Devavrat Shah

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MIT

Professor at Massachusetts Institute of Technology

Learning Mixture Model with Missing Values and its Application to Rankings

We consider the question of learning mixtures of generic sub-gaussian di...
12/31/2018 ∙ by Devavrat Shah, et al. ∙ 30 ∙ share

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Short and Wide Network Paths

Network flow is a powerful mathematical framework to systematically expl...
11/01/2019 ∙ by Lavanya Marla, et al. ∙ 19 ∙ share

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On Reinforcement Learning for Turn-based Zero-sum Markov Games

We consider the problem of finding Nash equilibrium for two-player turn-...
02/25/2020 ∙ by Devavrat Shah, et al. ∙ 8 ∙ share

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Unifying Framework for Crowd-sourcing via Graphon Estimation

We consider the question of inferring true answers associated with tasks...
03/23/2017 ∙ by Christina E. Lee, et al. ∙ 0 ∙ share

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Bayesian regression and Bitcoin

In this paper, we discuss the method of Bayesian regression and its effi...
10/06/2014 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Hardness of parameter estimation in graphical models

We consider the problem of learning the canonical parameters specifying ...
09/12/2014 ∙ by Guy Bresler, et al. ∙ 0 ∙ share

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Partition-Merge: Distributed Inference and Modularity Optimization

This paper presents a novel meta algorithm, Partition-Merge (PM), which ...
09/24/2013 ∙ by Vincent Blondel, et al. ∙ 0 ∙ share

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Structure learning of antiferromagnetic Ising models

In this paper we investigate the computational complexity of learning th...
12/03/2014 ∙ by Guy Bresler, et al. ∙ 0 ∙ share

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Learning Mixed Multinomial Logit Model from Ordinal Data

Motivated by generating personalized recommendations using ordinal (or p...
11/01/2014 ∙ by Sewoong Oh, et al. ∙ 0 ∙ share

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A Latent Source Model for Online Collaborative Filtering

Despite the prevalence of collaborative filtering in recommendation syst...
10/31/2014 ∙ by Guy Bresler, et al. ∙ 0 ∙ share

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Learning graphical models from the Glauber dynamics

In this paper we consider the problem of learning undirected graphical m...
10/28/2014 ∙ by Guy Bresler, et al. ∙ 0 ∙ share

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A Latent Source Model for Patch-Based Image Segmentation

Despite the popularity and empirical success of patch-based nearest-neig...
10/06/2015 ∙ by George Chen, et al. ∙ 0 ∙ share

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A Latent Source Model for Nonparametric Time Series Classification

For classifying time series, a nearest-neighbor approach is widely used ...
02/14/2013 ∙ by George H. Chen, et al. ∙ 0 ∙ share

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Belief Propagation for Min-cost Network Flow: Convergence and Correctness

Message passing type algorithms such as the so-called Belief Propagation...
04/09/2010 ∙ by David Gamarnik, et al. ∙ 0 ∙ share

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Rank Centrality: Ranking from Pair-wise Comparisons

The question of aggregating pair-wise comparisons to obtain a global ran...
09/08/2012 ∙ by Sahand Negahban, et al. ∙ 0 ∙ share

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Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems

Crowdsourcing systems, in which numerous tasks are electronically distri...
10/17/2011 ∙ by David R. Karger, et al. ∙ 0 ∙ share

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Sparse Choice Models

Choice models, which capture popular preferences over objects of interes...
11/19/2010 ∙ by Vivek F. Farias, et al. ∙ 0 ∙ share

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Community Detection in Networks: The Leader-Follower Algorithm

Traditional spectral clustering methods cannot naturally learn the numbe...
11/02/2010 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Rumors in a Network: Who's the Culprit?

We provide a systematic study of the problem of finding the source of a ...
09/24/2009 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Centralized Congestion Control and Scheduling in a Datacenter

We consider the problem of designing a packet-level congestion control a...
10/06/2017 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Q-learning with Nearest Neighbors

We consider the problem of model-free reinforcement learning for infinit...
02/12/2018 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Robust Synthetic Control

We present a robust generalization of the synthetic control method for c...
11/18/2017 ∙ by Muhammad Jehangir Amjad, et al. ∙ 0 ∙ share

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Iterative Collaborative Filtering for Sparse Matrix Estimation

The sparse matrix estimation problem consists of estimating the distribu...
12/03/2017 ∙ by Christian Borgs, et al. ∙ 0 ∙ share

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Time Series Analysis via Matrix Estimation

We consider the task of interpolating and forecasting a time series in t...
02/25/2018 ∙ by Anish Agarwal, et al. ∙ 0 ∙ share

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Monotone Matrix Estimation via Robust Deconvolution

The goal of deconvolution is in estimating the distribution of a random ...
03/09/2018 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Regret vs. Bandwidth Trade-off for Recommendation Systems

We consider recommendation systems that need to operate under wireless b...
10/15/2018 ∙ by Linqi Song, et al. ∙ 0 ∙ share

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On Reinforcement Learning Using Monte Carlo Tree Search with Supervised Learning: Non-Asymptotic Analysis

Inspired by the success of AlphaGo Zero (AGZ) which utilizes Monte Carlo...
02/14/2019 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Model Agnostic High-Dimensional Error-in-Variable Regression

We consider the problem of high-dimensional error-in-variable regression...
02/28/2019 ∙ by Anish Agarwal, et al. ∙ 0 ∙ share

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mRSC: Multi-dimensional Robust Synthetic Control

When evaluating the impact of a policy on a metric of interest, it may n...
05/15/2019 ∙ by Muhummad Amjad, et al. ∙ 0 ∙ share

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Time Series Predict DB

In this work, we are motivated to make predictive functionalities native...
03/17/2019 ∙ by Abdullah Alomar, et al. ∙ 0 ∙ share

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Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation

We consider the task of tensor estimation, i.e. estimating a low-rank 3-...
08/03/2019 ∙ by Devavrat Shah, et al. ∙ 0 ∙ share

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Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?

As we reach the apex of the COVID-19 pandemic, the most pressing questio...
04/30/2020 ∙ by Anish Agarwal, et al. ∙ 0 ∙ share

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Devavrat Shah

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