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07/05/2023
Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison
Gaussian graphical models are graphs that represent the conditional rela...
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07/03/2023
Fixing confirmation bias in feature attribution methods via semantic match
Feature attribution methods have become a staple method to disentangle t...
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06/30/2023
High-Dimensional Bayesian Structure Learning in Gaussian Graphical Models using Marginal Pseudo-Likelihood
Gaussian graphical models depict the conditional dependencies between va...
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01/31/2023
Differentially Private Distributed Bayesian Linear Regression with MCMC
We propose a novel Bayesian inference framework for distributed differen...
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01/26/2023
Finding Regions of Counterfactual Explanations via Robust Optimization
Counterfactual explanations play an important role in detecting bias and...
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01/05/2023
Semantic match: Debugging feature attribution methods in XAI for healthcare
The recent spike in certified Artificial Intelligence (AI) tools for hea...
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10/20/2022
Machine Learning for K-adaptability in Two-stage Robust Optimization
Two-stage robust optimization problems constitute one of the hardest opt...
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12/12/2021
Learning with Subset Stacking
We propose a new algorithm that learns from a set of input-output pairs....
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11/13/2021
Bolstering Stochastic Gradient Descent with Model Building
Stochastic gradient descent method and its variants constitute the core ...
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11/04/2021
Mixed-Integer Optimization with Constraint Learning
We establish a broad methodological foundation for mixed-integer optimiz...
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10/20/2021
Differential Privacy in Multi-Party Resource Sharing
This study examines a resource-sharing problem involving multiple partie...
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04/21/2021
Discovering Classification Rules for Interpretable Learning with Linear Programming
Rules embody a set of if-then statements which include one or more condi...
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08/05/2020
Differentially Private Accelerated Optimization Algorithms
We present two classes of differentially private optimization algorithms...
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07/17/2020
Low-dimensional Interpretable Kernels with Conic Discriminant Functions for Classification
Kernels are often developed and used as implicit mapping functions that ...
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07/13/2020
Rule Covering for Interpretation and Boosting
We propose two algorithms for interpretation and boosting of tree-based ...
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09/05/2015
HAMSI: A Parallel Incremental Optimization Algorithm Using Quadratic Approximations for Solving Partially Separable Problems
We propose HAMSI (Hessian Approximated Multiple Subsets Iteration), whic...
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06/03/2015