Bias Neutralization Framework: Measuring Fairness in Large Language Models with Bias Intelligence Quotient (BiQ)

no code implementations • 28 Apr 2024 • Malur Narayan, John Pasmore, Elton Sampaio, Vijay Raghavan, Gabriella Waters

The burgeoning influence of Large Language Models (LLMs) in shaping public discourse and decision-making underscores the imperative to address inherent biases within these AI systems.

Decision Making Fairness +2

Device-aware inference operations in SONOS nonvolatile memory arrays

no code implementations • 2 Apr 2020 • Christopher H. Bennett, T. Patrick Xiao, Ryan Dellana, Vineet Agrawal, Ben Feinberg, Venkatraman Prabhakar, Krishnaswamy Ramkumar, Long Hinh, Swatilekha Saha, Vijay Raghavan, Ramesh Chettuvetty, Sapan Agarwal, Matthew J. Marinella

Non-volatile memory arrays can deploy pre-trained neural network models for edge inference.

Deep Multi-view Learning to Rank

no code implementations • 31 Jan 2018 • Guanqun Cao, Alexandros Iosifidis, Moncef Gabbouj, Vijay Raghavan, Raju Gottumukkala

We study the problem of learning to rank from multiple information sources.

Learning-To-Rank MULTI-VIEW LEARNING

Multiple Kernel Learning and Automatic Subspace Relevance Determination for High-dimensional Neuroimaging Data

no code implementations • 2 Jun 2017 • Murat Seckin Ayhan, Vijay Raghavan, Alzheimer's Disease Neuroimaging Initiative

Extending the basic scheme towards the Multiple Kernel Learning, we improve the efficacy of the Gaussian Process models and their interpretability in terms of the known anatomical correlates of the disease.

Gaussian Processes General Classification +1