David Vickrey

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

Recommender systems are the algorithms which select, filter, and personalize content across many of the worlds largest platforms and apps. As such, their positive and negative effects on...

Constrained Approximate Maximum Entropy Learning of Markov Random Fields

Parameter estimation in Markov random fields (MRFs) is a difficult task, in which inference over the network is run in the inner loop of a gradient descent procedure. Replacing exact inference...

Online Word Games for Semantic Data Collection

Word-Sense Disambiguation for Machine Translation

Sentence Simplification for Semantic Role Labeling

An Active Learning Approach to Finding Related Terms

Applying Sentence Simplification to the CoNLL-2008 Shared Task

Constrained Approximate Maximum Entropy Learning of Markov Random Fields

Non-Local Contrastive Objectives

Learning a meta-level prior for feature relevance from multiple related tasks

Multi-Agent Algorithms for Solving Graphical Games