106 citations · 172 across the 3 of their papers we have counts for
3 papers
cs.LG2012★ 6 cited
Mixture-of-Parents Maximum Entropy Markov Models
David S. Rosenberg, Dan Klein, Ben Taskar
We present the mixture-of-parents maximum entropy Markov model (MoP-MEMM), a class of directed graphical models extending MEMMs. The MoP-MEMM allows tractable incorporation of long…
cs.LG2012★ 60 cited
Multi-View Learning over Structured and Non-Identical Outputs
Kuzman Ganchev, Joao Graca, John Blitzer +1
In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, eac…
cs.LG2012★ 106 cited
Learning Determinantal Point Processes
Alex Kulesza, Ben Taskar
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among…