We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Tweets are the most up-to-date and inclusive stream of information and commentary on current events, but they are also fragmented and noisy, motivating the need for systems that c...
Advanced technology in GPS and sensors enables us to track physical events, such as human movements and facility usage. Periodicity analysis from the recorded data is an important...
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
We present an algorithm to dereverberate single- and multi-channel audio recordings. The proposed algorithm models the magnitude spectrograms of clean audio signals as histograms ...