Pruning of error correcting output codes by optimization of accuracy-diversity trade off - 석슬기

• Date

  2017.12.15

• Speaker

  석슬기

Sparse Bayesian Learning and the Relevance Vector Machine - 하지현

• Date

  2017.11.23

• Speaker

  하지현

Additive Logistic Regression_A Statistical View of Boosting - 김동욱

• Date

  2017.11.16

• Speaker

  김동욱

Feature selection based on loss-margin of nearest neighbor - 김현호

• Date

  2017.11.16

• Speaker

  김현호

Cluster based boosting - 박기범

• Date

  2017.11.02

• Speaker

  박기범

Gradient-based boosting for statistical relational learning_The relational dependenct network case_2 - 김동욱

• Date

  2017.10.26

• Speaker

  김동욱

Extract minimum positive and maximum negative feature for imbalanced binary classification - 구본혁

• Date

  2017.10.26

• Speaker

  구본혁

Constraint-based clustering selection - 박연탁

• Date

  2017.10.19

• Speaker

  박연탁

An aggregate and iterative disaggregate algorithm with proven optimality in machine learning - 김태흥

• Date

  2017.10.19

• Speaker

  김태흥

Cost-sensitive boosting algorithms Do we really need - 박연탁

• Date

  2017.09.22

• Speaker

  박연탁

Using iterated bagging to debias regressions - 석슬기

• Date

  2017.09.15

• Speaker

  석슬기

Kernel Matching Pursuit - 한민석

• Date

  2017.09.15

• Speaker

  한민석