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» Learning Generative Models via Discriminative Approaches
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SIGIR
2009
ACM
15 years 7 months ago
An improved markov random field model for supporting verbose queries
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
Matthew Lease
117
Voted
ATAL
2010
Springer
15 years 24 days ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko
SI3D
2003
ACM
15 years 5 months ago
Smooth meshes for sketch-based freeform modeling
This paper describes a framework for introducing visually smooth surfaces into sketch-based freeform modeling systems. An existing sketch-based freeform modeling system generates ...
Takeo Igarashi, John F. Hughes
AAAI
2008
15 years 2 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam
GRAPHICSINTERFACE
2011
14 years 4 months ago
Formation sketching: an approach to stylize groups in crowd simulation
Most of existing crowd simulation algorithms focus on the moving trajectories of individual agents, while collective group formations are often roughly learned from video examples...
Qin Gu, Zhigang Deng