Yingyu Liang

Orcid: 0000-0003-1366-8686

According to our database1, Yingyu Liang authored at least 114 papers between 2008 and 2024.

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Bibliography

2024
Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study.
CoRR, 2024

Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent.
CoRR, 2024

Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix.
CoRR, 2024

HSR-Enhanced Sparse Attention Acceleration.
CoRR, 2024

Fine-grained Attention I/O Complexity: Comprehensive Analysis for Backward Passes.
CoRR, 2024

Looped ReLU MLPs May Be All You Need as Practical Programmable Computers.
CoRR, 2024

Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction.
CoRR, 2024

Multi-Layer Transformers Gradient Can be Approximated in Almost Linear Time.
CoRR, 2024

A Tighter Complexity Analysis of SparseGPT.
CoRR, 2024

Fast John Ellipsoid Computation with Differential Privacy Optimization.
CoRR, 2024

Do Large Language Models Have Compositional Ability? An Investigation into Limitations and Scalability.
CoRR, 2024

Differential Privacy of Cross-Attention with Provable Guarantee.
CoRR, 2024

Differential Privacy Mechanisms in Neural Tangent Kernel Regression.
CoRR, 2024

Toward Infinite-Long Prefix in Transformer.
CoRR, 2024

Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective.
CoRR, 2024

Tensor Attention Training: Provably Efficient Learning of Higher-order Transformers.
CoRR, 2024

Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers.
CoRR, 2024

Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond.
CoRR, 2024

Fourier Circuits in Neural Networks: Unlocking the Potential of Large Language Models in Mathematical Reasoning and Modular Arithmetic.
CoRR, 2024

Why Larger Language Models Do In-context Learning Differently?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
An Enhanced Current Differential Protection for AC Transmission Lines Connecting MMC-HVDC Stations.
IEEE Syst. J., March, 2023

Pilot Protection Based on Two-Dimensional Space Projection of Dual Differential Currents for Lines Connecting MMC-HVDC Stations.
IEEE Trans. Ind. Electron., 2023

Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection.
CoRR, 2023

Domain Generalization via Nuclear Norm Regularization.
CoRR, 2023

Provable Guarantees for Neural Networks via Gradient Feature Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

What Knowledge Gets Distilled in Knowledge Distillation?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis.
Proceedings of the International Conference on Machine Learning, 2023

Stratified Adversarial Robustness with Rejection.
Proceedings of the International Conference on Machine Learning, 2023

The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Attentive Walk-Aggregating Graph Neural Networks.
Trans. Mach. Learn. Res., 2022

Person Re-Identification Combined with Style Transfer and Pose Generation.
Int. J. Pattern Recognit. Artif. Intell., 2022

Person Re-Identification Method Based on the Construction of Graph Convolutional Network with Attribute Feature.
Int. J. Pattern Recognit. Artif. Intell., 2022

Siamese Network Object Tracking Algorithm Combining Attention Mechanism and Correlation Filter Theory.
Int. J. Pattern Recognit. Artif. Intell., 2022

On the identifiability of mixtures of ranking models.
CoRR, 2022

Deep Online Fused Video Stabilization.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Towards Evaluating the Robustness of Neural Networks Learned by Transduction.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Adaptive Mho Characteristic-Based Distance Protection for Lines Emanating From Photovoltaic Power Plants Under Unbalanced Faults.
IEEE Syst. J., 2021

Multi-Scale Anti-Occlusion Correlation Filters Object Tracking Method Based on Complementary Features.
Int. J. Pattern Recognit. Artif. Intell., 2021

An Analysis of Attentive Walk-Aggregating Graph Neural Networks.
CoRR, 2021

Towards Adversarial Robustness via Transductive Learning.
CoRR, 2021

ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A New View of Multi-modal Language Analysis: Audio and Video Features as Text "Styles".
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2020
Robust Out-of-distribution Detection via Informative Outlier Mining.
CoRR, 2020

Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation.
CoRR, 2020

SimpleTran: Transferring Pre-Trained Sentence Embeddings for Low Resource Text Classification.
CoRR, 2020

Robust Out-of-distribution Detection in Neural Networks.
CoRR, 2020

Functional Regularization for Representation Learning: A Unified Theoretical Perspective.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Beyond Fine-tuning: Few-Sample Sentence Embedding Transfer.
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, 2020

Gradients as Features for Deep Representation Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

PBoS: Probabilistic Bag-of-Subwords for Generalizing Word Embedding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Learning Entangled Single-Sample Gaussians in the Subset-of-Signals Model.
Proceedings of the Conference on Learning Theory, 2020

Can Adversarial Weight Perturbations Inject Neural Backdoors.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Learning Entangled Single-Sample Distributions via Iterative Trimming.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Sketching Transformed Matrices with Applications to Natural Language Processing.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Non-Convex Matrix Completion and Related Problems via Strong Duality.
J. Mach. Learn. Res., 2019

N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Robust Attribution Regularization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks.
Proceedings of the IEEE European Symposium on Security and Privacy, 2019

Shallow Domain Adaptive Embeddings for Sentiment Analysis.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Recovery Guarantees For Quadratic Tensors With Sparse Observations.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Linear Algebraic Structure of Word Senses, with Applications to Polysemy.
Trans. Assoc. Comput. Linguistics, 2018

Mapping between fMRI responses to movies and their natural language annotations.
NeuroImage, 2018

Recovery Guarantees for Quadratic Tensors with Limited Observations.
CoRR, 2018

N-Gram Graph, A Novel Molecule Representation.
CoRR, 2018

Improving Adversarial Robustness by Data-Specific Discretization.
CoRR, 2018

Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Matrix Completion and Related Problems via Strong Duality.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

Generalizing Word Embeddings using Bag of Subwords.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Learning Mixtures of Linear Regressions with Nearly Optimal Complexity.
Proceedings of the Conference On Learning Theory, 2018

A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Domain Adapted Word Embeddings for Improved Sentiment Classification.
Proceedings of the Workshop on Deep Learning Approaches for Low-Resource NLP, 2018

2017
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks.
J. Mach. Learn. Res., 2017

Optimal Sample Complexity for Matrix Completion and Related Problems via 𝓁s<sub>2</sub>-Regularization.
CoRR, 2017

Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations.
Proceedings of the 34th International Conference on Machine Learning, 2017

Differentially Private Clustering in High-Dimensional Euclidean Spaces.
Proceedings of the 34th International Conference on Machine Learning, 2017

Generalization and Equilibrium in Generative Adversarial Nets (GANs).
Proceedings of the 34th International Conference on Machine Learning, 2017

A Simple but Tough-to-Beat Baseline for Sentence Embeddings.
Proceedings of the 5th International Conference on Learning Representations, 2017

Diverse Neural Network Learns True Target Functions.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
A Latent Variable Model Approach to PMI-based Word Embeddings.
Trans. Assoc. Comput. Linguistics, 2016

Clustering under Perturbation Resilience.
SIAM J. Comput., 2016

Mapping Between Natural Movie fMRI Responses and Word-Sequence Representations.
CoRR, 2016

Diversity Leads to Generalization in Neural Networks.
CoRR, 2016

Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Communication Efficient Distributed Kernel Principal Component Analysis.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Recovery guarantee of weighted low-rank approximation via alternating minimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning in indefinite proximity spaces - recent trends.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Distributed Kernel Principal Component Analysis.
CoRR, 2015

Why are deep nets reversible: A simple theory, with implications for training.
CoRR, 2015

Random Walks on Context Spaces: Towards an Explanation of the Mysteries of Semantic Word Embeddings.
CoRR, 2015

A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Modern aspects of unsupervised learning.
PhD thesis, 2014

Robust hierarchical clustering.
J. Mach. Learn. Res., 2014

Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning.
CoRR, 2014

Improved Distributed Principal Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Time-Varying Coverage Functions.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Scalable Kernel Methods via Doubly Stochastic Gradients.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Influence Function Learning in Information Diffusion Networks.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Continuous-Time Influence Maximization for Multiple Items.
CoRR, 2013

Distributed Clustering on Graphs.
CoRR, 2013

Modeling and Detecting Community Hierarchies.
Proceedings of the Similarity-Based Pattern Recognition - Second International Workshop, 2013

Distributed k-means and k-median clustering on general communication topologies.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Efficient Semi-supervised and Active Learning of Disjunctions.
Proceedings of the 30th International Conference on Machine Learning, 2013

2010
Learning Vocabulary-Based Hashing with AdaBoost.
Proceedings of the Advances in Multimedia Modeling, 2010

2009
THU-IMG at TRECVID 2009.
Proceedings of the TRECVID 2009 workshop participants notebook papers, 2009

Vocabulary-based hashing for image search.
Proceedings of the 17th International Conference on Multimedia 2009, 2009

2008


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