Linglong Kong
21 papers · 2019–2025 · 8 conferences · across top CS/AI conferences
Achievements
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(38)
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Interdisciplinary Bridge
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(16)
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(8)
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(86)
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Century Club
(21)
Conferences
NIPS (6)
AAAI (5)
ICML (5)
AISTATS (1)
ICLR (1)
IJCAI (1)
JMLR (1)
NAACL (1)
Top co-authors
Research topics
Keywords
gaussian differential privacy
(3)
stochastic gradient descent
(2)
confidence interval
(2)
differential privacy
(2)
streaming datum
(2)
social bia
(2)
deep reinforcement learning
(2)
distributional reinforcement learning
(2)
gender bia
(2)
statistical inference
(1)
feature selection
(1)
natural language processing
(1)
text generation
(1)
masked language model
(1)
algorithmic fairness
(1)
causal inference
(1)
ensemble learning
(1)
utility optimization
(1)
conformal prediction
(1)
risk-aware learning
(1)
Papers
Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data
AISTATS 2025
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
ICML 2025
CBMA: Improving Conformal Prediction through Bayesian Model Averaging
ICLR 2025
Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations
NAACL 2024
Distributional Reinforcement Learning with Regularized Wasserstein Loss
NIPS 2024
Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach
NIPS 2024
Analysis of Differentially Private Synthetic Data: A Measurement Error Approach
AAAI 2024
Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility
AAAI 2024
Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
ICML 2024
Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data
ICML 2024
Inference on High-dimensional Single-index Models with Streaming Data
JMLR 2024
Opposite Online Learning via Sequentially Integrated Stochastic Gradient Descent Estimators
AAAI 2023
Gaussian Differential Privacy on Riemannian Manifolds
NIPS 2023
Online Local Differential Private Quantile Inference via Self-normalization
ICML 2023
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving
AAAI 2022
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy
NIPS 2022
Conformalized Fairness via Quantile Regression
NIPS 2022
Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability
AAAI 2022
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization
NIPS 2021
Ensemble-based Ultrahigh-dimensional Variable Screening
IJCAI 2019
Distributional Reinforcement Learning for Efficient Exploration
ICML 2019