[PDF][PDF] We need fairness and explainability in algorithmic hiring
Algorithms and machine learning models, including the decisions made by these models,
are becoming ubiquitous in our daily life, including hiring. We make no value judgment …
are becoming ubiquitous in our daily life, including hiring. We make no value judgment …
Fairness of exposure in stochastic bandits
Contextual bandit algorithms have become widely used for recommendation in online
systems (eg marketplaces, music streaming, news), where they now wield substantial …
systems (eg marketplaces, music streaming, news), where they now wield substantial …
Bridging machine learning and mechanism design towards algorithmic fairness
Decision-making systems increasingly orchestrate our world: how to intervene on the
algorithmic components to build fair and equitable systems is therefore a question of utmost …
algorithmic components to build fair and equitable systems is therefore a question of utmost …
Efficient frameworks for generalized low-rank matrix bandit problems
In the stochastic contextual low-rank matrix bandit problem, the expected reward of an action
is given by the inner product between the action's feature matrix and some fixed, but initially …
is given by the inner product between the action's feature matrix and some fixed, but initially …
Fair contextual multi-armed bandits: Theory and experiments
When an AI system interacts with multiple users, it frequently needs to make allocation
decisions. For instance, a virtual agent decides whom to pay attention to in a group, or a …
decisions. For instance, a virtual agent decides whom to pay attention to in a group, or a …
Fairness in ranking under uncertainty
Fairness has emerged as an important consideration in algorithmic decision making.
Unfairness occurs when an agent with higher merit obtains a worse outcome than an agent …
Unfairness occurs when an agent with higher merit obtains a worse outcome than an agent …
Honor among bandits: No-regret learning for online fair division
AD Procaccia, B Schiffer… - Advances in Neural …, 2025 - proceedings.neurips.cc
We consider the problem of online fair division of indivisible goods to players when there are
a finite number of types of goods and player values are drawn from distributions with …
a finite number of types of goods and player values are drawn from distributions with …
Socially fair reinforcement learning
D Mandal, J Gan - ar**-xu-ambuj-tewari" data-clk="hl=en&sa=T&ct=res&cd=9&d=13675421439244327894&ei=OLrHZ6zMAZ-_6rQPvv_vqQc" data-clk-atid="1lvr71fbyL0J" target="_blank">Bandit algorithms for precision medicine
The Oxford English Dictionary defines precision medicine as “medical care designed to
optimize efficiency or therapeutic benefit for particular groups of patients, especially by using …
optimize efficiency or therapeutic benefit for particular groups of patients, especially by using …