Search Results for author: Yuchen Zeng

Found 7 papers, 6 papers with code

LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks

1 code implementation14 Jun 2022 Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee

LIFT does not make any changes to the model architecture or loss function, and it solely relies on the natural language interface, enabling "no-code machine learning with LMs."

BIG-bench Machine Learning General Classification +2

The Expressive Power of Low-Rank Adaptation

1 code implementation26 Oct 2023 Yuchen Zeng, Kangwook Lee

Low-Rank Adaptation (LoRA), a parameter-efficient fine-tuning method that leverages low-rank adaptation of weight matrices, has emerged as a prevalent technique for fine-tuning pre-trained models such as large language models and diffusion models.

Improving Fairness via Federated Learning

2 code implementations29 Oct 2021 Yuchen Zeng, Hongxu Chen, Kangwook Lee

We then theoretically and empirically show that the performance tradeoff of FedAvg-based fair learning algorithms is strictly worse than that of a fair classifier trained on centralized data.

Fairness Federated Learning

Can MLLMs Perform Text-to-Image In-Context Learning?

1 code implementation2 Feb 2024 Yuchen Zeng, Wonjun Kang, Yicong Chen, Hyung Il Koo, Kangwook Lee

The evolution from Large Language Models (LLMs) to Multimodal Large Language Models (MLLMs) has spurred research into extending In-Context Learning (ICL) to its multimodal counterpart.

Image Generation In-Context Learning

Equal Improvability: A New Fairness Notion Considering the Long-term Impact

1 code implementation13 Oct 2022 Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee

In order to promote long-term fairness, we propose a new fairness notion called Equal Improvability (EI), which equalizes the potential acceptance rate of the rejected samples across different groups assuming a bounded level of effort will be spent by each rejected sample.

Fairness

Outlier-Robust Group Inference via Gradient Space Clustering

1 code implementation13 Oct 2022 Yuchen Zeng, Kristjan Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin

Traditional machine learning models focus on achieving good performance on the overall training distribution, but they often underperform on minority groups.

Clustering

Multiway clustering via tensor block models

no code implementations NeurIPS 2019 Miaoyan Wang, Yuchen Zeng

We consider the problem of identifying multiway block structure from a large noisy tensor.

Clustering

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