Translated Learning Wenyuan Dai, Yuqiang Chen, Gui-Rong Xue, Qiang Yang, and Yong Yu. Translated Learning. In Proceedings of Twenty- Second Annual Conference on Neural Information Processing Systems (NIPS 2008), December 8, 2008, Vancouver, British Columbia, Canada.

Definition Translated Learning – Learning across Different Feature Spaces

Applications Cross-language Classification – Rigutini et al., WI2005; Ling et al., WWW2008; … Text-aided Image Classification – We submitted two papers to AAAI2008 & ICML2008 respectively. Future work – Text to Music – Text to Video – Image to Video –…–…

Related Work Cross-language Classification – Rigutini et al., WI2005 English to Italian – Ling et al., WWW2008 English to Chinese Most cross-language classification approaches relies on machine translation. – Ad hoc – Machine translation is difficult in most scenarios. E.g. text-to-picture translation

Basic Idea Instance-level machine translation relies on understanding instances, at least basically. – Machine translation in NLP is an easy special case, since it is based on sentence understanding. Classification models are usually on the feature- level. Translating classification models is also on the feature-level. – could be much easier than instance-level translation

Human Learning Example Task: tyrannosaurus vs stegosaurus – htyrannosaurus: bipedal carnivore with a massive skull balanced by long, heavy tail. Its forelimbs were small and retained only two digits. – stegosaurus: quadruped ornithischian dinosaur of four long bony spikes on a flexible tail and two rows of upright triangular bony plates running along the back.

Model-level Translation Learning InputOutput Learning InputOutput Elephants are big mammals on earth... massive hoofed mammal of Africa... translating learning models

Naive Bayesian Approach Incorporating translator difficult to estimate

Risk Minimization Approach Loss function

Inference Assume there is no prior difference among all the classes

Model Estimation KL-divergence Negative of cosine Negative of PCC

Experimental Results

Outline Introduction Related Work Our Research Future Work

More applications – Cross-language classification Using dictionaries as translators – Text to music, video, … – Image to video Improving translator estimation – Integrating text classification and translator estimation into one optimization model

Questions