191 citations · 261 across the 15 of their papers we have counts for
18 papers
Intermediate Entity-based Sparse Interpretable Representation Learning
Diego Garcia-Olano, Yasumasa Onoe, Joydeep Ghosh +1
Interpretable entity representations (IERs) are sparse embeddings that are "human-readable" in that dimensions correspond to fine-grained entity types and values are predicted prob…
FASTER-CE: Fast, Sparse, Transparent, and Robust Counterfactual Explanations
Shubham Sharma, Alan H. Gee, Jette Henderson +1
Counterfactual explanations have substantially increased in popularity in the past few years as a useful human-centric way of understanding individual black-box model predictions.…
FEAMOE: Fair, Explainable and Adaptive Mixture of Experts
Shubham Sharma, Jette Henderson, Joydeep Ghosh
Three key properties that are desired of trustworthy machine learning models deployed in high-stakes environments are fairness, explainability, and an ability to account for variou…
Designing Robust Transformers using Robust Kernel Density Estimation
Xing Han, Tongzheng Ren, Tan Minh Nguyen +3
Recent advances in Transformer architectures have empowered their empirical success in a variety of tasks across different domains. However, existing works mainly focus on predicti…
Split Localized Conformal Prediction
Xing Han, Ziyang Tang, Joydeep Ghosh +1
Conformal prediction is a simple and powerful tool that can quantify uncertainty without any distributional assumptions. Many existing methods only address the average coverage gua…
Federated Self-supervised Learning for Heterogeneous Clients
Disha Makhija, Nhat Ho, Joydeep Ghosh
Federated Learning has become an important learning paradigm due to its privacy and computational benefits. As the field advances, two key challenges that still remain to be addres…