136 citations · 621 across the 37 of their papers we have counts for
40 papers
Explainable Machine Learning in Deployment
Umang Bhatt, Alice Xiang, Shubham Sharma +7
Explainable machine learning offers the potential to provide stakeholders with insights into model behavior by using various methods such as feature importance scores, counterfactu…
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems
Shalmali Joshi, Oluwasanmi Koyejo, Warut Vijitbenjaronk +2
Machine learning based decision making systems are increasingly affecting humans. An individual can suffer an undesirable outcome under such decision making systems (e.g. denied cr…
Learning More From Less: Towards Strengthening Weak Supervision for Ad-Hoc Retrieval
Dany Haddad, Joydeep Ghosh
The limited availability of ground truth relevance labels has been a major impediment to the application of supervised methods to ad-hoc retrieval. As a result, unsupervised scorin…
Vehicular Multi-object Tracking with Persistent Detector Failures
Michael Motro, Joydeep Ghosh
Autonomous vehicles often perceive the environment by feeding sensor data to a learned detector algorithm, then feeding detections to a multi-object tracker that models object moti…
On Single Source Robustness in Deep Fusion Models
Taewan Kim, Joydeep Ghosh
Algorithms that fuse multiple input sources benefit from both complementary and shared information. Shared information may provide robustness against faulty or noisy inputs, which…
Scaling Data Association for Hypothesis-Oriented MHT
Michael Motro, Joydeep Ghosh
Multi-hypothesis tracking is a flexible and intuitive approach to tracking multiple nearby objects. However, the original formulation of its data association step is widely thought…