RUI GAO
13 papers · 2018–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (34)
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Research topics
Machine Learning
(12)
Optimization & Theory
(7)
Learning Types Β· Machine Learning
(6)
Application Areas
(5)
Mathematics & Optimization
(4)
Core Methods
(4)
Artificial Intelligence
(3)
Core AI
(3)
Deep Learning
(2)
Mathematics
(2)
Models
(2)
Optimization
(2)
Learning Types Β· Deep Learning
(1)
Probability
(1)
Keywords
generalization bound
(3)
distributionally robust optimization
(2)
wasserstein distance
(2)
uncertainty quantification
(2)
differential privacy
(2)
information theory
(2)
continual learning
(2)
stochastic gradient langevin dynamics
(2)
calibration
(1)
statistical inference
(1)
image classification
(1)
conformal prediction
(1)
few-shot learning
(1)
metric learning
(1)
federated learning
(1)
class-incremental learning
(1)
robust statistics
(1)
robust classification
(1)
cross-modal retrieval
(1)
epistemic uncertainty
(1)
Papers
Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
ICML 2025
Model Uncertainty Quantification by Conformal Prediction in Continual Learning
ICML 2025
High-Order Semantic Alignment for Unsupervised Fine-Grained Image-Text Retrieval
COLING 2024
SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic
ICML 2024
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions
NeurIPS 2023
DDGR: Continual Learning with Deep Diffusion-based Generative Replay
ICML 2023
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels
JMLR 2023
Distributionally robust weighted k-nearest neighbors
NeurIPS 2022
Two-Sample Test with Kernel Projected Wasserstein Distance
AISTATS 2022
Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels
NeurIPS 2021
Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators
NeurIPS 2021
Generalization Bounds for (Wasserstein) Robust Optimization
NeurIPS 2021
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
NeurIPS 2018