8 citations · 22 across the 7 of their papers we have counts for
7 papers
A Principle-based Framework for the Development and Evaluation of Large Language Models for Health and Wellness
Brent Winslow, Jacqueline Shreibati, Javier Perez +18
The incorporation of generative artificial intelligence into personal health applications presents a transformative opportunity for personalized, data-driven health and fitness gui…
Overcoming Prior Misspecification in Online Learning to Rank
Javad Azizi, Ofer Meshi, Masrour Zoghi +1
The recent literature on online learning to rank (LTR) has established the utility of prior knowledge to Bayesian ranking bandit algorithms. However, a major limitation of existing…
IMO: Interactive Multi-Objective Off-Policy Optimization
Nan Wang, Hongning Wang, Maryam Karimzadehgan +2
Most real-world optimization problems have multiple objectives. A system designer needs to find a policy that trades off these objectives to reach a desired operating point. This p…
CORe: Capitalizing On Rewards in Bandit Exploration
Nan Wang, Branislav Kveton, Maryam Karimzadehgan
We propose a bandit algorithm that explores purely by randomizing its past observations. In particular, the sufficient optimism in the mean reward estimates is achieved by exploiti…
Separate and Attend in Personal Email Search
Yu Meng, Maryam Karimzadehgan, Honglei Zhuang +1
In personal email search, user queries often impose different requirements on different aspects of the retrieved emails. For example, the query "my recent flight to the US" require…
Domain Adaptation for Enterprise Email Search
Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi +2
In the enterprise email search setting, the same search engine often powers multiple enterprises from various industries: technology, education, manufacturing, etc. However, using…
Multi-Task Learning for Email Search Ranking with Auxiliary Query Clustering
Jiaming Shen, Maryam Karimzadehgan, Michael Bendersky +2
User information needs vary significantly across different tasks, and therefore their queries will also differ considerably in their expressiveness and semantics. Many studies have…