3 citations · 3 across the 1 of their papers we have counts for
3 papers
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi +1
Algorithmic decision making based on computer vision and machine learning technologies continue to permeate our lives. But issues related to biases of these models and the extent t…
Stochastic Bandits with Delayed Composite Anonymous Feedback
Siddhant Garg, Aditya Kumar Akash
We explore a novel setting of the Multi-Armed Bandit (MAB) problem inspired from real world applications which we call bandits with "stochastic delayed composite anonymous feedback…
Lower Bounds for Graph Exploration Using Local Policies
Aditya Kumar Akash, Sandor P. Fekete, Seoung Kyou Lee +3
We give lower bounds for various natural node- and edge-based local strategies for exploring a graph. We consider this problem both in the setting of an arbitrary graph as well as…