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Found 9 papers, 1 papers with code
Doubly Robust Structure Identification from Temporal Data
Furthermore, potential causes may be correlated in practical applications.
Diffusion Based Causal Representation Learning
Causal reasoning can be considered a cornerstone of intelligent systems.
DRCFS: Doubly Robust Causal Feature Selection
Knowing the features of a complex system that are highly relevant to a particular target variable is of fundamental interest in many areas of science.
Optimal Transport for Correctional Learning
In this framework, an expert agent, referred to as the teacher, modifies the data used by a learning agent, known as the student, to improve its estimation process.
Learning Counterfactually Invariant Predictors
Notions of counterfactual invariance (CI) have proven essential for predictors that are fair, robust, and generalizable in the real world.
Fast Feature Selection with Fairness Constraints
We study the fundamental problem of selecting optimal features for model construction.
Adaptive Sampling for Fast Constrained Maximization of Submodular Function
Our algorithm is suitable to maximize a non-monotone submodular function under a $p$-system side constraint, and it achieves a $(p + O(\sqrt{p}))$-approximation for this problem, after only poly-logarithmic adaptive rounds and polynomial queries to the valuation oracle function.
Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings
We show that our proposed algorithm competes with the state-of-the-art in static settings.
Approximating Optimization Problems using EAs on Scale-Free Networks
It has been observed that many complex real-world networks have certain properties, such as a high clustering coefficient, a low diameter, and a power-law degree distribution.
