112 citations · 241 across the 8 of their papers we have counts for
8 papers
Linear Regression from 1-bit Quantized Data
Daniel Hill, Martin Slawski
Motivated by the prevalence of environments in which data is abundant while resources for storage and/or transmission might be scarce, we study linear regression when predictors, t…
Bayesian regularization of empirical MDPs
Samarth Gupta, Daniel N. Hill, Lexing Ying +1
In most applications of model-based Markov decision processes, the parameters for the unknown underlying model are often estimated from the empirical data. Due to noise, the policy…
Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion
Adam Block, Rahul Kidambi, Daniel N. Hill +2
Conventional methods for query autocompletion aim to predict which completed query a user will select from a list. A shortcoming of this approach is that users often do not know wh…
Top- eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying +4
Motivated by modern applications, such as online advertisement and recommender systems, we study the top- extreme contextual bandits problem, where the total number of arms can…
Session-Aware Query Auto-completion using Extreme Multi-label Ranking
Nishant Yadav, Rajat Sen, Daniel N. Hill +2
Query auto-completion (QAC) is a fundamental feature in search engines where the task is to suggest plausible completions of a prefix typed in the search bar. Previous queries in t…
A Zero Attention Model for Personalized Product Search
Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan +1
Product search is one of the most popular methods for people to discover and purchase products on e-commerce websites. Because personal preferences often have an important influenc…