Tao Lin

Affiliations

EPFLHarvard UniversityPeking University

papers

2,055

total citations

papers (21)

Ensemble Distillation for Robust Model Fusion in Federated Learning

NEURIPS 2020arXiv

1,349

citations

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning

NEURIPS 2021arXiv

125

citations

On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm

CVPR 2024arXiv

citations

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them

NEURIPS 2020arXiv

citations

No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier

ICCV 2023arXiv

citations

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering

ICML 2024arXiv

citations

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

CVPR 2025arXiv

citations

Multi-Sender Persuasion: A Computational Perspective

ICML 2024arXiv

citations

Learning Utilities and Equilibria in Non-Truthful Auctions

NEURIPS 2020arXiv

citations

GIFT: Unlocking Full Potential of Labels in Distilled Dataset at Near-zero Cost

ICLR 2025arXiv

citations

ELICIT: LLM Augmentation Via External In-context Capability

ICLR 2025arXiv

citations

A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling

NEURIPS 2020arXiv

citations

Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors

ECCV 2024arXiv

citations

Learn How to Query from Unlabeled Data Streams in Federated Learning

AAAI 2025arXiv

citations

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing

ICCV 2025arXiv

citations

CollabEdit: Towards Non-destructive Collaborative Knowledge Editing

ICLR 2025arXiv

citations

Sample Complexity of Forecast Aggregation

NEURIPS 2023arXiv

citations

Tao Lin

Affiliations

papers (21)

Ensemble Distillation for Robust Model Fusion in Federated Learning

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning

On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them

No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier

Adversarial training for high-stakes reliability

RelaySum for Decentralized Deep Learning on Heterogeneous Data

DELTA: Diverse Client Sampling for Fasting Federated Learning

STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Multi-Sender Persuasion: A Computational Perspective

Learning Utilities and Equilibria in Non-Truthful Auctions

GIFT: Unlocking Full Potential of Labels in Distilled Dataset at Near-zero Cost

ELICIT: LLM Augmentation Via External In-context Capability

A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling

Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors

Learn How to Query from Unlabeled Data Streams in Federated Learning

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing

CollabEdit: Towards Non-destructive Collaborative Knowledge Editing

Sample Complexity of Forecast Aggregation

papers (21)

Ensemble Distillation for Robust Model Fusion in Federated Learning

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning

On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them

No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier

Adversarial training for high-stakes reliability

RelaySum for Decentralized Deep Learning on Heterogeneous Data

DELTA: Diverse Client Sampling for Fasting Federated Learning

STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Multi-Sender Persuasion: A Computational Perspective

Learning Utilities and Equilibria in Non-Truthful Auctions

GIFT: Unlocking Full Potential of Labels in Distilled Dataset at Near-zero Cost

ELICIT: LLM Augmentation Via External In-context Capability

A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling

Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors

Learn How to Query from Unlabeled Data Streams in Federated Learning

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing

CollabEdit: Towards Non-destructive Collaborative Knowledge Editing

Sample Complexity of Forecast Aggregation