Timezone: »
Poster
Learning Mixtures of Ranking Models
Pranjal Awasthi · Avrim Blum · Or Sheffet · Aravindan Vijayaraghavan
This work concerns learning probabilistic models for ranking data in a heterogeneous population. The specific problem we study is learning the parameters of a {\em Mallows Mixture Model}. Despite being widely studied, current heuristics for this problem do not have theoretical guarantees and can get stuck in bad local optima. We present the first polynomial time algorithm which provably learns the parameters of a mixture of two Mallows models. A key component of our algorithm is a novel use of tensor decomposition techniques to learn the top-$k$ prefix in both the rankings. Before this work, even the question of {\em identifiability} in the case of a mixture of two Mallows models was unresolved.
Author Information
Pranjal Awasthi (Princeton)
Avrim Blum (Toyota Technological Institute at Chicago)
Or Sheffet (Havard University)
Aravindan Vijayaraghavan (Carnegie Mellon University)
Related Events (a corresponding poster, oral, or spotlight)
-
2014 Spotlight: Learning Mixtures of Ranking Models »
Wed. Dec 10th 04:40 -- 05:05 PM Room Level 2, room 210
More from the Same Authors
-
2021 Spotlight: Excess Capacity and Backdoor Poisoning »
Naren Manoj · Avrim Blum -
2021 : One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning »
Richard Phillips · Han Shao · Avrim Blum · Nika Haghtalab -
2021 : On classification of strategic agents who can both game and improve »
Saba Ahmadi · Hedyeh Beyhaghi · Avrim Blum · Keziah Naggita -
2021 : The Strategic Perceptron »
Saba Ahmadi · Hedyeh Beyhaghi · Avrim Blum · Keziah Naggita -
2021 : One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning »
Richard Phillips · Han Shao · Avrim Blum · Nika Haghtalab -
2021 : On classification of strategic agents who can both game and improve »
Saba Ahmadi · Hedyeh Beyhaghi · Avrim Blum · Keziah Naggita -
2021 : The Strategic Perceptron »
Saba Ahmadi · Hedyeh Beyhaghi · Avrim Blum · Keziah Naggita -
2021 Poster: Excess Capacity and Backdoor Poisoning »
Naren Manoj · Avrim Blum -
2015 Poster: On some provably correct cases of variational inference for topic models »
Pranjal Awasthi · Andrej Risteski -
2015 Spotlight: On some provably correct cases of variational inference for topic models »
Pranjal Awasthi · Andrej Risteski -
2014 Poster: Learning Optimal Commitment to Overcome Insecurity »
Avrim Blum · Nika Haghtalab · Ariel Procaccia -
2014 Poster: Active Learning and Best-Response Dynamics »
Maria-Florina F Balcan · Christopher Berlind · Avrim Blum · Emma Cohen · Kaushik Patnaik · Le Song -
2010 Spotlight: Supervised Clustering »
Pranjal Awasthi · Reza Zadeh -
2010 Poster: Supervised Clustering »
Pranjal Awasthi · Reza Zadeh -
2010 Spotlight: Trading off Mistakes and Don't-Know Predictions »
Amin Sayedi · Avrim Blum · Morteza Zadimoghaddam -
2010 Poster: Trading off Mistakes and Don't-Know Predictions »
Amin Sayedi · Morteza Zadimoghaddam · Avrim Blum -
2009 Workshop: Clustering: Science or art? Towards principled approaches »
Margareta Ackerman · Shai Ben-David · Avrim Blum · Isabelle Guyon · Ulrike von Luxburg · Robert Williamson · Reza Zadeh -
2009 Poster: Tracking Dynamic Sources of Malicious Activity at Internet Scale »
Shobha Venkataraman · Avrim Blum · Dawn Song · Subhabrata Sen · Oliver Spatscheck -
2009 Spotlight: Tracking Dynamic Sources of Malicious Activity at Internet Scale »
Shobha Venkataraman · Avrim Blum · Dawn Song · Subhabrata Sen · Oliver Spatscheck -
2008 Workshop: New Challanges in Theoretical Machine Learning: Data Dependent Concept Spaces »
Maria-Florina F Balcan · Shai Ben-David · Avrim Blum · Kristiaan Pelckmans · John Shawe-Taylor