
Causal Imputation via Synthetic Interventions
Consider the problem of determining the effect of a drug on a specific c...
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GradientBased Empirical Risk Minimization using Local Polynomial Regression
In this paper, we consider the problem of empirical risk minimization (E...
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On Learning Continuous Pairwise Markov Random Fields
We consider learning a sparse pairwise Markov Random Field (MRF) with co...
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On Principal Component Regression in a HighDimensional ErrorinVariables Setting
We analyze the classical method of Principal Component Regression (PCR) ...
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On Multivariate Singular Spectrum Analysis
We analyze a variant of multivariate singular spectrum analysis (mSSA), ...
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Regulating algorithmic filtering on social media
Through the algorithmic filtering (AF) of content, social media platform...
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Estimation of Skill Distributions
In this paper, we study the problem of learning the skill distribution o...
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Synthetic Interventions
We develop a method to help quantify the impact different levels of mobi...
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Sample Efficient Reinforcement Learning via LowRank Matrix Estimation
We consider the question of learning Qfunction in a sample efficient ma...
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Stable Reinforcement Learning with Unbounded State Space
We consider the problem of reinforcement learning (RL) with unbounded st...
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Two Burning Questions on COVID19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?
As we reach the apex of the COVID19 pandemic, the most pressing questio...
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On Reinforcement Learning for Turnbased Zerosum Markov Games
We consider the problem of finding Nash equilibrium for twoplayer turn...
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Short and Wide Network Paths
Network flow is a powerful mathematical framework to systematically expl...
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Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation
We consider the task of tensor estimation, i.e. estimating a lowrank 3...
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mRSC: Multidimensional Robust Synthetic Control
When evaluating the impact of a policy on a metric of interest, it may n...
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Time Series Predict DB
In this work, we are motivated to make predictive functionalities native...
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Model Agnostic HighDimensional ErrorinVariable Regression
We consider the problem of highdimensional errorinvariable regression...
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On Reinforcement Learning Using Monte Carlo Tree Search with Supervised Learning: NonAsymptotic Analysis
Inspired by the success of AlphaGo Zero (AGZ) which utilizes Monte Carlo...
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Learning Mixture Model with Missing Values and its Application to Rankings
We consider the question of learning mixtures of generic subgaussian di...
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Regret vs. Bandwidth Tradeoff for Recommendation Systems
We consider recommendation systems that need to operate under wireless b...
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Monotone Matrix Estimation via Robust Deconvolution
The goal of deconvolution is in estimating the distribution of a random ...
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Time Series Analysis via Matrix Estimation
We consider the task of interpolating and forecasting a time series in t...
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Qlearning with Nearest Neighbors
We consider the problem of modelfree reinforcement learning for infinit...
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Iterative Collaborative Filtering for Sparse Matrix Estimation
The sparse matrix estimation problem consists of estimating the distribu...
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Robust Synthetic Control
We present a robust generalization of the synthetic control method for c...
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Centralized Congestion Control and Scheduling in a Datacenter
We consider the problem of designing a packetlevel congestion control a...
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Unifying Framework for Crowdsourcing via Graphon Estimation
We consider the question of inferring true answers associated with tasks...
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A Latent Source Model for PatchBased Image Segmentation
Despite the popularity and empirical success of patchbased nearestneig...
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Structure learning of antiferromagnetic Ising models
In this paper we investigate the computational complexity of learning th...
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Learning Mixed Multinomial Logit Model from Ordinal Data
Motivated by generating personalized recommendations using ordinal (or p...
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A Latent Source Model for Online Collaborative Filtering
Despite the prevalence of collaborative filtering in recommendation syst...
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Learning graphical models from the Glauber dynamics
In this paper we consider the problem of learning undirected graphical m...
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Bayesian regression and Bitcoin
In this paper, we discuss the method of Bayesian regression and its effi...
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Hardness of parameter estimation in graphical models
We consider the problem of learning the canonical parameters specifying ...
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PartitionMerge: Distributed Inference and Modularity Optimization
This paper presents a novel meta algorithm, PartitionMerge (PM), which ...
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A Latent Source Model for Nonparametric Time Series Classification
For classifying time series, a nearestneighbor approach is widely used ...
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Rank Centrality: Ranking from Pairwise Comparisons
The question of aggregating pairwise comparisons to obtain a global ran...
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BudgetOptimal Task Allocation for Reliable Crowdsourcing Systems
Crowdsourcing systems, in which numerous tasks are electronically distri...
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Sparse Choice Models
Choice models, which capture popular preferences over objects of interes...
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Community Detection in Networks: The LeaderFollower Algorithm
Traditional spectral clustering methods cannot naturally learn the numbe...
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Belief Propagation for Mincost Network Flow: Convergence and Correctness
Message passing type algorithms such as the socalled Belief Propagation...
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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 ...
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