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09/12/2023
On Computationally Efficient Learning of Exponential Family Distributions
We consider the classical problem of learning, with arbitrary accuracy, ...
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06/07/2023
Exploiting Observation Bias to Improve Matrix Completion
We consider a variant of matrix completion where entries are revealed in...
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06/02/2023
Auditing for Human Expertise
High-stakes prediction tasks (e.g., patient diagnosis) are often handled...
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05/25/2023
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise
The well-established practice of time series analysis involves estimatin...
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04/20/2023
A User-Driven Framework for Regulating and Auditing Social Media
People form judgments and make decisions based on the information that t...
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02/04/2023
Counterfactual Identifiability of Bijective Causal Models
We study counterfactual identifiability in causal models with bijective ...
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02/04/2023
Matrix Estimation for Individual Fairness
In recent years, multiple notions of algorithmic fairness have arisen. O...
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11/25/2022
Doubly robust nearest neighbors in factor models
In this technical note, we introduce an improved variant of nearest neig...
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11/14/2022
On counterfactual inference with unobserved confounding
Given an observational study with n independent but heterogeneous units ...
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10/20/2022
Network Synthetic Interventions: A Framework for Panel Data with Network Interference
We propose a generalization of the synthetic controls and synthetic inte...
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06/16/2022
Gradient Descent for Low-Rank Functions
Several recent empirical studies demonstrate that important machine lear...
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03/29/2022
Current Implicit Policies May Not Eradicate COVID-19
Successful predictive modeling of epidemics requires an understanding of...
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02/14/2022
Counterfactual inference for sequential experimental design
We consider the problem of counterfactual inference in sequentially desi...
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01/07/2022
Unifying Epidemic Models with Mixtures
The COVID-19 pandemic has emphasized the need for a robust understanding...
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01/06/2022
Federated Optimization of Smooth Loss Functions
In this work, we study empirical risk minimization (ERM) within a federa...
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01/05/2022
CausalSim: Unbiased Trace-Driven Network Simulation
Evaluating the real-world performance of network protocols is challengin...
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12/29/2021
Time varying regression with hidden linear dynamics
We revisit a model for time-varying linear regression that assumes the u...
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10/28/2021
A Computationally Efficient Method for Learning Exponential Family Distributions
We consider the question of learning the natural parameters of a k param...
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09/30/2021
Causal Matrix Completion
Matrix completion is the study of recovering an underlying matrix from a...
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02/19/2021
Approximating the Log-Partition Function
Variational approximation, such as mean-field (MF) and tree-reweighted (...
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02/13/2021
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
We consider offline reinforcement learning (RL) with heterogeneous agent...
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02/11/2021
Regret, stability, and fairness in matching markets with bandit learners
We consider the two-sided matching market with bandit learners. In the s...
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11/05/2020
Causal Imputation via Synthetic Interventions
Consider the problem of determining the effect of a drug on a specific c...
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11/04/2020
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression
In this paper, we consider the problem of empirical risk minimization (E...
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10/28/2020
On Learning Continuous Pairwise Markov Random Fields
We consider learning a sparse pairwise Markov Random Field (MRF) with co...
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10/27/2020
On Principal Component Regression in a High-Dimensional Error-in-Variables Setting
We analyze the classical method of Principal Component Regression (PCR) ...
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06/24/2020
On Multivariate Singular Spectrum Analysis
We analyze a variant of multivariate singular spectrum analysis (mSSA), ...
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06/17/2020
Regulating algorithmic filtering on social media
Through the algorithmic filtering (AF) of content, social media platform...
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06/15/2020
Estimation of Skill Distributions
In this paper, we study the problem of learning the skill distribution o...
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06/13/2020
Synthetic Interventions
We develop a method to help quantify the impact different levels of mobi...
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06/11/2020
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
We consider the question of learning Q-function in a sample efficient ma...
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06/08/2020
Stable Reinforcement Learning with Unbounded State Space
We consider the problem of reinforcement learning (RL) with unbounded st...
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04/30/2020
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...
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02/25/2020
On Reinforcement Learning for Turn-based Zero-sum Markov Games
We consider the problem of finding Nash equilibrium for two-player turn-...
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11/01/2019
Short and Wide Network Paths
Network flow is a powerful mathematical framework to systematically expl...
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08/03/2019
Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation
We consider the task of tensor estimation, i.e. estimating a low-rank 3-...
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05/15/2019
mRSC: Multi-dimensional Robust Synthetic Control
When evaluating the impact of a policy on a metric of interest, it may n...
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03/17/2019
Time Series Predict DB
In this work, we are motivated to make predictive functionalities native...
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02/28/2019
Model Agnostic High-Dimensional Error-in-Variable Regression
We consider the problem of high-dimensional error-in-variable regression...
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02/14/2019
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...
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12/31/2018
Learning Mixture Model with Missing Values and its Application to Rankings
We consider the question of learning mixtures of generic sub-gaussian di...
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10/15/2018
Regret vs. Bandwidth Trade-off for Recommendation Systems
We consider recommendation systems that need to operate under wireless b...
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03/09/2018
Monotone Matrix Estimation via Robust Deconvolution
The goal of deconvolution is in estimating the distribution of a random ...
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02/25/2018
Time Series Analysis via Matrix Estimation
We consider the task of interpolating and forecasting a time series in t...
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02/12/2018
Q-learning with Nearest Neighbors
We consider the problem of model-free reinforcement learning for infinit...
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12/03/2017
Iterative Collaborative Filtering for Sparse Matrix Estimation
The sparse matrix estimation problem consists of estimating the distribu...
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11/18/2017
Robust Synthetic Control
We present a robust generalization of the synthetic control method for c...
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10/06/2017
Centralized Congestion Control and Scheduling in a Datacenter
We consider the problem of designing a packet-level congestion control a...
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03/23/2017
Unifying Framework for Crowd-sourcing via Graphon Estimation
We consider the question of inferring true answers associated with tasks...
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10/06/2015