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Found 7 papers, 0 papers with code
Robust Black Box Explanations Under Distribution Shift
As machine learning black boxes are increasingly being deployed in real-world applications, there has been a growing interest in developing post hoc explanations that summarize the behaviors of these black box models.
Robust and Stable Black Box Explanations
To the best of our knowledge, this work makes the first attempt at generating post hoc explanations that are robust to a general class of adversarial perturbations that are of practical interest.
Network Embedding: An Overview
In addition, we give examples of real-world machine learning problems on networks in which the embedding is critical in order to maximize the predictive performance of the machine learning task.
Prediction of Horizontal Data Partitioning Through Query Execution Cost Estimation
In this paper we present a novel approach for finding an optimal horizontally partitioned schema that manifests a minimal total execution cost of a given database workload.
A Measure of Similarity in Textual Data Using Spearman's Rank Correlation Coefficient
In the last decade, many diverse advances have occurred in the field of information extraction from data.
Stability of decision trees and logistic regression
To that end, in this paper, we derive two stability notions for decision trees and logistic regression: hypothesis and pointwise hypothesis stability.
Stacking and stability
We show that the hypothesis stability of stacking is a product of the hypothesis stability of each of the base models and the combiner.
