Differentially private and incentive compatible recommendation system for the adoption of network goods. - Kevin He; Xiaosheng Mu (EC, 2014)

Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates. - Kevin He; Yanming Li; Ji Zhu; Hongliang Liu; Jeffrey E. Lee; Christopher I. Amos; Terry Hyslop; Jiashun Jin; Huazhen Lin; Qinyi Wei; Yi Li 019 (Bioinform., 2016)

Classification with Ultrahigh-Dimensional Features. - Yanming Li; Hyokyoung Grace Hong; Jian Kang; Kevin He; Ji Zhu; Yi Li 019 (CoRR, 2016)

Network Structure and Naive Sequential Learning. - Krishna Dasaratha; Kevin He (CoRR, 2017)

Mislearning from Censored Data: Gambler's Fallacy in a Search Problem. - Kevin He (CoRR, 2018)

Speed of Rational Social Learning in Networks with Gaussian Information. - Krishna Dasaratha; Kevin He (CoRR, 2019)

Covariance-insured screening. - Kevin He; Jian Kang; Hyokyoung Grace Hong; Ji Zhu; Yanming Li; Huazhen Lin; Han Xu; Yi Li 019 (Comput. Stat. Data Anal., 2019)

Payoff information and learning in signaling games. - Drew Fudenberg; Kevin He (Games Econ. Behav., 2020)

Generalized linear mixed models with Gaussian mixture random effects: Inference and application. - Lanfeng Pan; Yehua Li; Kevin He; Yanming Li; Yi Li 019 (J. Multivar. Anal., 2020)

SurvBoost: An R Package for High-Dimensional Variable Selection in the Stratified Proportional Hazards Model via Gradient Boosting. - Emily Morris; Kevin He; Yanming Li; Yi Li; Jian Kang (R J., 2020)

Aggregative Efficiency of Bayesian Learning in Networks. - Krishna Dasaratha; Kevin He (EC, 2021)

Evolutionarily Stable (Mis)specifications: Theory and Applications. - Kevin He; Jonathan Libgober (EC, 2021)

Kullback-Leibler-Based Discrete Relative Risk Models for Integration of Published Prediction Models with New Dataset. - Di Wang; Wen Ye; Kevin He (SPACA, 2021)

Cox-nnet v2.0: improved neural-network-based survival prediction extended to large-scale EMR data. - Di Wang; Zheng Jing; Kevin He; Lana X. Garmire (Bioinform., 2021)

An experiment on network density and sequential learning. - Krishna Dasaratha; Kevin He (Games Econ. Behav., 2021)

Advancement in predicting interactions between drugs used to treat psoriasis and its comorbidities by integrating molecular and clinical resources. - Matthew T. Patrick; Redina Bardhi; Kalpana Raja; Kevin He; Lam C. Tsoi (J. Am. Medical Informatics Assoc., 2021)

Player-compatible learning and player-compatible equilibrium. - Drew Fudenberg; Kevin He (J. Econ. Theory, 2021)

Network structure and social learning. - Krishna Dasaratha; Kevin He (SIGecom Exch., 2021)

Screening p-Hackers: Dissemination Noise as Bait. - Federico Echenique; Kevin He (EC, 2022)

Private Private Information. - Kevin He; Fedor Sandomirskiy; Omer Tamuz (EC, 2022)

Observability, dominance, and induction in learning models. - Daniel Clark; Drew Fudenberg; Kevin He (J. Econ. Theory, 2022)

Fast 2-out-of-n ECDSA Threshold Signature. - Lin Zhong; Yujue Wang; Jun Du; Daji Liang; Ziyuan Zhong; Kevin He; Andrew Zhang (ISPA/BDCloud/SocialCom/SustainCom, 2023)

Distributed Key Derivation for Multi-Party Management of Blockchain Digital Assets. - Lin Zhong; Yujue Wang; Yong Ding 005; Jun Du; Kevin He; Andrew Zhang (ICPADS, 2023)

Direct Collocation for Quantum Optimal Control. - Aaron Trowbridge; Aditya Bhardwaj; Kevin He; David I. Schuster; Zachary Manchester (QCE, 2023)

Late Breaking Results: Differential and Massively Parallel Sampling of SAT Formulas. - Arash Ardakani; Minwoo Kang; Kevin He; Vighnesh M. Iyer; Suhong Moon; John Wawrzynek (DAC, 2024)

A Distributed Stealth Address Generation Protocol for Threshold Signatures. - Yujue Wang; Lin Zhong; Jun Du; Yudi Zou; Kevin He; Andrew Zhang (ISPA, 2024)

Training-Aware Risk Control for Intensity Modulated Radiation Therapies Quality Assurance with Conformal Prediction. - Kevin He; David Adam; Sarah Han-Oh; Anqi Liu (ML4H@NeurIPS, 2024)

Learning from Viral Content. - Krishna Dasaratha; Kevin He (EC, 2024)

Competing Risk Modeling with Bivariate Varying Coefficients to Understand the Dynamic Impact of COVID-19. - Wenbo Wu; John D. Kalbfleisch; Jeremy M. G. Taylor; Jian Kang 003; Kevin He (J. Comput. Graph. Stat., 2024)

surtvep: An R package for estimating time-varying effects. - Lingfeng Luo; Wenbo Wu; Jeremy M. G. Taylor; Jian Kang; Michael J. Kleinsasser; Kevin He (J. Open Source Softw., 2024)

DEMOTIC: A Differentiable Sampler for Multi-Level Digital Circuits. - Arash Ardakani; Minwoo Kang; Kevin He; Qijing Huang 001; Vighnesh M. Iyer; Suhong Moon; John Wawrzynek (ASP-DAC, 2025)

High-Throughput SAT Sampling. - Arash Ardakani; Minwoo Kang; Kevin He; Qijing Huang 001; John Wawrzynek (DATE, 2025)

Human Misperception of Generative-AI Alignment: A Laboratory Experiment. - Kevin He; Ran Shorrer; Mengjia Xia (EC, 2025)

Recurrent CircuitSAT Sampling for Sequential Circuits. - Arash Ardakani; Kevin He; John Wawrzynek (CoRR, 2025)

Controlled Social Learning: Altruism vs. Bias. - Raghu Arghal; Kevin He; Shirin Saeedi Bidokhti; Saswati Sarkar (CoRR, 2025)

Implementation Considerations for Automated AI Grading of Student Work. - Zewei Tian; Alex Liu; Lief Esbenshade; Shawon Sarkar; Zachary Zhang; Kevin He; Min Sun (CoRR, 2025)

Decoding Instructional Dialogue: Human-AI Collaborative Analysis of Teacher Use of AI Tool at Scale. - Alex Liu; Lief Esbenshade; Shawon Sarkar; Victor Tian; Zachary Zhang; Kevin He; Min Sun (CoRR, 2025)