← Authors

Yaoliang Yu

68 papers · 2009–2026 · 13 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌈 Renaissance Researcher (9) 🐝 Cross-Pollinator (6) πŸƒ Academic Marathon (16) 🌍 Conference Polyglot (13) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (22) 🌟 Keyword Trendsetter Combo (7) 🏠 Conference Loyalist (22) πŸ”¬ Deep Specialist (10) πŸ† Grand Slam 🌱 Topic Pioneer πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ”₯ Unstoppable (14) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (67) ❓ The Questioner (3) πŸ—ƒοΈ Keyword Collector (107)

Conferences

NIPS (22) ICML (15) AISTATS (7) ICLR (5) ACL (4) EMNLP (3) JMLR (3) AAAI (2) CVPR (2) IJCNLP (2) EACL (1) IJCAI (1) NAACL (1)

Top co-authors

Jimmy Lin (9) Xinhua Zhang (9) Dale Schuurmans (9) Ji Xin (9) Yao-Liang Yu (8) Raphael Tang (6) Pascal Poupart (5) Eric Xing (4) Sun Sun (4) Eric P. Xing (4)

Keywords

convex optimization (9) model compression (6) gradient descent (5) density estimation (4) conditional gradient (4) proximal gradient (4) early exiting (3) semi-supervised learning (3) matrix completion (3) proximal maps (3) stochastic optimization (2) bregman divergence (2) image segmentation (2) metric learning (2) unsupervised learning (2) early exit (2) dimensionality reduction (2) adversarial robustness (2) neural network interpretability (2) robust regression (2)

Papers

Demystifying Foreground-Background Memorization in Diffusion Models AAAI 2026
Leveraging Variable Sparsity to Refine Pareto Stationarity in Multi-Objective Optimization ICLR 2025
A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD ICML 2025
Diffusion Models under Group Transformations AISTATS 2025
Last-iterate Convergence in Regularized Graphon Mean Field Game AAAI 2025
Stochastic Forward–Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets ICML 2025
Disguised Copyright Infringement of Latent Diffusion Models ICML 2024
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning ICML 2024
One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently NIPS 2024
Faster Approximation of Probabilistic and Distributional Values via Least Squares ICLR 2024
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games AISTATS 2024
Operator Selection and Ordering in a Pipeline Approach to Efficiency Optimizations for Transformers ACL 2023
Batchnorm Allows Unsupervised Radial Attacks NIPS 2023
Functional Renyi Differential Privacy for Generative Modeling NIPS 2023
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers NIPS 2023
Robust Data Valuation with Weighted Banzhaf Values NIPS 2023
Multi-Objective Reinforcement Learning: Convexity, Stationarity and Pareto Optimality ICLR 2023
Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks ICML 2023
Revisiting flow generative models for Out-of-distribution detection ICLR 2022
OLALA: Object-Level Active Learning for Efficient Document Layout Annotation EMNLP 2022
Optimality and Stability in Non-Convex Smooth Games JMLR 2022
Demystifying and Generalizing BinaryConnect NIPS 2021
BERxiT: Early Exiting for BERT with Better Fine-Tuning and Extension to Regression EACL 2021
The Art of Abstention: Selective Prediction and Error Regularization for Natural Language Processing IJCNLP 2021
Quantifying and Improving Transferability in Domain Generalization NIPS 2021
S$^3$: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks NIPS 2021
Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training NIPS 2021
The Art of Abstention: Selective Prediction and Error Regularization for Natural Language Processing ACL 2021
Posterior Differential Regularization with f-divergence for Improving Model Robustness NAACL 2021
Unsupervised Multilingual Alignment using Wasserstein Barycenter IJCAI 2020
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference ACL 2020
Showing Your Work Doesn’t Always Work ACL 2020
Early Exiting BERT for Efficient Document Ranking EMNLP 2020
Stronger and Faster Wasserstein Adversarial Attacks ICML 2020
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space ICML 2020
On Minimax Optimality of GANs for Robust Mean Estimation AISTATS 2020
Tails of Lipschitz Triangular Flows ICML 2020
Convergence of Gradient Methods on Bilinear Zero-Sum Games ICLR 2020
Least Squares Estimation of Weakly Convex Functions AISTATS 2019
What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Neurons EMNLP 2019
Sum-of-Squares Polynomial Flow ICML 2019
Distributional Reinforcement Learning for Efficient Exploration ICML 2019
What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Neurons IJCNLP 2019
Multivariate Triangular Quantile Maps for Novelty Detection NIPS 2019
Inductive Two-Layer Modeling with Parametric Bregman Transfer ICML 2018
Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters JMLR 2018
Deep Homogeneous Mixture Models: Representation, Separation, and Approximation NIPS 2018
Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction NIPS 2017
Learning Latent Space Models with Angular Constraints ICML 2017
Generalized Conditional Gradient for Sparse Estimation JMLR 2017
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data CVPR 2017
On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System AISTATS 2016
Convex Two-Layer Modeling with Latent Structure NIPS 2016
Scalable and Sound Low-Rank Tensor Learning AISTATS 2016
Closed-Form Training of Mahalanobis Distance for Supervised Clustering CVPR 2016
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA ICML 2016
Minimizing Nonconvex Non-Separable Functions AISTATS 2015
Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM ICML 2015
Efficient Structured Matrix Rank Minimization NIPS 2014
On Decomposing the Proximal Map NIPS 2013
Characterizing the Representer Theorem ICML 2013
Better Approximation and Faster Algorithm Using the Proximal Average NIPS 2013
Polar Operators for Structured Sparse Estimation NIPS 2013
Accelerated Training for Matrix-norm Regularization: A Boosting Approach NIPS 2012
A Polynomial-time Form of Robust Regression NIPS 2012
Convex Multi-view Subspace Learning NIPS 2012
Relaxed Clipping: A Global Training Method for Robust Regression and Classification NIPS 2010
A General Projection Property for Distribution Families NIPS 2009