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CVPR
2005
IEEE
16 years 8 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...
ICANN
2009
Springer
16 years 1 months ago
Learning Features by Contrasting Natural Images with Noise
Abstract. Modeling the statistical structure of natural images is interesting for reasons related to neuroscience as well as engineering. Currently, this modeling relies heavily on...
Michael Gutmann, Aapo Hyvärinen
WEBDB
2010
Springer
155views Database» more  WEBDB 2010»
15 years 12 months ago
Learning Topical Transition Probabilities in Click Through Data with Regression Models
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diļ...
Xiao Zhang, Prasenjit Mitra
ATAL
2008
Springer
15 years 8 months ago
Learning to interact: connecting perception with action in virtual environments
Modeling synthetic characters which interact with objects in dynamic virtual worlds is important when we want the agents to act in an autonomous and non-preplanned way. Such inter...
Pedro Sequeira, Ana Paiva
SODA
2003
ACM
132views Algorithms» more  SODA 2003»
15 years 8 months ago
Online learning in online auctions
We consider the problem of revenue maximization in online auctions, that is, auctions in which bids are received and dealt with one-by-one. In this note, we demonstrate that resul...
Avrim Blum, Vijay Kumar, Atri Rudra, Felix Wu