182 citations · 625 across the 44 of their papers we have counts for
10 papers · 1 filter
Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation
Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang +2
Data valuation aims to quantify the usefulness of individual data sources in training machine learning (ML) models, and is a critical aspect of data-centric ML research. However, d…
Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar +2
Current literature, aiming to surpass the "Chain-of-Thought" approach, often resorts to external modi operandi involving halting, modifying, and then resuming the generation proces…
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…
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources
Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu +1
Traditionally, data selection has been studied in settings where all samples from prospective sources are fully revealed to a machine learning developer. However, in practical data…
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
Junyuan Hong, Yi Zeng, Shuyang Yu +3
Data-free knowledge distillation (KD) helps transfer knowledge from a pre-trained model (known as the teacher model) to a smaller model (known as the student model) without access…
LAVA: Data Valuation without Pre-Specified Learning Algorithms
Hoang Anh Just, Feiyang Kang, Jiachen T. Wang +4
Traditionally, data valuation (DV) is posed as a problem of equitably splitting the validation performance of a learning algorithm among the training data. As a result, the calcula…
A Randomized Approach for Tight Privacy Accounting
Jiachen T. Wang, Saeed Mahloujifar, Tong Wu +2
Bounding privacy leakage over compositions, i.e., privacy accounting, is a key challenge in differential privacy (DP). The privacy parameter ($\eps$ or ) is often easy to estima…
A Note on "Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms"
Jiachen T. Wang, Ruoxi Jia
Data valuation is a growing research field that studies the influence of individual data points for machine learning (ML) models. Data Shapley, inspired by cooperative game theory…
A Note on "Towards Efficient Data Valuation Based on the Shapley Value''
Jiachen T. Wang, Ruoxi Jia
The Shapley value (SV) has emerged as a promising method for data valuation. However, computing or estimating the SV is often computationally expensive. To overcome this challenge,…
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms
Minzhou Pan, Yi Zeng, Lingjuan Lyu +2
Backdoor data detection is traditionally studied in an end-to-end supervised learning (SL) setting. However, recent years have seen the proliferating adoption of self-supervised le…