13 citations · 28 across the 6 of their papers we have counts for
8 papers
CM-DPO: Constraint-Margin Direct Preference Optimization for LLM Planning
Rabimba Karanjai, Qun Gu, Hemanth Hegadehalli Madhavarao +8
Direct Preference Optimization (DPO) treats all constraint violations equally: a 1,000 overshoot induce the same training signal. It is also susceptible…
Inverse classification with logistic and softmax classifiers: efficient optimization
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
In recent years, a certain type of problems have become of interest where one wants to query a trained classifier. Specifically, one wants to find the closest instance to a given i…
Very fast, approximate counterfactual explanations for decision forests
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
We consider finding a counterfactual explanation for a classification or regression forest, such as a random forest. This requires solving an optimization problem to find the close…
Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov
The widespread deployment of deep nets in practical applications has lead to a growing desire to understand how and why such black-box methods perform prediction. Much work has foc…
Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
We consider counterfactual explanations, the problem of minimally adjusting features in a source input instance so that it is classified as a target class under a given classifier.…
An Experimental Comparison of Old and New Decision Tree Algorithms
Arman Zharmagambetov, Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán +1
This paper presents a detailed comparison of a recently proposed algorithm for optimizing decision trees, tree alternating optimization (TAO), with other popular, established algor…
Sampling the "Inverse Set" of a Neuron: An Approach to Understanding Neural Nets
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
With the recent success of deep neural networks in computer vision, it is important to understand the internal working of these networks. What does a given neuron represent? The co…
Style Transfer by Rigid Alignment in Neural Net Feature Space
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Arbitrary style transfer is an important problem in computer vision that aims to transfer style patterns from an arbitrary style image to a given content image. However, current me…