for Product Distributions is #P-Complete. CoRR (2024)
Yuhao Wang, Ming Gao, Wai Ming Tai, Bryon Aragam, Arnab Bhattacharyya
Optimal estimation of Gaussian (poly)trees. AISTATS (2024)
Vipul Arora, Arnab Bhattacharyya, Mathews Boban, Venkatesan Guruswami, Esty Kelman
Outlier Robust Multivariate Polynomial Regression. CoRR (2024)
Arnab Bhattacharyya, Sutanu Gayen, Philips George John, Sayantan Sen, N. V. Vinodchandran
Distribution Learning Meets Graph Structure Sampling. CoRR (2024)
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran
On Approximating Total Variation Distance. IJCAI (2023)
Aduri Pavan, Kuldeep S. Meel, N. V. Vinodchandran, Arnab Bhattacharyya
Constraint Optimization over Semirings. CoRR (2023)
Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf
On the Interventional Kullback-Leibler Divergence. CLeaR (2023)
Arnab Bhattacharyya, Sutanu Gayen, Eric Price, Vincent Y. F. Tan, N. V. Vinodchandran
Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu. SIAM J. Comput. 52 (3) (2023)
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran
Total Variation Distance Estimation Is as Easy as Probabilistic Inference. CoRR (2023)
A. Pavan, N. V. Vinodchandran, Arnab Bhattacharyya, Kuldeep S. Meel
Model Counting Meets Distinct Elements. Commun. ACM 66 (9) (2023)
Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects. CoRR (2023)
Vipul Arora, Arnab Bhattacharyya, Noah Fleming, Esty Kelman, Yuichi Yoshida
Low Degree Testing over the Reals. SODA (2023)
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran
Total Variation Distance Estimation Is as Easy as Probabilistic Inference. Electron. Colloquium Comput. Complex. (2023)
Vipul Arora, Arnab Bhattacharyya, Clément L. Canonne, Joy Qiping Yang
Near-Optimal Degree Testing for Bayes Nets. ISIT (2023)
A. Pavan, N. Variyam Vinodchandran, Arnab Bhattacharyya, Kuldeep S. Meel
Estimation. ACM Trans. Database Syst. 48 (3) (2023)
Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun
Sample Complexity of Distinguishing Cause from Effect. AISTATS (2023)
Davin Choo, Themistoklis Gouleakis, Arnab Bhattacharyya
Active causal structure learning with advice. ICML (2023)
Aduri Pavan, Kuldeep S. Meel, N. V. Vinodchandran, Arnab Bhattacharyya
Constraint Optimization over Semirings. AAAI (2023)
Davin Choo, Themis Gouleakis, Arnab Bhattacharyya
Active causal structure learning with advice. CoRR (2023)
Vipul Arora, Arnab Bhattacharyya, Clément L. Canonne, Joy Qiping Yang
Near-Optimal Degree Testing for Bayes Nets. CoRR (2023)
Davin Choo, Joy Qiping Yang, Arnab Bhattacharyya, Clément L. Canonne
Learning bounded-degree polytrees with known skeleton. CoRR (2023)
Jonas Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf
On the Interventional Kullback-Leibler Divergence. CoRR (2023)
Vipul Arora, Arnab Bhattacharyya, Noah Fleming, Esty Kelman, Yuichi Yoshida
Low Degree Testing over the Reals. CoRR (2022)
A. Pavan, N. V. Vinodchandran, Arnab Bhattacharyya, Kuldeep S. Meel
Model Counting Meets Distinct Elements in a Data Stream. SIGMOD Rec. 51 (1) (2022)
Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects. NeurIPS (2022)
Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang
Learning Sparse Fixed-Structure Gaussian Bayesian Networks. AISTATS (2022)
Yuhao Wang, Arnab Bhattacharyya
Identifiability of Linear AMP Chain Graph Models. AAAI (2022)
Sidhant Bansal, Arnab Bhattacharyya, Anamay Chaturvedi, Jonathan Scarlett
Universal 1-Bit Compressive Sensing for Bounded Dynamic Range Signals. ISIT (2022)
Arnab Bhattacharyya, Clément L. Canonne, Joy Qiping Yang
Independence Testing for Bounded Degree Bayesian Network. CoRR (2022)
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, Aduri Pavan, N. V. Vinodchandran
On Approximating Total Variation Distance. CoRR (2022)
Arnab Bhattacharyya, Clément L. Canonne, Joy Qiping Yang
Independence Testing for Bounded Degree Bayesian Networks. NeurIPS (2022)
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Vedant Raval, N. Variyam Vinodchandran
Efficient interventional distribution learning in the PAC framework. AISTATS (2022)
Vipul Arora, Arnab Bhattacharyya, Noah Fleming, Esty Kelman, Yuichi Yoshida
Low Degree Testing over the Reals. Electron. Colloquium Comput. Complex. (2022)
Sidhant Bansal, Arnab Bhattacharyya, Anamay Chaturvedi, Jonathan Scarlett
Universal 1-Bit Compressive Sensing for Bounded Dynamic Range Signals. CoRR (2022)
Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya
Verification and search algorithms for causal DAGs. NeurIPS (2022)
Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya
Verification and search algorithms for causal DAGs. CoRR (2022)
Arnab Bhattacharyya, Édouard Bonnet, László Egri, Suprovat Ghoshal, Karthik C. S., Bingkai Lin, Pasin Manurangsi, Dániel Marx
Parameterized Intractability of Even Set and Shortest Vector Problem. J. ACM 68 (3) (2021)
Arnab Bhattacharyya, Palash Dey
Predicting winner and estimating margin of victory in elections using sampling. Artif. Intell. 296 (2021)
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Vedant Raval, N. V. Vinodchandran
Efficient inference of interventional distributions. CoRR (2021)
Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang
Learning Sparse Fixed-Structure Gaussian Bayesian Networks. CoRR (2021)
Arnab Bhattacharyya, Ashutosh Gupta, Lakshmanan Kuppusamy, Somya Mani, Ankit Shukla, Mandayam K. Srivas, Mukund Thattai
A formal methods approach to predicting new features of the eukaryotic vesicle traffic system. Acta Informatica 58 (1-2) (2021)
Yuhao Wang, Arnab Bhattacharyya
Identifiability of AMP chain graph models. CoRR (2021)
Aduri Pavan, N. V. Vinodchandran, Arnab Bhattacharyya, Kuldeep S. Meel
Model Counting meets F0 Estimation. CoRR (2021)
Arnab Bhattacharyya, Sutanu Gayen, Eric Price, N. V. Vinodchandran
Near-optimal learning of tree-structured distributions by Chow-Liu. STOC (2021)
Arnab Bhattacharyya, Rathin Desai, Sai Ganesh Nagarajan, Ioannis Panageas
Efficient Statistics for Sparse Graphical Models from Truncated Samples. AISTATS (2021)
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran
Testing Product Distributions: A Closer Look. ALT (2021)
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, N. V. Vinodchandran
Efficiently Learning and Sampling Interventional Distributions from Observations. CoRR (2020)
Arnab Bhattacharyya, Rathin Desai, Sai Ganesh Nagarajan, Ioannis Panageas
Efficient Statistics for Sparse Graphical Models from Truncated Samples. CoRR (2020)
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran
Testing Product Distributions: A Closer Look. CoRR (2020)
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, N. V. Vinodchandran
Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning. NeurIPS (2020)
Arnab Bhattacharyya, L. Sunil Chandran, Suprovat Ghoshal
Combinatorial Lower Bounds for 3-Query LDCs. ITCS (2020)
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, N. V. Vinodchandran
Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning. CoRR (2020)
Arnab Bhattacharyya, Ameet Gadekar, Ninad Rajgopal
-parities. Theor. Comput. Sci. 840 (2020)
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, N. Variyam Vinodchandran
Learning and Sampling of Atomic Interventions from Observations. ICML (2020)
Arnab Bhattacharyya, Sutanu Gayen, Eric Price, N. V. Vinodchandran
Near-Optimal Learning of Tree-Structured Distributions by Chow-Liu. CoRR (2020)
Arnab Bhattacharyya, Édouard Bonnet, László Egri, Suprovat Ghoshal, Karthik C. S., Bingkai Lin, Pasin Manurangsi, Dániel Marx
Parameterized Intractability of Even Set and Shortest Vector Problem. Electron. Colloquium Comput. Complex. 26 (2019)
Arnab Bhattacharyya, Palash Dey, David P. Woodruff
-Heavy Hitters in Insertion Streams and Related Problems. ACM Trans. Algorithms 15 (1) (2019)
Saravanan Kandasamy, Arnab Bhattacharyya, Vasant G. Honavar
Minimum Intervention Cover of a Causal Graph. AAAI (2019)
Arnab Bhattacharyya, Édouard Bonnet, László Egri, Suprovat Ghoshal, Karthik C. S., Bingkai Lin, Pasin Manurangsi, Dániel Marx
Parameterized Intractability of Even Set and Shortest Vector Problem. CoRR (2019)
Arnab Bhattacharyya, Philips George John, Suprovat Ghoshal, Raghu Meka
Average Bias and Polynomial Sources. Electron. Colloquium Comput. Complex. 26 (2019)
Arnab Bhattacharyya, L. Sunil Chandran, Suprovat Ghoshal
Combinatorial lower bounds for 3-query LDCs. CoRR (2019)
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
Learning and Testing Causal Models with Interventions. CoRR (2018)
Arnab Bhattacharyya, Ameet Gadekar, Ninad Rajgopal
Improved Learning of k-Parities. COCOON (2018)
Arnab Bhattacharyya, Fabrizio Grandoni, Aleksandar Nikolov, Barna Saha, Saket Saurabh, Aravindan Vijayaraghavan, Qin Zhang
Editorial: ACM-SIAM Symposium on Discrete Algorithms (SODA) 2016 Special Issue. ACM Trans. Algorithms 14 (3) (2018)
Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi
Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH. ICALP (2018)
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
Learning and Testing Causal Models with Interventions. NeurIPS (2018)
Siddharth Barman, Arnab Bhattacharyya, Suprovat Ghoshal
Testing Sparsity over Known and Unknown Bases. ICML (2018)
Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi
Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH. CoRR (2018)
Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi
Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH. Electron. Colloquium Comput. Complex. 25 (2018)
Arnab Bhattacharyya, Suprovat Ghoshal, Rishi Saket
Hardness of Learning Noisy Halfspaces using Polynomial Thresholds. COLT (2018)
Arnab Bhattacharyya, Sivakanth Gopi, Avishay Tal
Lower Bounds for 2-Query LCCs over Large Alphabet. APPROX-RANDOM (2017)
Arnab Bhattacharyya, Suprovat Ghoshal, Rishi Saket
Hardness of learning noisy halfspaces using polynomial thresholds. CoRR (2017)
Anurita Mathur, Arnab Bhattacharyya
On the Gap between Outcomes of Voting Rules. AAMAS (2017)
Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath
Improved bounds for universal one-bit compressive sensing. ISIT (2017)
Arnab Bhattacharyya, Sivakanth Gopi
Lower Bounds for Constant Query Affine-Invariant LCCs and LTCs. ACM Trans. Comput. Theory 9 (2) (2017)
Arnab Bhattacharyya, Suprovat Ghoshal, Rishi Saket
Hardness of learning noisy halfspaces using polynomial thresholds. Electron. Colloquium Comput. Complex. 24 (2017)
Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath
Improved Bounds for Universal One-Bit Compressive Sensing. CoRR (2017)
Siddharth Barman, Arnab Bhattacharyya, Suprovat Ghoshal
The Dictionary Testing Problem. CoRR (2016)
Arnab Bhattacharyya, Ameet Gadekar, Suprovat Ghoshal, Rishi Saket
On the Hardness of Learning Sparse Parities. ESA (2016)
Arnab Bhattacharyya, Palash Dey, David P. Woodruff
An Optimal Algorithm for l1-Heavy Hitters in Insertion Streams and Related Problems. CoRR (2016)
Arnab Bhattacharyya, Sivakanth Gopi
Lower bounds for 2-query LCCs over large alphabet. Electron. Colloquium Comput. Complex. 23 (2016)
Arnab Bhattacharyya, Abhishek Bhowmick, Chetan Gupta
On Higher-Order Fourier Analysis over Non-Prime Fields. APPROX-RANDOM (2016)
Arnab Bhattacharyya, Zeev Dvir, Shubhangi Saraf, Amir Shpilka
Tight lower bounds for linear 2-query LCCs over finite fields. Comb. 36 (1) (2016)
Arnab Bhattacharyya, Palash Dey, David P. Woodruff
An Optimal Algorithm for l1-Heavy Hitters in Insertion Streams and Related Problems. PODS (2016)
Arnab Bhattacharyya, Sivakanth Gopi
Lower bounds for 2-query LCCs over large alphabet. CoRR (2016)
Arnab Bhattacharyya, Sivakanth Gopi
Lower Bounds for Constant Query Affine-Invariant LCCs and LTCs. Computational Complexity Conference (2016)
Arnab Bhattacharyya, Ameet Gadekar, Suprovat Ghoshal, Rishi Saket
On the hardness of learning sparse parities. Electron. Colloquium Comput. Complex. 22 (2015)
Arnab Bhattacharyya, Kirankumar Shiragur
How friends and non-determinism affect opinion dynamics. CoRR (2015)
Arnab Bhattacharyya, Kirankumar Shiragur
How friends and non-determinism affect opinion dynamics. CDC (2015)
Arnab Bhattacharyya, Palash Dey
Sample Complexity for Winner Prediction in Elections. CoRR (2015)
Arnab Bhattacharyya, Palash Dey
Fishing out Winners from Vote Streams. CoRR (2015)
Arnab Bhattacharyya, Ameet Gadekar, Suprovat Ghoshal, Rishi Saket
On the hardness of learning sparse parities. CoRR (2015)
Arnab Bhattacharyya, Sivakanth Gopi
Lower bounds for constant query affine-invariant LCCs and LTCs. Electron. Colloquium Comput. Complex. 22 (2015)
Arnab Bhattacharyya, Palash Dey
Fishing out Winners from Vote Streams. Electron. Colloquium Comput. Complex. 22 (2015)
Arnab Bhattacharyya, Elena Grigorescu, Asaf Shapira
A unified framework for testing linear-invariant properties. Random Struct. Algorithms 46 (2) (2015)
Arnab Bhattacharyya, Pooya Hatami, Madhur Tulsiani
Algorithmic regularity for polynomials and applications. SODA (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Arnab Bhattacharyya