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Oral
Thu Jun 13 11:00 AM -- 11:20 AM (PDT) @ Room 201
Scaling Up Ordinal Embedding: A Landmark Approach
Jesse Anderton · Javed Aslam
[ Slides [ Oral
Oral
Thu Jun 13 11:20 AM -- 11:25 AM (PDT) @ Room 201
Learning to select for a predefined ranking
Aleksei Ustimenko · Aleksandr Vorobev · Gleb Gusev · Pavel Serdyukov
[ Slides [ Oral
Oral
Thu Jun 13 11:25 AM -- 11:30 AM (PDT) @ Room 201
Mallows ranking models: maximum likelihood estimate and regeneration
Wenpin Tang
Oral
Thu Jun 13 11:30 AM -- 11:35 AM (PDT) @ Room 201
Fast and Stable Maximum Likelihood Estimation for Incomplete Multinomial Models
Chenyang ZHANG · Guosheng Yin
Oral
Thu Jun 13 11:35 AM -- 11:40 AM (PDT) @ Room 201
Fast Algorithm for Generalized Multinomial Models with Ranking Data
Jiaqi Gu · Guosheng Yin
[ Slides [ Oral
Oral
Thu Jun 13 11:40 AM -- 12:00 PM (PDT) @ Room 201
Graph Resistance and Learning from Pairwise Comparisons
Julien Hendrickx · Alex Olshevsky · Venkatesh Saligrama
[ Slides [ Oral
Oral
Thu Jun 13 12:00 PM -- 12:05 PM (PDT) @ Room 201
Learning Context-dependent Label Permutations for Multi-label Classification
Jinseok Nam · Young-Bum Kim · Eneldo Loza Mencia · Sunghyun Park · Ruhi Sarikaya · Johannes F├╝rnkranz
[ Slides [ Oral
Oral
Thu Jun 13 12:05 PM -- 12:10 PM (PDT) @ Room 201
Discovering Context Effects from Raw Choice Data
Arjun Seshadri · Alexander Peysakhovich · Johan Ugander
[ Slides [ Oral
Oral
Thu Jun 13 12:10 PM -- 12:15 PM (PDT) @ Room 201
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference
Rohin Shah · Noah Gundotra · Pieter Abbeel · Anca Dragan
[ Slides [ Oral
Oral
Thu Jun 13 12:15 PM -- 12:20 PM (PDT) @ Room 201
Learning Distance for Sequences by Learning a Ground Metric
Bing Su · Ying Wu
[ Slides [ Oral