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← Core Methods
Machine Learning
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Core Methods
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Structured Prediction
170 directly classified papers
Papers per year
2006: 3
2007: 6
2008: 4
2009: 3
2010: 11
2011: 4
2012: 1
2013: 16
2014: 12
2015: 8
2016: 7
2017: 11
2018: 24
2019: 14
2020: 17
2021: 11
2022: 12
2023: 6
Papers
Improving Human Judgments by Decontaminating Sequential Dependencies
NIPS 2010
Energy Disaggregation via Discriminative Sparse Coding
NIPS 2010
Static Analysis of Binary Executables Using Structural SVMs
NIPS 2010
MAP estimation in Binary MRFs via Bipartite Multi-cuts
NIPS 2010
Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions
NIPS 2009
Local Rules for Global MAP: When Do They Work ?
NIPS 2009
A Rate Distortion Approach for Semi-Supervised Conditional Random Fields
NIPS 2009
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
NIPS 2008
Global Ranking Using Continuous Conditional Random Fields
NIPS 2008
Structured ranking learning using cumulative distribution networks
NIPS 2008
Partially Observed Maximum Entropy Discrimination Markov Networks
NIPS 2008
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
NIPS 2007
An Analysis of Convex Relaxations for MAP Estimation
NIPS 2007
Efficient multiple hyperparameter learning for log-linear models
NIPS 2007
CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation
NIPS 2007
Configuration Estimates Improve Pedestrian Finding
NIPS 2007
Structured Learning with Approximate Inference
NIPS 2007
Isotonic Conditional Random Fields and Local Sentiment Flow
NIPS 2006
Training Conditional Random Fields for Maximum Labelwise Accuracy
NIPS 2006
Comparative Gene Prediction using Conditional Random Fields
NIPS 2006
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