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ORCIDDevavrat Shah
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- affiliation: MIT, Cambridge, USA
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2020 – today
- 2024
[j69]Ali Jadbabaie
, Anuran Makur, Devavrat Shah:
Estimation of Skill Distributions. IEEE Trans. Inf. Theory 70(9): 6447-6480 (2024)- [j68]Arnab Sarker, Ali Jadbabaie, Devavrat Shah:
Unifying Epidemic Models With Mixtures. IEEE Trans. Signal Inf. Process. over Networks 10: 239-252 (2024) - [i94]Rohan Alur, Manish Raghavan, Devavrat Shah:
Distinguishing the Indistinguishable: Human Expertise in Algorithmic Prediction. CoRR abs/2402.00793 (2024) - [i93]Jessy Xinyi Han, Andrew Miller, S. Craig Watkins, Christopher Winship, Fotini Christia, Devavrat Shah:
A Causal Framework to Evaluate Racial Bias in Law Enforcement Systems. CoRR abs/2402.14959 (2024) - [i92]Jia Wan, Sean R. Sinclair, Devavrat Shah, Martin J. Wainwright:
Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning. CoRR abs/2409.14557 (2024) - 2023
- [j67]Devavrat Shah, Christina Lee Yu:
Robust Max Entrywise Error Bounds for Tensor Estimation From Sparse Observations via Similarity-Based Collaborative Filtering. IEEE Trans. Inf. Theory 69(5): 3121-3149 (2023) - [j66]Ali Jadbabaie, Anuran Makur, Devavrat Shah:
Federated Optimization of Smooth Loss Functions. IEEE Trans. Inf. Theory 69(12): 7836-7866 (2023) - [c156]Romain Cosson, Ali Jadbabaie, Anuran Makur, Amirhossein Reisizadeh, Devavrat Shah:
Gradient Descent with Low-Rank Objective Functions. CDC 2023: 3309-3314 - [c155]Anish Agarwal, Munther A. Dahleh, Devavrat Shah, Dennis Shen:
Causal Matrix Completion. COLT 2023: 3821-3826 - [c154]Arash Nasr-Esfahany, Mohammad Alizadeh, Devavrat Shah:
Counterfactual Identifiability of Bijective Causal Models. ICML 2023: 25733-25754 - [c153]Cindy Y. Zhang, Sarah Huiyi Cen, Devavrat Shah:
Matrix Estimation for Individual Fairness. ICML 2023: 40871-40887 - [c152]Abdullah Alomar, Munther A. Dahleh, Sean Mann, Devavrat Shah:
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise. NeurIPS 2023 - [c151]Rohan Alur, Loren Laine, Darrick K. Li, Manish Raghavan, Devavrat Shah, Dennis L. Shung:
Auditing for Human Expertise. NeurIPS 2023 - [c150]Abdullah Alomar, Pouya Hamadanian, Arash Nasr-Esfahany, Anish Agarwal, Mohammad Alizadeh, Devavrat Shah:
CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation. NSDI 2023: 1115-1147 - [i91]Cindy Y. Zhang, Sarah Huiyi Cen, Devavrat Shah:
Matrix Estimation for Individual Fairness. CoRR abs/2302.02096 (2023) - [i90]Arash Nasr-Esfahany, Mohammad Alizadeh, Devavrat Shah:
Counterfactual Identifiability of Bijective Causal Models. CoRR abs/2302.02228 (2023) - [i89]Sarah H. Cen, Aleksander Madry, Devavrat Shah:
A User-Driven Framework for Regulating and Auditing Social Media. CoRR abs/2304.10525 (2023) - [i88]Abdullah Alomar, Munther A. Dahleh, Sean Mann, Devavrat Shah:
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise. CoRR abs/2305.16491 (2023) - [i87]Rohan Alur, Loren Laine, Darrick K. Li, Manish Raghavan, Devavrat Shah, Dennis L. Shung:
Auditing for Human Expertise. CoRR abs/2306.01646 (2023) - [i86]Sean Mann, Charlotte Park, Devavrat Shah:
Exploiting Observation Bias to Improve Matrix Completion. CoRR abs/2306.04775 (2023) - [i85]Abhin Shah, Devavrat Shah, Gregory W. Wornell:
On Computationally Efficient Learning of Exponential Family Distributions. CoRR abs/2309.06413 (2023) - [i84]Bowen Song, Marco Paolieri, Harper E. Stewart, Leana Golubchik, Jill L. McNitt-Gray, Vishal Misra, Devavrat Shah:
Predicting Ground Reaction Force from Inertial Sensors. CoRR abs/2311.02287 (2023) - 2022
- [j65]Christian Borgs, Jennifer T. Chayes, Devavrat Shah, Christina Lee Yu:
Iterative Collaborative Filtering for Sparse Matrix Estimation. Oper. Res. 70(6): 3143-3175 (2022) - [j64]Devavrat Shah, Qiaomin Xie, Zhi Xu:
Nonasymptotic Analysis of Monte Carlo Tree Search. Oper. Res. 70(6): 3234-3260 (2022) - [j63]Lavanya Marla, Lav R. Varshney, Devavrat Shah, Nirmal A. Prakash, Michael E. Gale:
Short and Wide Network Paths. IEEE Trans. Netw. Sci. Eng. 9(2): 524-537 (2022) - [c149]Sarah Huiyi Cen, Devavrat Shah:
Regret, stability & fairness in matching markets with bandit learners. AISTATS 2022: 8938-8968 - [c148]Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, Caroline Uhler:
Causal Imputation via Synthetic Interventions. CLeaR 2022: 688-711 - [c147]Horia Mania, Ali Jadbabaie, Devavrat Shah, Suvrit Sra:
Time Varying Regression with Hidden Linear Dynamics. L4DC 2022: 858-869 - [c146]Anish Agarwal, Abdullah Alomar, Devavrat Shah:
On Multivariate Singular Spectrum Analysis and Its Variants. SIGMETRICS (Abstracts) 2022: 79-80 - [i83]Abdullah Alomar, Pouya Hamadanian, Arash Nasr-Esfahany, Anish Agarwal, Mohammad Alizadeh, Devavrat Shah:
CausalSim: Toward a Causal Data-Driven Simulator for Network Protocols. CoRR abs/2201.01811 (2022) - [i82]Ali Jadbabaie, Anuran Makur, Devavrat Shah:
Federated Optimization of Smooth Loss Functions. CoRR abs/2201.01954 (2022) - [i81]Arnab Sarker, Ali Jadbabaie, Devavrat Shah:
Unifying Epidemic Models with Mixtures. CoRR abs/2201.04960 (2022) - [i80]Raaz Dwivedi, Susan A. Murphy, Devavrat Shah:
Counterfactual inference for sequential experimental design. CoRR abs/2202.06891 (2022) - [i79]Ali Jadbabaie, Arnab Sarker, Devavrat Shah:
Current Implicit Policies May Not Eradicate COVID-19. CoRR abs/2203.15916 (2022) - [i78]Romain Cosson, Ali Jadbabaie, Anuran Makur, Amirhossein Reisizadeh, Devavrat Shah:
Gradient Descent for Low-Rank Functions. CoRR abs/2206.08257 (2022) - [i77]Anish Agarwal, Sarah H. Cen, Devavrat Shah, Christina Lee Yu:
Network Synthetic Interventions: A Framework for Panel Data with Network Interference. CoRR abs/2210.11355 (2022) - [i76]Abhin Shah, Raaz Dwivedi, Devavrat Shah, Gregory W. Wornell:
On counterfactual inference with unobserved confounding. CoRR abs/2211.08209 (2022) - [i75]Raaz Dwivedi, Katherine Tian, Sabina Tomkins, Predrag V. Klasnja, Susan A. Murphy, Devavrat Shah:
Doubly robust nearest neighbors in factor models. CoRR abs/2211.14297 (2022) - 2021
- [j62]Vincent D. Blondel, Kyomin Jung, Pushmeet Kohli, Devavrat Shah, Seungpil Won:
Partition-Merge: Distributed Inference and Modularity Optimization. IEEE Access 9: 54032-54055 (2021) - [c145]Abhin Shah, Devavrat Shah, Gregory W. Wornell:
On Learning Continuous Pairwise Markov Random Fields. AISTATS 2021: 1153-1161 - [c144]Romain Cosson, Devavrat Shah:
Quantifying Variational Approximation for Log-Partition Function. COLT 2021: 1330-1357 - [c143]Bader Alaskar, Abdullah Alhadlaq, Meshal Alharbi, Saud Alghumayjan, Ahmad Alabdulkareem, Mansour Alsaleh, Devavrat Shah:
Next-day Electricity Demand Forecast: A New Ensemble Recommendation System Using Peak and Valley. ISGT 2021: 1-5 - [c142]Meshal Alharbi, Saud Alghumayjan, Mansour Alsaleh, Devavrat Shah, Ahmad Alabdulkareem:
Electricity Non-Technical Loss Detection: Enhanced Cost-Driven Approach Utilizing Synthetic Control. ISGT 2021: 1-5 - [c141]Sarah Huiyi Cen, Devavrat Shah:
Regulating algorithmic filtering on social media. NeurIPS 2021: 6997-7011 - [c140]Abhin Shah, Devavrat Shah, Gregory W. Wornell:
A Computationally Efficient Method for Learning Exponential Family Distributions. NeurIPS 2021: 15841-15854 - [c139]Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang:
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators. NeurIPS 2021: 18564-18576 - [c138]Arwa Alanqary, Abdullah Alomar, Devavrat Shah:
Change Point Detection via Multivariate Singular Spectrum Analysis. NeurIPS 2021: 23218-23230 - [c137]Michael Fleder, Devavrat Shah:
I Know What You Bought At Chipotle for $9.81 by Solving A Linear Inverse Problem. SIGMETRICS (Abstracts) 2021: 59-60 - [i74]Sarah Huiyi Cen, Devavrat Shah:
Regret, stability, and fairness in matching markets with bandit learners. CoRR abs/2102.06246 (2021) - [i73]Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang:
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators. CoRR abs/2102.06961 (2021) - [i72]Romain Cosson, Devavrat Shah:
Approximating the Log-Partition Function. CoRR abs/2102.10196 (2021) - [i71]Anish Agarwal, Munther A. Dahleh, Devavrat Shah, Dennis Shen:
Causal Matrix Completion. CoRR abs/2109.15154 (2021) - [i70]Abhin Shah, Devavrat Shah, Gregory W. Wornell:
A Computationally Efficient Method for Learning Exponential Family Distributions. CoRR abs/2110.15397 (2021) - 2020
- [j61]Devavrat Shah, Guy Bresler, John C. Duchi, Po-Ling Loh, Yihong Wu, Christina Lee Yu:
Editorial. IEEE J. Sel. Areas Inf. Theory 1(3): 612 (2020) - [j60]Michael Fleder, Devavrat Shah:
I Know What You Bought At Chipotle for $9.81 by Solving A Linear Inverse Problem. Proc. ACM Meas. Anal. Comput. Syst. 4(3): 47:1-47:17 (2020) - [j59]Yihua Li, Devavrat Shah, Dogyoon Song, Christina Lee Yu:
Nearest Neighbors for Matrix Estimation Interpreted as Blind Regression for Latent Variable Model. IEEE Trans. Inf. Theory 66(3): 1760-1784 (2020) - [j58]Asuman E. Ozdaglar, Devavrat Shah, Christina Lee Yu:
Asynchronous Approximation of a Single Component of the Solution to a Linear System. IEEE Trans. Netw. Sci. Eng. 7(3): 975-986 (2020) - [c136]Devavrat Shah, Varun Somani, Qiaomin Xie, Zhi Xu:
On Reinforcement Learning for Turn-based Zero-sum Markov Games. FODS 2020: 139-148 - [c135]Devavrat Shah, Qiaomin Xie, Zhi Xu:
Stable Reinforcement Learning with Unbounded State Space. L4DC 2020: 581 - [c134]Anish Agarwal, Abdullah Alomar, Devavrat Shah:
tspDB: Time Series Predict DB. NeurIPS (Competition and Demos) 2020: 27-56 - [c133]Ali Jadbabaie, Anuran Makur, Devavrat Shah:
Estimation of Skill Distribution from a Tournament. NeurIPS 2020 - [c132]Devavrat Shah, Dogyoon Song, Zhi Xu, Yuzhe Yang:
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation. NeurIPS 2020 - [c131]Michael Fleder, Devavrat Shah:
Forecasting with Alternative Data. SIGMETRICS (Abstracts) 2020: 23-24 - [c130]Devavrat Shah, Qiaomin Xie, Zhi Xu:
Non-Asymptotic Analysis of Monte Carlo Tree Search. SIGMETRICS (Abstracts) 2020: 31-32 - [i69]Devavrat Shah, Varun Somani, Qiaomin Xie, Zhi Xu:
On Reinforcement Learning for Turn-based Zero-sum Markov Games. CoRR abs/2002.10620 (2020) - [i68]Anish Agarwal, Abdullah Alomar, Arnab Sarker, Devavrat Shah, Dennis Shen, Cindy Yang:
Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave? CoRR abs/2005.00072 (2020) - [i67]Devavrat Shah, Qiaomin Xie, Zhi Xu:
Stable Reinforcement Learning with Unbounded State Space. CoRR abs/2006.04353 (2020) - [i66]Devavrat Shah, Dogyoon Song, Zhi Xu, Yuzhe Yang:
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation. CoRR abs/2006.06135 (2020) - [i65]Anish Agarwal, Abdullah Alomar, Romain Cosson, Devavrat Shah, Dennis Shen:
Synthetic Interventions. CoRR abs/2006.07691 (2020) - [i64]Ali Jadbabaie, Anuran Makur, Devavrat Shah:
Estimation of Skill Distributions. CoRR abs/2006.08189 (2020) - [i63]Sarah Huiyi Cen, Devavrat Shah:
Regulating algorithmic filtering on social media. CoRR abs/2006.09647 (2020) - [i62]Anish Agarwal, Abdullah Alomar, Devavrat Shah:
On Multivariate Singular Spectrum Analysis. CoRR abs/2006.13448 (2020) - [i61]Anish Agarwal, Devavrat Shah, Dennis Shen:
On Principal Component Regression in a High-Dimensional Error-in-Variables Setting. CoRR abs/2010.14449 (2020) - [i60]Abhin Shah, Devavrat Shah, Gregory W. Wornell:
On Learning Continuous Pairwise Markov Random Fields. CoRR abs/2010.15031 (2020) - [i59]Ali Jadbabaie, Anuran Makur, Devavrat Shah:
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression. CoRR abs/2011.02522 (2020)
2010 – 2019
- 2019
- [j57]Kyomin Jung, Yingdong Lu, Devavrat Shah, Mayank Sharma, Mark S. Squillante:
Revisiting Stochastic Loss Networks: Structures and Approximations. Math. Oper. Res. 44(3): 890-918 (2019) - [j56]Muhammad J. Amjad, Vishal Misra, Devavrat Shah, Dennis Shen:
mRSC: Multi-dimensional Robust Synthetic Control. Proc. ACM Meas. Anal. Comput. Syst. 3(2): 37:1-37:27 (2019) - [j55]Michael Fleder, Devavrat Shah:
Forecasting with Alternative Data. Proc. ACM Meas. Anal. Comput. Syst. 3(3): 46:1-46:29 (2019) - [c129]Devavrat Shah, Christina Lee Yu:
Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation. Allerton 2019: 904-909 - [c128]Devavrat Shah, Christina Lee Yu:
Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation. ISIT 2019: 41-45 - [c127]Linqi Song, Christina Fragouli, Devavrat Shah:
Interactions Between Learning and Broadcasting in Wireless Recommendation Systems. ISIT 2019: 2549-2553 - [c126]Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song:
On Robustness of Principal Component Regression. NeurIPS 2019: 9889-9900 - [c125]Muhammad Jehangir Amjad, Vishal Misra, Devavrat Shah, Dennis Shen:
mRSC: Multidimensional Robust Synthetic Control. SIGMETRICS (Abstracts) 2019: 55-56 - [c124]Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen:
Model Agnostic Time Series Analysis via Matrix Estimation. SIGMETRICS (Abstracts) 2019: 85-86 - [i58]Devavrat Shah, Qiaomin Xie, Zhi Xu:
On Reinforcement Learning Using Monte Carlo Tree Search with Supervised Learning: Non-Asymptotic Analysis. CoRR abs/1902.05213 (2019) - [i57]Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song:
Model Agnostic High-Dimensional Error-in-Variable Regression. CoRR abs/1902.10920 (2019) - [i56]Abdullah Alomar, Muhammad J. Amjad, Robert Lindland, Devavrat Shah:
Time Series Predict DB. CoRR abs/1903.07097 (2019) - [i55]Anish Agarwal, Munther A. Dahleh, Devavrat Shah, Dylan Sleeper, Andrew Tsai, Madeline Wong:
Zorro: A Model Agnostic System to Price Consumer Data. CoRR abs/1906.02420 (2019) - [i54]Devavrat Shah, Christina Lee Yu:
Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation. CoRR abs/1908.01241 (2019) - [i53]Lavanya Marla, Lav R. Varshney, Devavrat Shah, Nirmal A. Prakash, Michael E. Gale:
Short and Wide Network Paths. CoRR abs/1911.00344 (2019) - 2018
- [j54]George H. Chen, Devavrat Shah:
Explaining the Success of Nearest Neighbor Methods in Prediction. Found. Trends Mach. Learn. 10(5-6): 337-588 (2018) - [j53]Muhammad J. Amjad, Devavrat Shah, Dennis Shen:
Robust Synthetic Control. J. Mach. Learn. Res. 19: 22:1-22:51 (2018) - [j52]Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen:
Model Agnostic Time Series Analysis via Matrix Estimation. Proc. ACM Meas. Anal. Comput. Syst. 2(3): 40:1-40:39 (2018) - [j51]Guy Bresler, David Gamarnik, Devavrat Shah:
Learning Graphical Models From the Glauber Dynamics. IEEE Trans. Inf. Theory 64(6): 4072-4080 (2018) - [c123]Devavrat Shah, Christina E. Lee:
Reducing Crowdsourcing to Graphon Estimation, Statistically. AISTATS 2018: 1741-1750 - [c122]Devavrat Shah, Sai Burle, Vishal Doshi, Ying-zong Huang, Balaji Rengarajan:
Prediction Query Language. Allerton 2018: 611-616 - [c121]Linqi Song, Christina Fragouli, Devavrat Shah:
Recommender Systems over Wireless: Challenges and Opportunities. ITW 2018: 1-5 - [c120]Devavrat Shah, Qiaomin Xie:
Q-learning with Nearest Neighbors. NeurIPS 2018: 3115-3125 - [c119]Muhammad J. Amjad, Devavrat Shah:
Censored Demand Estimation in Retail. SIGMETRICS (Abstracts) 2018: 17-19 - [i52]Devavrat Shah, Qiaomin Xie:
Q-learning with Nearest Neighbors. CoRR abs/1802.03900 (2018) - [i51]Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen:
Time Series Analysis via Matrix Estimation. CoRR abs/1802.09064 (2018) - [i50]Linqi Song, Christina Fragouli, Devavrat Shah:
Regret vs. Bandwidth Trade-off for Recommendation Systems. CoRR abs/1810.06313 (2018) - [i49]Devavrat Shah, Dogyoon Song:
Learning Mixture Model with Missing Values and its Application to Rankings. CoRR abs/1812.11917 (2018) - 2017
- [j50]Sahand Negahban, Sewoong Oh, Devavrat Shah:
Rank Centrality: Ranking from Pairwise Comparisons. Oper. Res. 65(1): 266-287 (2017) - [j49]Muhammad J. Amjad, Devavrat Shah:
Censored Demand Estimation in Retail. Proc. ACM Meas. Anal. Comput. Syst. 1(2): 31:1-31:28 (2017) - [j48]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard, Parastoo Sadeghi:
Feedback-Based Online Network Coding. IEEE Trans. Inf. Theory 63(10): 6628-6649 (2017) - [c118]Devavrat Shah:
Matrix Estimation, Latent Variable Model and Collaborative Filtering. FSTTCS 2017: 4:1-4:8 - [c117]Christian Borgs, Jennifer T. Chayes, Christina E. Lee, Devavrat Shah:
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation. NIPS 2017: 4715-4726 - [c116]Jonathan Perry, Hari Balakrishnan, Devavrat Shah:
Flowtune: Flowlet Control for Datacenter Networks. NSDI 2017: 421-435 - [i48]Devavrat Shah, Qiaomin Xie:
Centralized Congestion Control and Scheduling in a Datacenter. CoRR abs/1710.02548 (2017) - 2016
- [j47]Devavrat Shah, Tauhid Zaman:
Finding Rumor Sources on Random Trees. Oper. Res. 64(3): 736-755 (2016) - [c115]Devavrat Shah:
Compute Choice. ICALP 2016: 1:1-1:1 - [c114]Muhammad J. Amjad, Devavrat Shah:
Trading Bitcoin and Online Time Series Prediction. NIPS Time Series Workshop 2016: 1-15 - [c113]Dogyoon Song, Christina E. Lee, Yihua Li, Devavrat Shah:
Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering. NIPS 2016: 2155-2163 - [c112]Guy Bresler, Devavrat Shah, Luis Filipe Voloch:
Collaborative Filtering with Low Regret. SIGMETRICS 2016: 207-220 - 2015
- [c111]George H. Chen, Devavrat Shah, Polina Golland:
A Latent Source Model for Patch-Based Image Segmentation. MICCAI (3) 2015: 140-148 - [e1]Bill Lin, Jun (Jim) Xu, Sudipta Sengupta, Devavrat Shah:
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, Portland, OR, USA, June 15-19, 2015. ACM 2015, ISBN 978-1-4503-3486-0 [contents] - [i47]Guy Bresler, Devavrat Shah, Luis Filipe Voloch:
Collaborative Filtering with Low Regret. CoRR abs/1507.05371 (2015) - [i46]George H. Chen, Devavrat Shah, Polina Golland:
A Latent Source Model for Patch-Based Image Segmentation. CoRR abs/1510.01648 (2015) - 2014
- [j46]David R. Karger, Sewoong Oh, Devavrat Shah:
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems. Oper. Res. 62(1): 1-24 (2014) - [j45]H. Vincent Poor, Kwang-Cheng Chen, Vikram Krishnamurthy, Devavrat Shah, Patrick J. Wolfe:
Introduction to the Issue on Signal Processing for Social Networks [Guest editorial]. IEEE J. Sel. Top. Signal Process. 8(4): 511-513 (2014) - [c110]Devavrat Shah, Kang Zhang:
Bayesian regression and Bitcoin. Allerton 2014: 409-414 - [c109]Guy Bresler, David Gamarnik, Devavrat Shah:
Learning graphical models from the Glauber dynamics. Allerton 2014: 1148-1155 - [c108]Sewoong Oh, Devavrat Shah:
Learning Mixed Multinomial Logit Model from Ordinal Data. NIPS 2014: 595-603 - [c107]Guy Bresler, David Gamarnik, Devavrat Shah:
Hardness of parameter estimation in graphical models. NIPS 2014: 1062-1070 - [c106]Guy Bresler, David Gamarnik, Devavrat Shah:
Structure learning of antiferromagnetic Ising models. NIPS 2014: 2852-2860 - [c105]Guy Bresler, George H. Chen, Devavrat Shah:
A Latent Source Model for Online Collaborative Filtering. NIPS 2014: 3347-3355 - [c104]Jonathan Perry, Amy Ousterhout, Hari Balakrishnan, Devavrat Shah, Hans Fugal:
Fastpass: a centralized "zero-queue" datacenter network. SIGCOMM 2014: 307-318 - [c103]Ammar Ammar, Sewoong Oh, Devavrat Shah, Luis Filipe Voloch:
What's your choice?: learning the mixed multi-nomial. SIGMETRICS 2014: 565-566 - [i45]Devavrat Shah, John N. Tsitsiklis, Yuan Zhong:
On Queue-Size Scaling for Input-Queued Switches. CoRR abs/1405.4764 (2014) - [i44]Guy Bresler, David Gamarnik, Devavrat Shah:
Hardness of parameter estimation in graphical models. CoRR abs/1409.3836 (2014) - [i43]Angélique Dremeau, Christophe Schülke, Yingying Xu, Devavrat Shah:
Statistical inference with probabilistic graphical models. CoRR abs/1409.4928 (2014) - [i42]Devavrat Shah, Kang Zhang:
Bayesian regression and Bitcoin. CoRR abs/1410.1231 (2014) - [i41]Guy Bresler, David Gamarnik, Devavrat Shah:
Learning graphical models from the Glauber dynamics. CoRR abs/1410.7659 (2014) - [i40]Christina E. Lee, Asuman E. Ozdaglar, Devavrat Shah:
Solving Systems of Linear Equations: Locally and Asynchronously. CoRR abs/1411.2647 (2014) - [i39]Guy Bresler, George H. Chen, Devavrat Shah:
A Latent Source Model for Online Collaborative Filtering. CoRR abs/1411.6591 (2014) - [i38]Guy Bresler, David Gamarnik, Devavrat Shah:
Structure learning of antiferromagnetic Ising models. CoRR abs/1412.1443 (2014) - 2013
- [j44]Vivek F. Farias, Srikanth Jagabathula, Devavrat Shah:
A Nonparametric Approach to Modeling Choice with Limited Data. Manag. Sci. 59(2): 305-322 (2013) - [j43]Masood Qazi, Mehul Tikekar, Lara Dolecek, Devavrat Shah, Anantha P. Chandrakasan:
Technique for Efficient Evaluation of SRAM Timing Failure. IEEE Trans. Very Large Scale Integr. Syst. 21(8): 1558-1562 (2013) - [c102]George H. Chen, Stanislav Nikolov, Devavrat Shah:
A Latent Source Model for Nonparametric Time Series Classification. NIPS 2013: 1088-1096 - [c101]Christina E. Lee, Asuman E. Ozdaglar, Devavrat Shah:
Computing the Stationary Distribution Locally. NIPS 2013: 1376-1384 - [c100]David R. Karger, Sewoong Oh, Devavrat Shah:
Efficient crowdsourcing for multi-class labeling. SIGMETRICS 2013: 81-92 - [i37]George H. Chen, Stanislav Nikolov, Devavrat Shah:
A Latent Source Model for Online Time Series Classification. CoRR abs/1302.3639 (2013) - [i36]Vincent D. Blondel, Kyomin Jung, Pushmeet Kohli, Devavrat Shah:
Partition-Merge: Distributed Inference and Modularity Optimization. CoRR abs/1309.6129 (2013) - [i35]Christina E. Lee, Asuman E. Ozdaglar, Devavrat Shah:
Computing the Stationary Distribution Locally. CoRR abs/1312.1986 (2013) - 2012
- [j42]David Gamarnik, Devavrat Shah, Yehua Wei:
Belief Propagation for Min-Cost Network Flow: Convergence and Correctness. Oper. Res. 60(2): 410-428 (2012) - [j41]Devavrat Shah, Damon Wischik:
Log-weight scheduling in switched networks. Queueing Syst. Theory Appl. 71(1-2): 97-136 (2012) - [j40]Devavrat Shah:
Product-form distributions and network algorithms (abstract only). SIGMETRICS Perform. Evaluation Rev. 39(4): 24 (2012) - [j39]Urs Niesen, Devavrat Shah, Gregory W. Wornell:
Caching in Wireless Networks. IEEE Trans. Inf. Theory 58(10): 6524-6540 (2012) - [c99]Sahand Negahban, Devavrat Shah:
Learning sparse Boolean polynomials. Allerton Conference 2012: 2032-2036 - [c98]Peter Anthony Iannucci, Kermin Elliott Fleming, Jonathan Perry, Hari Balakrishnan, Devavrat Shah:
A hardware spinal decoder. ANCS 2012: 151-162 - [c97]Vivek F. Farias, Srikanth Jagabathula, Devavrat Shah:
Sparse choice models. CISS 2012: 1-28 - [c96]Peter Anthony Iannucci, Jonathan Perry, Hari Balakrishnan, Devavrat Shah:
No symbol left behind: a link-layer protocol for rateless codes. MobiCom 2012: 17-28 - [c95]Sahand Negahban, Sewoong Oh, Devavrat Shah:
Iterative ranking from pair-wise comparisons. NIPS 2012: 2483-2491 - [c94]Jonathan Perry, Peter Iannucci, Kermin Fleming, Hari Balakrishnan, Devavrat Shah:
Spinal codes. SIGCOMM 2012: 49-60 - [c93]Devavrat Shah, Neil S. Walton, Yuan Zhong:
Optimal queue-size scaling in switched networks. SIGMETRICS 2012: 17-28 - [c92]Devavrat Shah, Tauhid Zaman:
Rumor centrality: a universal source detector. SIGMETRICS 2012: 199-210 - [c91]Ammar Ammar, Devavrat Shah:
Efficient rank aggregation using partial data. SIGMETRICS 2012: 355-366 - [c90]Shreeshankar Bodas, Devavrat Shah, Damon Wischik:
Congestion control meets medium access: throughput, delay, and complexity. SIGMETRICS 2012: 399-400 - [i34]Hari Balakrishnan, Peter Iannucci, Jonathan Perry, Devavrat Shah:
De-randomizing Shannon: The Design and Analysis of a Capacity-Achieving Rateless Code. CoRR abs/1206.0418 (2012) - [i33]Sahand Negahban, Sewoong Oh, Devavrat Shah:
Iterative Ranking from Pair-wise Comparisons. CoRR abs/1209.1688 (2012) - 2011
- [j38]Shreevatsa Rajagopalan, Devavrat Shah:
Distributed Averaging in Dynamic Networks. IEEE J. Sel. Top. Signal Process. 5(4): 845-854 (2011) - [j37]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard, Szymon Jakubczak, Michael Mitzenmacher, João Barros:
Network Coding Meets TCP: Theory and Implementation. Proc. IEEE 99(3): 490-512 (2011) - [j36]Devavrat Shah, John N. Tsitsiklis, Yuan Zhong:
Optimal scaling of average queue sizes in an input-queued switch: an open problem. Queueing Syst. Theory Appl. 68(3-4): 375-384 (2011) - [j35]Devavrat Shah, Damon Wischik:
Fluid models of congestion collapse in overloaded switched networks. Queueing Syst. Theory Appl. 69(2): 121-143 (2011) - [j34]Venkat Chandrasekaran, Misha Chertkov, David Gamarnik, Devavrat Shah, Jinwoo Shin:
Counting Independent Sets Using the Bethe Approximation. SIAM J. Discret. Math. 25(2): 1012-1034 (2011) - [j33]Nigel Drego, Anantha P. Chandrakasan, Duane S. Boning, Devavrat Shah:
Reduction of Variation-Induced Energy Overhead in Multi-Core Processors. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 30(6): 891-904 (2011) - [j32]Srikanth Jagabathula, Devavrat Shah:
Fair Scheduling in Networks Through Packet Election. IEEE Trans. Inf. Theory 57(3): 1368-1381 (2011) - [j31]Devavrat Shah, Tauhid Zaman:
Rumors in a Network: Who's the Culprit? IEEE Trans. Inf. Theory 57(8): 5163-5181 (2011) - [j30]Srikanth Jagabathula, Devavrat Shah:
Inferring Rankings Using Constrained Sensing. IEEE Trans. Inf. Theory 57(11): 7288-7306 (2011) - [j29]Devavrat Shah, David N. C. Tse, John N. Tsitsiklis:
Hardness of Low Delay Network Scheduling. IEEE Trans. Inf. Theory 57(12): 7810-7817 (2011) - [c89]Shreeshankar Bodas, Devavrat Shah, Damon Wischik:
Interference is not noise. Allerton 2011: 119-126 - [c88]David R. Karger, Sewoong Oh, Devavrat Shah:
Budget-optimal crowdsourcing using low-rank matrix approximations. Allerton 2011: 284-291 - [c87]Ammar Ammar, Devavrat Shah:
Ranking: Compare, don't score. Allerton 2011: 776-783 - [c86]Lav R. Varshney, Devavrat Shah:
Informational limits of neural circuits. Allerton 2011: 1757-1763 - [c85]Devavrat Shah:
Three metrics for stochastic networks: Capacity, queue-size and complexity. COMSNETS 2011: 1-4 - [c84]Devavrat Shah, Jinwoo Shin, Prasad Tetali:
Medium Access Using Queues. FOCS 2011: 698-707 - [c83]Jonathan Perry, Hari Balakrishnan, Devavrat Shah:
Rateless spinal codes. HotNets 2011: 6 - [c82]Shreeshankar Bodas, Devavrat Shah:
Fast averaging. ISIT 2011: 2153-2157 - [c81]David R. Karger, Sewoong Oh, Devavrat Shah:
Iterative Learning for Reliable Crowdsourcing Systems. NIPS 2011: 1953-1961 - [i32]Devavrat Shah, Jinwoo Shin, Prasad Tetali:
Efficient Distributed Medium Access. CoRR abs/1104.2380 (2011) - [i31]David R. Karger, Sewoong Oh, Devavrat Shah:
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems. CoRR abs/1110.3564 (2011) - [i30]Devavrat Shah, Neil S. Walton, Yuan Zhong:
Optimal Queue-Size Scaling in Switched Networks. CoRR abs/1110.4697 (2011) - 2010
- [j28]Damon Mosk-Aoyama, Tim Roughgarden, Devavrat Shah:
Fully Distributed Algorithms for Convex Optimization Problems. SIAM J. Optim. 20(6): 3260-3279 (2010) - [j27]Kyomin Jung, Devavrat Shah, Jinwoo Shin:
Distributed averaging via lifted Markov chains. IEEE Trans. Inf. Theory 56(1): 634-647 (2010) - [j26]Urs Niesen, Piyush Gupta, Devavrat Shah:
The balanced unicast and multicast capacity regions of large wireless networks. IEEE Trans. Inf. Theory 56(5): 2249-2271 (2010) - [j25]Vishal Doshi, Devavrat Shah, Muriel Médard, Michelle Effros:
Functional compression through graph coloring. IEEE Trans. Inf. Theory 56(8): 3901-3917 (2010) - [j24]Ola Ayaso, Devavrat Shah, Munther A. Dahleh:
Information Theoretic Bounds for Distributed Computation Over Networks of Point-to-Point Channels. IEEE Trans. Inf. Theory 56(12): 6020-6039 (2010) - [j23]Libin Jiang, Devavrat Shah, Jinwoo Shin, Jean C. Walrand:
Distributed Random Access Algorithm: Scheduling and Congestion Control. IEEE Trans. Inf. Theory 56(12): 6182-6207 (2010) - [j22]Atilla Eryilmaz, Asuman E. Ozdaglar, Devavrat Shah, Eytan H. Modiano:
Distributed cross-layer algorithms for the optimal control of multihop wireless networks. IEEE/ACM Trans. Netw. 18(2): 638-651 (2010) - [c80]Masood Qazi, Mehul Tikekar, Lara Dolecek, Devavrat Shah, Anantha P. Chandrakasan:
Loop flattening & spherical sampling: Highly efficient model reduction techniques for SRAM yield analysis. DATE 2010: 801-806 - [c79]Paolo Giaccone, Devavrat Shah:
Message-Passing for Wireless Scheduling: An Experimental Study. ICCCN 2010: 1-6 - [c78]Venkat Chandar, Devavrat Shah, Gregory W. Wornell:
A simple message-passing algorithm for compressed sensing. ISIT 2010: 1968-1972 - [c77]Ciamac Cyrus Moallemi, Devavrat Shah:
On the flow-level dynamics of a packet-switched network. SIGMETRICS 2010: 83-94 - [c76]Devavrat Shah, Jinwoo Shin:
Dynamics in congestion games. SIGMETRICS 2010: 107-118 - [c75]Devavrat Shah, Tauhid Zaman:
Detecting sources of computer viruses in networks: theory and experiment. SIGMETRICS 2010: 203-214 - [c74]Devavrat Shah, John N. Tsitsiklis, Yuan Zhong:
Qualitative properties of alpha-weighted scheduling policies. SIGMETRICS 2010: 239-250 - [c73]Shreevatsa Rajagopalan, Devavrat Shah:
Distributed averaging in dynamic networks. SIGMETRICS 2010: 369-370 - [c72]Devavrat Shah, Jinwoo Shin:
Delay optimal queue-based CSMA. SIGMETRICS 2010: 373-374 - [c71]David Gamarnik, Devavrat Shah, Yehua Wei:
Belief Propagation for Min-cost Network Flow: Convergence & Correctness. SODA 2010: 279-292 - [i29]Venkat Chandar, Devavrat Shah, Gregory W. Wornell:
A Simple Message-Passing Algorithm for Compressed Sensing. CoRR abs/1001.4110 (2010) - [i28]Ciamac Cyrus Moallemi, Devavrat Shah:
On the Flow-level Dynamics of a Packet-switched Network. CoRR abs/1003.0929 (2010) - [i27]Devavrat Shah, Jinwoo Shin:
Efficient Queue-based CSMA with Collisions. CoRR abs/1003.2749 (2010) - [i26]Devavrat Shah, John N. Tsitsiklis, Yuan Zhong:
Qualitative Properties of alpha-Weighted Scheduling Policies. CoRR abs/1003.5979 (2010) - [i25]Devavrat Shah, Damon Wischik:
Switched networks with maximum weight policies: Fluid approximation and multiplicative state space collapse. CoRR abs/1004.1995 (2010) - [i24]Devavrat Shah, Tauhid Zaman:
Community Detection in Networks: The Leader-Follower Algorithm. CoRR abs/1011.0774 (2010)
2000 – 2009
- 2009
- [j21]Devavrat Shah:
Gossip Algorithms. Found. Trends Netw. 3(1): 1-125 (2009) - [j20]Justin Salez, Devavrat Shah:
Belief Propagation: An Asymptotically Optimal Algorithm for the Random Assignment Problem. Math. Oper. Res. 34(2): 468-480 (2009) - [j19]Urs Niesen, Devavrat Shah, Gregory W. Wornell:
Adaptive Alternating Minimization Algorithms. IEEE Trans. Inf. Theory 55(3): 1423-1429 (2009) - [j18]Urs Niesen, Piyush Gupta, Devavrat Shah:
On capacity scaling in arbitrary wireless networks. IEEE Trans. Inf. Theory 55(9): 3959-3982 (2009) - [j17]Sujay Sanghavi, Devavrat Shah, Alan S. Willsky:
Message passing for maximum weight independent set. IEEE Trans. Inf. Theory 55(11): 4822-4834 (2009) - [c70]Venkat Chandar, Devavrat Shah, Gregory W. Wornell:
A locally encodable and decodable compressed data structure. Allerton 2009: 613-619 - [c69]Devavrat Shah:
Network gossip algorithms. ICASSP 2009: 3673-3676 - [c68]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard, Michael Mitzenmacher, João Barros:
Network Coding Meets TCP. INFOCOM 2009: 280-288 - [c67]Ramakrishna Gummadi, Kyomin Jung, Devavrat Shah, Ramavarapu S. Sreenivas:
Computing the Capacity Region of a Wireless Network. INFOCOM 2009: 1341-1349 - [c66]Urs Niesen, Piyush Gupta, Devavrat Shah:
The Multicast Capacity Region of Large Wireless Networks. INFOCOM 2009: 1881-1889 - [c65]Lara Dolecek, Devavrat Shah:
Influence in a large society: Interplay between information dynamics and network structure. ISIT 2009: 1574-1578 - [c64]Urs Niesen, Devavrat Shah, Gregory W. Wornell:
Caching in wireless networks. ISIT 2009: 2111-2115 - [c63]Vivek F. Farias, Srikanth Jagabathula, Devavrat Shah:
A Data-Driven Approach to Modeling Choice. NIPS 2009: 504-512 - [c62]Kyomin Jung, Pushmeet Kohli, Devavrat Shah:
Local Rules for Global MAP: When Do They Work ? NIPS 2009: 871-879 - [c61]Shreevatsa Rajagopalan, Devavrat Shah, Jinwoo Shin:
Network adiabatic theorem: an efficient randomized protocol for contention resolution. SIGMETRICS/Performance 2009: 133-144 - [i23]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard:
Feedback-based online network coding. CoRR abs/0904.1730 (2009) - [i22]Libin Jiang, Devavrat Shah, Jinwoo Shin, Jean C. Walrand:
Distributed Random Access Algorithm: Scheduling and Congesion Control. CoRR abs/0907.1266 (2009) - [i21]Urs Niesen, Devavrat Shah, Gregory W. Wornell:
Caching in Wireless Networks. CoRR abs/0908.1916 (2009) - [i20]Devavrat Shah, Jinwoo Shin:
Randomized Scheduling Algorithm for Queueing Networks. CoRR abs/0908.3670 (2009) - [i19]Kyomin Jung, Devavrat Shah, Jinwoo Shin:
Distributed Averaging via Lifted Markov Chains. CoRR abs/0908.4073 (2009) - 2008
- [j16]Holly A. Waisanen, Devavrat Shah, Munther A. Dahleh:
A Dynamic Pickup and Delivery Problem in Mobile Networks Under Information Constraints. IEEE Trans. Autom. Control. 53(6): 1419-1433 (2008) - [j15]Mohsen Bayati, Devavrat Shah, Mayank Sharma:
Max-Product for Maximum Weight Matching: Convergence, Correctness, and LP Duality. IEEE Trans. Inf. Theory 54(3): 1241-1251 (2008) - [j14]Ritesh Madan, Devavrat Shah, Olivier Lévêque:
Product Multicommodity Flow in Wireless Networks. IEEE Trans. Inf. Theory 54(4): 1460-1476 (2008) - [j13]Damon Mosk-Aoyama, Devavrat Shah:
Fast Distributed Algorithms for Computing Separable Functions. IEEE Trans. Inf. Theory 54(7): 2997-3007 (2008) - [c60]Urs Niesen, Piyush Gupta, Devavrat Shah:
The capacity region of large wireless networks. Allerton 2008: 460-466 - [c59]Devavrat Shah, Damon Wischik:
Lower bound and optimality in switched networks. Allerton 2008: 1262-1269 - [c58]Ola Ayaso, Devavrat Shah, Munther A. Dahleh:
Distributed computation under bit constraints. CDC 2008: 4837-4842 - [c57]Shreevatsa Rajagopalan, Devavrat Shah:
Distributed algorithm and reversible network. CISS 2008: 498-502 - [c56]Atilla Eryilmaz, Asuman E. Ozdaglar, Devavrat Shah, Eytan H. Modiano:
Imperfect randomized algorithms for the optimal control of wireless networks. CISS 2008: 932-937 - [c55]Lara Dolecek, Masood Qazi, Devavrat Shah, Anantha P. Chandrakasan:
Breaking the simulation barrier: SRAM evaluation through norm minimization. ICCAD 2008: 322-329 - [c54]Srikanth Jagabathula, Vishal Doshi, Devavrat Shah:
Fair Scheduling through Packet Election. INFOCOM 2008: 301-305 - [c53]Ramakrishna Gummadi, Kyomin Jung, Devavrat Shah, Ramavarapu S. Sreenivas:
Feasible Rate Allocation in Wireless Networks. INFOCOM 2008: 995-1003 - [c52]Urs Niesen, Piyush Gupta, Devavrat Shah:
Hierarchical cooperation for arbitrary wireless networks. ISIT 2008: 181-185 - [c51]Ola Ayaso, Devavrat Shah, Munther A. Dahleh:
Counting bits for distributed function computation. ISIT 2008: 652-656 - [c50]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard:
ARQ for network coding. ISIT 2008: 1651-1655 - [c49]Urs Niesen, Piyush Gupta, Devavrat Shah:
Cooperative multi-hop schemes for arbitrary wireless networks. ITW 2008: 222-226 - [c48]Srikanth Jagabathula, Devavrat Shah:
Inferring rankings under constrained sensing. NIPS 2008: 753-760 - [c47]Srikanth Jagabathula, Devavrat Shah:
Optimal delay scheduling in networks with arbitrary constraints. SIGMETRICS 2008: 395-406 - [c46]Kyomin Jung, Yingdong Lu, Devavrat Shah, Mayank Sharma, Mark S. Squillante:
Revisiting stochastic loss networks: structures and algorithms. SIGMETRICS 2008: 407-418 - [i18]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard:
ARQ for Network Coding. CoRR abs/0802.1754 (2008) - [i17]Urs Niesen, Devavrat Shah, Gregory W. Wornell:
Source Coding with Mismatched Distortion Measures. CoRR abs/0804.0635 (2008) - [i16]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard:
Online network coding for optimal throughput and delay -- the two-receiver case. CoRR abs/0806.4264 (2008) - [i15]Sujay Sanghavi, Devavrat Shah, Alan S. Willsky:
Message-passing for Maximum Weight Independent Set. CoRR abs/0807.5091 (2008) - [i14]Srikanth Jagabathula, Devavrat Shah:
Fair Scheduling in Networks Through Packet Election. CoRR abs/0808.2530 (2008) - [i13]Urs Niesen, Piyush Gupta, Devavrat Shah:
The Capacity Region of Large Wireless Networks. CoRR abs/0809.1344 (2008) - [i12]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard, Michael Mitzenmacher, João Barros:
Network coding meets TCP. CoRR abs/0809.5022 (2008) - 2007
- [j12]James P. Mammen, Devavrat Shah:
Throughput and Delay in Random Wireless Networks With Restricted Mobility. IEEE Trans. Inf. Theory 53(3): 1108-1116 (2007) - [j11]Paolo Giaccone, Emilio Leonardi, Devavrat Shah:
Throughput Region of Finite-Buffered Networks. IEEE Trans. Parallel Distributed Syst. 18(2): 251-263 (2007) - [c45]Holly A. Waisanen, Devavrat Shah, Munther A. Dahleh:
Lower bounds for multi-stage vehicle routing. CDC 2007: 4570-4575 - [c44]Vishal Doshi, Devavrat Shah, Muriel Médard, Sidharth Jaggi:
Distributed Functional Compression through Graph Coloring. DCC 2007: 93-102 - [c43]Mohsen Bayati, Balaji Prabhakar, Devavrat Shah, Mayank Sharma:
Iterative Scheduling Algorithms. INFOCOM 2007: 445-453 - [c42]Jay Kumar Sundararajan, Muriel Médard, Minji Kim, Atilla Eryilmaz, Devavrat Shah, Ralf Koetter:
Network Coding in a Multicast Switch. INFOCOM 2007: 1145-1153 - [c41]Devavrat Shah, Sanjay Shakkottai:
Oblivious Routing with Mobile Fusion Centers over a Sensor Network. INFOCOM 2007: 1541-1549 - [c40]Kyomin Jung, Devavrat Shah:
Low Delay Scheduling in Wireless Network. ISIT 2007: 1396-1400 - [c39]Vishal Doshi, Devavrat Shah, Muriel Médard:
Source Coding with Distortion through Graph Coloring. ISIT 2007: 1501-1505 - [c38]Urs Niesen, Devavrat Shah, Gregory W. Wornell:
Adaptive Alternating Minimization Algorithms. ISIT 2007: 1641-1645 - [c37]Jay Kumar Sundararajan, Devavrat Shah, Muriel Médard:
On queueing in coded networks - queue size follows degrees of freedom. ITW 2007: 1-6 - [c36]Kyomin Jung, Devavrat Shah:
Local Algorithms for Approximate Inference in Minor-Excluded Graphs. NIPS 2007: 729-736 - [c35]Sujay Sanghavi, Devavrat Shah, Alan S. Willsky:
Message Passing for Max-weight Independent Set. NIPS 2007: 1281-1288 - [c34]Andrea Montanari, Devavrat Shah:
Counting good truth assignments of random k-SAT formulae. SODA 2007: 1255-1264 - [c33]Damon Mosk-Aoyama, Tim Roughgarden, Devavrat Shah:
Fully Distributed Algorithms for Convex Optimization Problems. DISC 2007: 492-493 - [i11]Urs Niesen, Piyush Gupta, Devavrat Shah:
On Capacity Scaling in Arbitrary Wireless Networks. CoRR abs/0711.2745 (2007) - [i10]Urs Niesen, Devavrat Shah, Gregory W. Wornell:
Adaptive Alternating Minimization Algorithms. CoRR abs/cs/0701043 (2007) - 2006
- [j10]Stephen P. Boyd, Arpita Ghosh, Balaji Prabhakar, Devavrat Shah:
Randomized gossip algorithms. IEEE Trans. Inf. Theory 52(6): 2508-2530 (2006) - [j9]Abbas El Gamal, James P. Mammen, Balaji Prabhakar, Devavrat Shah:
Optimal throughput-delay scaling in wireless networks: part I: the fluid model. IEEE Trans. Inf. Theory 52(6): 2568-2592 (2006) - [j8]Abbas El Gamal, James P. Mammen, Balaji Prabhakar, Devavrat Shah:
Optimal Throughput-Delay Scaling in Wireless Networks - Part II: Constant-Size Packets. IEEE Trans. Inf. Theory 52(11): 5111-5116 (2006) - [c32]Holly A. Waisanen, Devavrat Shah, Munther A. Dahleh:
Minimal Delay in Controlled Mobile Relay Networks. CDC 2006: 1918-1922 - [c31]Supratim Deb, Devavrat Shah, Sanjay Shakkottai:
Fast Matching Algorithms for Repetitive Optimization: An Application to Switch Scheduling. CISS 2006: 1266-1271 - [c30]Urs Niesen, Uri Erez, Devavrat Shah, Gregory W. Wornell:
Rateless Codes for the Gaussian Multiple Access Channel. GLOBECOM 2006 - [c29]Devavrat Shah, Damon Wischik:
Optimal Scheduling Algorithms for Input-Queued Switches. INFOCOM 2006 - [c28]Mohsen Bayati, Devavrat Shah, Mayank Sharma:
A Simpler Max-Product Maximum Weight Matching Algorithm and the Auction Algorithm. ISIT 2006: 557-561 - [c27]Damon Mosk-Aoyama, Devavrat Shah:
Information Dissemination via Network Coding. ISIT 2006: 1748-1752 - [c26]Olivier Lévêque, Ritesh Madan, Devavrat Shah:
Uniform Multi-commodity Flow in Wireless Networks with Gaussian Fading Channels. ISIT 2006: 1846-1850 - [c25]Kyomin Jung, Devavrat Shah:
Fast Gossip via Non-reversible Random Walk. ITW 2006: 67-71 - [c24]Damon Mosk-Aoyama, Devavrat Shah:
Computing separable functions via gossip. PODC 2006: 113-122 - [c23]Eytan H. Modiano, Devavrat Shah, Gil Zussman:
Maximizing throughput in wireless networks via gossiping. SIGMETRICS/Performance 2006: 27-38 - [i9]Ritesh Madan, Devavrat Shah, Olivier Lévêque:
Product Multicommodity Flow in Wireless Networks. CoRR abs/cs/0601012 (2006) - [i8]Andrea Montanari, Devavrat Shah:
Counting good truth assignments of random k-SAT formulae. CoRR abs/cs/0607073 (2006) - [i7]Chandra Nair, Balaji Prabhakar, Devavrat Shah:
On entropy for mixtures of discrete and continuous variables. CoRR abs/cs/0607075 (2006) - [i6]Jay Kumar Sundararajan, Muriel Médard, Minji Kim, Atilla Eryilmaz, Devavrat Shah, Ralf Koetter:
Network Coding in a Multicast Switch. CoRR abs/cs/0608044 (2006) - [i5]Kyomin Jung, Devavrat Shah:
Local approximate inference algorithms. CoRR abs/cs/0610111 (2006) - 2005
- [b1]Devavrat Shah:
Randomization and heavy traffic theory : new approaches to the design and analysis of switch algorithms. Stanford University, USA, 2005 - [j7]Yashar Ganjali, Abtin Keshavarzian, Devavrat Shah:
Cell switching versus packet switching in input-queued switches. IEEE/ACM Trans. Netw. 13(4): 782-789 (2005) - [c22]Stephen P. Boyd, Arpita Ghosh, Balaji Prabhakar, Devavrat Shah:
Mixing Times for Random Walks on Geometric Random Graphs. ALENEX/ANALCO 2005: 240-249 - [c21]Paolo Giaccone, Emilio Leonardi, Devavrat Shah:
On the maximal throughput of networks with finite buffers and its application to buffered crossbars. INFOCOM 2005: 971-980 - [c20]Stephen P. Boyd, Arpita Ghosh, Balaji Prabhakar, Devavrat Shah:
Gossip algorithms: design, analysis and applications. INFOCOM 2005: 1653-1664 - [c19]Abbas El Gamal, James P. Mammen, Balaji Prabhakar, Devavrat Shah:
Throughput-delay scaling in wireless networks with constant-size packets. ISIT 2005: 1329-1333 - [c18]Mohsen Bayati, Devavrat Shah, Mayank Sharma:
Maximum weight matching via max-product belief propagation. ISIT 2005: 1763-1767 - [i4]Damon Mosk-Aoyama, Devavrat Shah:
Fast Distributed Algorithms for Computing Separable Functions. CoRR abs/cs/0504029 (2005) - [i3]James P. Mammen, Devavrat Shah:
Throughput and Delay in Random Wireless Networks with Restricted Mobility. CoRR abs/cs/0508074 (2005) - [i2]Devavrat Shah:
Max Product for Max-Weight Independent Set and Matching. CoRR abs/cs/0508097 (2005) - [i1]Mohsen Bayati, Devavrat Shah, Mayank Sharma:
Maximum Weight Matching via Max-Product Belief Propagation. CoRR abs/cs/0508101 (2005) - 2004
- [j6]Paolo Giaccone, Emilio Leonardi, Balaji Prabhakar, Devavrat Shah:
Delay bounds for combined input-output switches with low speedup. Perform. Evaluation 55(1-2): 113-128 (2004) - [c17]Stephen P. Boyd, Arpita Ghosh, Balaji Prabhakar, Devavrat Shah:
Analysis and optimization of randomized gossip algorithms. CDC 2004: 5310-5315 - [c16]Neha Kumar, Rong Pan, Devavrat Shah:
Fair scheduling in input-queued switches under inadmissible traffic. GLOBECOM 2004: 1713-1717 - [c15]Abbas El Gamal, James P. Mammen, Balaji Prabhakar, Devavrat Shah:
Throughput-Delay Trade-off in Wireless Networks. INFOCOM 2004 - [c14]Abbas El Gamal, James P. Mammen, Balaji Prabhakar, Devavrat Shah:
Throughput-delay trade-off in energy constrained wireless networks. ISIT 2004: 439 - [c13]James P. Mammen, Devavrat Shah:
Throughput and delay in random wireless networks: 1-D mobility is just as good as 2-D. ISIT 2004: 440 - 2003
- [j5]Paolo Giaccone, Balaji Prabhakar, Devavrat Shah:
Randomized scheduling algorithms for high-aggregate bandwidth switches. IEEE J. Sel. Areas Commun. 21(4): 546-559 (2003) - [c12]Gagan Aggarwal, Rajeev Motwani, Devavrat Shah, An Zhu:
Switch Scheduling via Randomized Edge Coloring. FOCS 2003: 502-512 - [c11]Devavrat Shah:
Maximal matching scheduling is good enough. GLOBECOM 2003: 3009-3013 - [c10]Yashar Ganjali, Abtin Keshavarzian, Devavrat Shah:
Input Queued Switches: Cell Switching vs. Packet Switching. INFOCOM 2003: 1651-1658 - 2002
- [j4]Devavrat Shah, Paolo Giaccone, Balaji Prabhakar:
Efficient Randomized Algorithms for Input-Queued Switch Scheduling. IEEE Micro 22(1): 10-18 (2002) - [j3]Paolo Giaccone, Devavrat Shah, Balaji Prabhakar:
An Implementable Parallel Scheduler for Input-Queued Switches. IEEE Micro 22(1): 19-25 (2002) - [j2]Devavrat Shah, Sundar Iyer, Balaji Prabhakar, Nick McKeown:
Maintaining Statistics Counters in Router Line Cards. IEEE Micro 22(1): 76-81 (2002) - [c9]Michael Mitzenmacher, Balaji Prabhakar, Devavrat Shah:
Load Balancing with Memory. FOCS 2002: 799-808 - [c8]Paolo Giaccone, Emilio Leonardi, Balaji Prabhakar, Devavrat Shah:
Delay performance of high-speed packet switches with low speedup. GLOBECOM 2002: 2629-2633 - [c7]Devavrat Shah, Milind Kopikare:
Delay bounds for the approximate Maximum weight matching algorithm for input queued switches. INFOCOM 2002: 1024-1031 - [c6]Paolo Giaccone, Balaji Prabhakar, Devavrat Shah:
Towards Simple, High-performance Schedulers for High-aggregate Bandwidth Switches. INFOCOM 2002: 1160-1169 - 2001
- [j1]Devavrat Shah, Pankaj Gupta:
Fast Updating Algorithms for TCAMs. IEEE Micro 21(1): 36-47 (2001) - [c5]Devavrat Shah, Paolo Giaccone, Balaji Prabhakar:
An efficient randomized algorithm for input-queued switch scheduling. Hot Interconnects 2001: 3-8 - [c4]Paolo Giaccone, Devavrat Shah, Balaji Prabhakar:
An implementable parallel scheduler for input-queued switches. Hot Interconnects 2001: 9-14 - [c3]Devavrat Shah, Sundar Iyer, Balaji Prabhakar, Nick McKeown:
Analysis of a statistics counter architecture. Hot Interconnects 2001: 107-111 - 2000
- [c2]Pradeep Shenoy, Jayant R. Haritsa, S. Sudarshan, Gaurav Bhalotia, Mayank Bawa, Devavrat Shah:
Turbo-charging Vertical Mining of Large Databases. SIGMOD Conference 2000: 22-33
1990 – 1999
- 1999
- [c1]Devavrat Shah, Laks V. S. Lakshmanan, Krithi Ramamritham, S. Sudarshan:
Interestingness and Pruning of Mined Patterns. 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery 1999
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-22 21:13 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
