1 citations · 1 across the 5 of their papers we have counts for
5 papers
Towards Fair Predictions: Group Conditional Concordance Index to Quantify Fairness in Time-to-Event Prognostication
Haoyuan Wang, Riddhiman Bhattacharya, Richardo Henao +3
Fairness metrics are essential for rigorously defining, quantifying, and mitigating biases in predictive models. While most existing metrics focus on binary classification tasks, f…
Entropy-Guided Sampling of Flat Modes in Discrete Spaces
Pinaki Mohanty, Riddhiman Bhattacharya, Ruqi Zhang
Sampling from flat modes in discrete spaces is a crucial yet underexplored problem. Flat modes represent robust solutions and have broad applications in combinatorial optimization…
Active Learning for Fair and Stable Online Allocations
Riddhiman Bhattacharya, Thanh Nguyen, Will Wei Sun +1
We explore an active learning approach for dynamic fair resource allocation problems. Unlike previous work that assumes full feedback from all agents on their allocations, we consi…
Gradient-based Discrete Sampling with Automatic Cyclical Scheduling
Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan +1
Discrete distributions, particularly in high-dimensional deep models, are often highly multimodal due to inherent discontinuities. While gradient-based discrete sampling has proven…
Fast Sampling and Inference via Preconditioned Langevin Dynamics
Riddhiman Bhattacharya, Tiefeng Jiang
Sampling from distributions play a crucial role in aiding practitioners with statistical inference. However, in numerous situations, obtaining exact samples from complex distributi…