6 papers · 1 filter
Nonlinear Axiomatic Attribution for Cooperative Games
Weida Li, Zhuanghua Liu, Yaoliang Yu +1
The Shapley value is a widely used concept in attribution problems, as it uniquely satisfies the axioms of linearity, consistency, equal treatment, and efficiency. Often, the inclu…
Adalina: Adaptive Linear Approximation for the Shapley Value and Beyond
Weida Li, Yaoliang Yu, Bryan Kian Hsiang Low
The Shapley value, and its broader family of semi-values, has received much attention in various attribution problems. A fundamental and long-standing challenge is their efficient…
TreeGrad-Ranker: Feature Ranking via -Time Gradients for Decision Trees
Weida Li, Yaoliang Yu, Bryan Kian Hsiang Low
We revisit the use of probabilistic values, which include the well-known Shapley and Banzhaf values, to rank features for explaining the local predicted values of decision trees. T…
Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning
Yuhui Wang, Qingyuan Wu, Dylan R. Ashley +4
The Value Iteration Network (VIN) is an end-to-end differentiable neural network architecture for planning. It exhibits strong generalization to unseen domains by incorporating a d…
One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently
Weida Li, Yaoliang Yu
The concept of probabilistic values, such as Beta Shapley values and weighted Banzhaf values, has gained recent attention in applications like feature attribution and data valuatio…
Highway Value Iteration Networks
Yuhui Wang, Weida Li, Francesco Faccio +2
Value iteration networks (VINs) enable end-to-end learning for planning tasks by employing a differentiable "planning module" that approximates the value iteration algorithm. Howev…