most cited2D-Shapley: A Framework for Fragmented Data Valuation

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML2024

Uncertainty Quantification of Data Shapley via Statistical Inference

Mengmeng Wu, Zhihong Liu, Xiang Li +2

As data plays an increasingly pivotal role in decision-making, the emergence of data markets underscores the growing importance of data valuation. Within the machine learning lands…

math.OC2024

Anderson Acceleration Without Restart: A Novel Method with -Step Super Quadratic Convergence Rate

Haishan Ye, Dachao Lin, Xiangyu Chang +1

In this paper, we propose a novel Anderson's acceleration method to solve nonlinear equations, which does \emph{not} require a restart strategy to achieve numerical stability. We p…

cs.LG2024

Plug-and-Play Transformer Modules for Test-Time Adaptation

Xiangyu Chang, Sk Miraj Ahmed, Srikanth V. Krishnamurthy +4

Parameter-efficient tuning (PET) methods such as LoRA, Adapter, and Visual Prompt Tuning (VPT) have found success in enabling adaptation to new domains by tuning small modules with…

cs.LG20231 cited

2D-Shapley: A Framework for Fragmented Data Valuation

Zhihong Liu, Hoang Anh Just, Xiangyu Chang +2

Data valuation -- quantifying the contribution of individual data sources to certain predictive behaviors of a model -- is of great importance to enhancing the transparency of mach…

stat.ME2023

Subsampling-Based Modified Bayesian Information Criterion for Large-Scale Stochastic Block Models

Jiayi Deng, Danyang Huang, Xiangyu Chang +1

Identifying the number of communities is a fundamental problem in community detection, which has received increasing attention recently. However, rapid advances in technology have…