45 citations · 54 across the 6 of their papers we have counts for
6 papers
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions
Manish Nagireddy, Moninder Singh, Samuel C. Hoffman +3
Ensuring trustworthiness in machine learning (ML) models is a multi-dimensional task. In addition to the traditional notion of predictive performance, other notions such as privacy…
Ground-Truth, Whose Truth? -- Examining the Challenges with Annotating Toxic Text Datasets
Kofi Arhin, Ioana Baldini, Dennis Wei +2
The use of machine learning (ML)-based language models (LMs) to monitor content online is on the rise. For toxic text identification, task-specific fine-tuning of these models are…
Data-Centric AI Requires Rethinking Data Notion
Mustafa Hajij, Ghada Zamzmi, Karthikeyan Natesan Ramamurthy +1
The transition towards data-centric AI requires revisiting data notions from mathematical and implementational standpoints to obtain unified data-centric machine learning packages.…
A Deep Learning Approach To Multiple Kernel Fusion
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri +2
Kernel fusion is a popular and effective approach for combining multiple features that characterize different aspects of data. Traditional approaches for Multiple Kernel Learning (…
Robust Local Scaling using Conditional Quantiles of Graph Similarities
Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy +1
Spectral analysis of neighborhood graphs is one of the most widely used techniques for exploratory data analysis, with applications ranging from machine learning to social sciences…
TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning
Jayaraman J. Thiagarajan, Bhavya Kailkhura, Prasanna Sattigeri +1
With the advent of highly predictive but opaque deep learning models, it has become more important than ever to understand and explain the predictions of such models. Existing appr…