1k citations
- Stanford UniversityUS33 papers
- Google (United States)US32 papers
- University of Illinois Urbana-ChampaignUS32 papers
- University of California, BerkeleyUS29 papers
- Massachusetts Institute of TechnologyUS28 papers
- Carnegie Mellon UniversityUS26 papers
- University of California San DiegoUS25 papers
- University College LondonGB22 papers
- Georgia Institute of TechnologyUS21 papers
- University of Maryland, College ParkUS21 papers
- University of MichiganUS18 papers
- University of Southern CaliforniaUS16 papers
Showing 2016 · stat.MLShow all
3 papers · 2 filters
stat.ML2016★ 8 cited
Bottleneck Conditional Density Estimation
Rui Shu, Hung H. Bui, Mohammad Ghavamzadeh
We introduce a new framework for training deep generative models for high-dimensional conditional density estimation. The Bottleneck Conditional Density Estimator (BCDE) is a varia…
stat.ML2016★ 45 cited
Conservative Contextual Linear Bandits
Abbas Kazerouni, Mohammad Ghavamzadeh, Yasin Abbasi-Yadkori +1
Safety is a desirable property that can immensely increase the applicability of learning algorithms in real-world decision-making problems. It is much easier for a company to deplo…
stat.ML2016★ 7 cited
The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM
Ardavan Saeedi, Matthew Hoffman, Matthew Johnson +1
We propose the segmented iHMM (siHMM), a hierarchical infinite hidden Markov model (iHMM) that supports a simple, efficient inference scheme. The siHMM is well suited to segmentati…