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Devavrat Shah

40 papers · 2007–2025 · 8 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (8) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (26) 🌟 Keyword Trendsetter Combo (5) 🏠 Conference Loyalist (26) πŸ† Keyword Champion 🌱 Topic Pioneer πŸ’Ž Century Club (40) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (88) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (10) ⚑ Prolific Year (6) πŸ“ˆ Trend Setter

Conferences

NIPS (26) AISTATS (3) COLT (2) ICML (2) JMLR (2) L4DC (2) NSDI (2) CLEAR (1)

Top co-authors

Dennis Shen (6) Anish Agarwal (6) Abdullah Alomar (4) Sewoong Oh (3) Dogyoon Song (3) Christina E. Lee (3) Guy Bresler (3) Zhi Xu (3) Kyomin Jung (2) Gregory Wornell (2)

Research topics

Methods (1) Statistics (1)

Keywords

combinatorial optimization (5) graphical model (5) causal inference (4) markov random field (4) matrix completion (4) collaborative filtering (3) graph algorithm (3) matrix estimation (3) singular value thresholding (3) preference learning (3) parameter estimation (3) exponential family (3) pairwise comparison (3) reinforcement learning (3) approximate inference (2) online learning (2) nearest neighbor (2) partition function (2) message passing (2) map estimation (2)

Papers

On Model Identification and Out-of-Sample Prediction of PCR with Applications to Synthetic Controls JMLR 2025
Human Expertise in Algorithmic Prediction NIPS 2024
Matrix Estimation for Individual Fairness ICML 2023
Counterfactual Identifiability of Bijective Causal Models ICML 2023
Causal Matrix Completion COLT 2023
Auditing for Human Expertise NIPS 2023
CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation NSDI 2023
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise NIPS 2023
Regret, stability & fairness in matching markets with bandit learners AISTATS 2022
Time Varying Regression with Hidden Linear Dynamics L4DC 2022
Causal Imputation via Synthetic Interventions CLEAR 2022
A Computationally Efficient Method for Learning Exponential Family Distributions NIPS 2021
Regulating algorithmic filtering on social media NIPS 2021
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators NIPS 2021
Change Point Detection via Multivariate Singular Spectrum Analysis NIPS 2021
On Learning Continuous Pairwise Markov Random Fields AISTATS 2021
Quantifying Variational Approximation for Log-Partition Function COLT 2021
Stable Reinforcement Learning with Unbounded State Space L4DC 2020
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation NIPS 2020
Estimation of Skill Distribution from a Tournament NIPS 2020
On Robustness of Principal Component Regression NIPS 2019
Reducing Crowdsourcing to Graphon Estimation, Statistically AISTATS 2018
Q-learning with Nearest Neighbors NIPS 2018
Robust Synthetic Control JMLR 2018
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation NIPS 2017
Flowtune: Flowlet Control for Datacenter Networks NSDI 2017
Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering NIPS 2016
Structure learning of antiferromagnetic Ising models NIPS 2014
Learning Mixed Multinomial Logit Model from Ordinal Data NIPS 2014
A Latent Source Model for Online Collaborative Filtering NIPS 2014
Hardness of parameter estimation in graphical models NIPS 2014
A Latent Source Model for Nonparametric Time Series Classification NIPS 2013
Computing the Stationary Distribution Locally NIPS 2013
Iterative ranking from pair-wise comparisons NIPS 2012
Iterative Learning for Reliable Crowdsourcing Systems NIPS 2011
A Data-Driven Approach to Modeling Choice NIPS 2009
Local Rules for Global MAP: When Do They Work ? NIPS 2009
Inferring rankings under constrained sensing NIPS 2008
Message Passing for Max-weight Independent Set NIPS 2007
Local Algorithms for Approximate Inference in Minor-Excluded Graphs NIPS 2007