Multiclass Classification with Filter Trees

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Doubly Robust Policy Evaluation and Learning (2011, methodology): “Similarly, the Offset Tree algorithm (Beygelzimer & Langford, 2009) can be thought of as using a crude reward estimate for the “offset”.”
Support vector machines for noise robust ASR (2009, methodology): “The alternative approach, and the one examined in this paper is a reduction style scheme using tree-based classifiers [11], [12], [13].”
Learning Tree-based Deep Model for Recommender Systems (2018, methodology): “Tree and treebased methods are researched in multiclass classification problem [1, 2, 5] and language model [20], but researchers seldom set foot in the context of recommender systems using tree structure.”
Composite Multiclass Losses (2011, unknown): “Many of our results are characterisations.”
Large Scale Visual Recognition (2012, methodology): “Classification with many classes has received increasing attention recently, and most approaches appear to have converged to tree based models [42, 43, 25, 26].”
Information, Divergence and Risk for Binary Experiments (2009, background): “However recently there has been a large number of explicit constructions of reductions (Zadrozny et al., 2003; Langford, 2006; Beygelzimer et al., 2005; Langford and Beygelzimer, 2005; Langford and Zadrozny, 2005; Langford et al., 2006; Li and Lin, 2006; Beygelzimer et al., 2007; Langford, 2007; Sco”