Yun Yang
32 papers · 2018–2026 · 13 conferences · across top CS/AI conferences
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Conferences
AISTATS (8)
ICML (4)
COLT (3)
CVPR (3)
JMLR (3)
AAAI (2)
ICLR (2)
NIPS (2)
ACL (1)
EMNLP (1)
ICCV (1)
IJCAI (1)
NAACL (1)
Top co-authors
Research topics
Keywords
variational inference
(4)
semidefinite programming
(3)
bayesian inference
(3)
approximation algorithm
(2)
adversarial attack
(2)
gaussian mixture model
(2)
low-rank approximation
(2)
k-means clustering
(2)
minimax optimality
(2)
adversarial robustness
(2)
kernel ridge regression
(2)
nonparametric testing
(2)
self-attention mechanism
(2)
clustering algorithm
(2)
wasserstein distance
(2)
optimal transport
(2)
density estimation
(2)
convex optimization
(2)
mean-field approximation
(2)
deep neural network
(2)
Papers
EnViT: Enhancing the Performance of Early-Exit Vision Transformers via Exit-Aware Structured Dropout-Enabled Self-Distillation
AAAI 2026
CLeVeR: Multi-modal Contrastive Learning for Vulnerability Code Representation
ACL 2025
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
ICML 2025
Testing Conditional Mean Independence Using Generative Neural Networks
ICML 2025
Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation
ICLR 2025
Personalized Question Answering with User Profile Generation and Compression
EMNLP 2025
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow
AISTATS 2024
On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling
JMLR 2024
Adaptivity of Diffusion Models to Manifold Structures
AISTATS 2024
Wasserstein Proximal Coordinate Gradient Algorithms
JMLR 2024
Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming
ICLR 2024
A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
ICML 2023
Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data
ICML 2023
Robust Temporal Smoothness in Multi-Task Learning
AAAI 2023
Global and Local Mixture Consistency Cumulative Learning for Long-Tailed Visual Recognitions
CVPR 2023
Gaussian Processes with Errors in Variables: Theory and Computation
JMLR 2023
Minimax Nonparametric Two-Sample Test under Adversarial Losses
AISTATS 2023
Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences
NAACL 2022
Structured variational inference in Bayesian state-space models
AISTATS 2022
Mean-field nonparametric estimation of interacting particle systems
COLT 2022
Sketch-and-lift: scalable subsampled semidefinite program for K-means clustering
AISTATS 2022
Wasserstein $K$-means for clustering probability distributions
NIPS 2022
Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink
CVPR 2021
Fast Statistical Leverage Score Approximation in Kernel Ridge Regression
AISTATS 2021
Accumulations of ProjectionsβA Unified Framework for Random Sketches in Kernel Ridge Regression
AISTATS 2021
On Empirical Bayes Variational Autoencoder: An Excess Risk Bound
COLT 2021
Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method
NIPS 2021
AdvDrop: Adversarial Attack to DNNs by Dropping Information
ICCV 2021
Adversarial Camouflage: Hiding Physical-World Attacks With Natural Styles
CVPR 2020
Non-asymptotic Analysis for Nonparametric Testing
COLT 2020
Discovering Regularities from Traditional Chinese Medicine Prescriptions via Bipartite Embedding Model
IJCAI 2019
On Statistical Optimality of Variational Bayes
AISTATS 2018