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NIPS
2008
15 years 6 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey
AAMAS
2005
Springer
15 years 4 months ago
Learning and Exploiting Relative Weaknesses of Opponent Agents
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
Shaul Markovitch, Ronit Reger
CVPR
2005
IEEE
16 years 6 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...
STOC
2009
ACM
102views Algorithms» more  STOC 2009»
16 years 5 months ago
Multiple intents re-ranking
One of the most fundamental problems in web search is how to re-rank result web pages based on user logs. Most traditional models for re-ranking assume each query has a single int...
Yossi Azar, Iftah Gamzu, Xiaoxin Yin
ICPR
2008
IEEE
16 years 6 months ago
Visual features with semantic combination using Bayesian network for a more effective image retrieval
In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the use...
Sabine Barrat, Salvatore Tabbone