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Yingyu Liang

63 papers · 2013–2025 · 15 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer πŸƒ Academic Marathon (12) 🌈 Renaissance Researcher (7) 🌍 Conference Polyglot (15) 🐝 Cross-Pollinator (7) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (14) 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (4) 🀝 Dynamic Duo (20) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ”¬ Deep Specialist (14) πŸ”₯ Unstoppable (13) πŸš€ Conference Pioneer ⚑ Prolific Year (8) ❓ The Questioner (4) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (222) πŸ’Ž Century Club (63)

Conferences

NIPS (14) ICML (12) AISTATS (8) EMNLP (6) ICLR (6) JMLR (3) AAAI (2) ACL (2) COLT (2) ICCV (2) WACV (2) AACL (1) EACL (1) IJCNLP (1) UAI (1)

Top co-authors

Zhenmei Shi (20) Zhao Song (15) Xi Wu (6) Jiefeng Chen (6) Somesh Jha (6) Le Song (6) Yuanzhi Li (6) Zhizhou Sha (5) Xiaoyu Li (5) Junyi Wei (4)

Research topics

Optimization & Theory (1)

Keywords

word embedding (6) domain adaptation (5) neural network (5) neural tangent kernel (4) sentiment analysis (4) sample complexity (4) k-means clustering (3) learning theory (3) representation learning (3) transfer learning (3) kernel methods (3) canonical correlation analysis (3) emotion recognition (2) stochastic optimization (2) text classification (2) stochastic gradient (2) differential privacy (2) transformer architecture (2) adversarial robustness (2) semi-supervised learning (2)

Papers

Learning to Inference Adaptively for Multimodal Large Language Models ICCV 2025
Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective ICCV 2025
Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers EMNLP 2025
Circuit Complexity Bounds for RoPE-based Transformer Architecture EMNLP 2025
Towards Infinite-Long Prefix in Transformer EMNLP 2025
Differential Privacy Mechanisms in Neural Tangent Kernel Regression WACV 2025
Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix ICLR 2025
NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism UAI 2025
Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation Abilities ICML 2025
Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies ICML 2025
Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs AISTATS 2025
Looped ReLU MLPs May Be All You Need as Practical Programmable Computers AISTATS 2025
When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time? AISTATS 2025
Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent AISTATS 2025
Why Larger Language Models Do In-context Learning Differently? ICML 2024
Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection ICML 2024
Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning ICLR 2024
Stratified Adversarial Robustness with Rejection ICML 2023
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning ICLR 2023
What Knowledge Gets Distilled in Knowledge Distillation? NIPS 2023
Provable Guarantees for Neural Networks via Gradient Feature Learning NIPS 2023
When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis ICML 2023
A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features ICLR 2022
Towards Evaluating the Robustness of Neural Networks Learned by Transduction ICLR 2022
Deep Online Fused Video Stabilization WACV 2022
A New View of Multi-modal Language Analysis: Audio and Video Features as Text β€œStyles” EACL 2021
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles NIPS 2021
Gradients as Features for Deep Representation Learning ICLR 2020
Functional Regularization for Representation Learning: A Unified Theoretical Perspective NIPS 2020
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis AAAI 2020
Beyond Fine-tuning: Few-Sample Sentence Embedding Transfer AACL 2020
Sketching Transformed Matrices with Applications to Natural Language Processing AISTATS 2020
Learning Entangled Single-Sample Distributions via Iterative Trimming AISTATS 2020
Learning Entangled Single-Sample Gaussians in the Subset-of-Signals Model COLT 2020
PBoS: Probabilistic Bag-of-Subwords for Generalizing Word Embedding EMNLP 2020
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning AAAI 2019
Shallow Domain Adaptive Embeddings for Sentiment Analysis IJCNLP 2019
Recovery Guarantees For Quadratic Tensors With Sparse Observations AISTATS 2019
Robust Attribution Regularization NIPS 2019
Non-Convex Matrix Completion and Related Problems via Strong Duality JMLR 2019
Shallow Domain Adaptive Embeddings for Sentiment Analysis EMNLP 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers NIPS 2019
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules NIPS 2019
Learning Mixtures of Linear Regressions with Nearly Optimal Complexity COLT 2018
Generalizing Word Embeddings using Bag of Subwords EMNLP 2018
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors ACL 2018
Domain Adapted Word Embeddings for Improved Sentiment Classification ACL 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data NIPS 2018
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations ICML 2017
Diverse Neural Network Learns True Target Functions AISTATS 2017
Generalization and Equilibrium in Generative Adversarial Nets (GANs) ICML 2017
Differentially Private Clustering in High-Dimensional Euclidean Spaces ICML 2017
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks JMLR 2017
Recovery guarantee of weighted low-rank approximation via alternating minimization ICML 2016
Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates NIPS 2016
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients NIPS 2015
Scalable Kernel Methods via Doubly Stochastic Gradients NIPS 2014
Robust Hierarchical Clustering JMLR 2014
Influence Function Learning in Information Diffusion Networks ICML 2014
Improved Distributed Principal Component Analysis NIPS 2014
Learning Time-Varying Coverage Functions NIPS 2014
Distributed $k$-means and $k$-median Clustering on General Topologies NIPS 2013
Efficient Semi-supervised and Active Learning of Disjunctions ICML 2013