Size Matters - 機器學習的分散式和平行處理議題

John Langford的個人部落格看到這個消息:由 Ron Bekkerman (LinkedIn),John Langford (Yahoo! Research)和 Misha Bilenko(Microsoft Research)共同編輯的 Scaling up Machine Learning 將在今年底出版。而且他們將在 KDD 2011 以這本書為基礎發表 Scaling Up Machine Learning 的 Tutorial

依照 John Langford 的介紹:
This tutorial focuses on providing an integrated overview of state-of-the-art platforms and algorithm choices. These span a range of hardware options (from FPGAs and GPUs to multi-core systems and commodity clusters), programming frameworks (including CUDA, MPI, MapReduce, and DryadLINQ), and learning settings (e.g., semi-supervised and online learning). The tutorial is example-driven, covering a number of popular algorithms (e.g., boosted trees, spectral clustering, belief propagation) and diverse applications (e.g., speech recognition and object recognition in vision).

不在現場的我,是沒有機會親聆這場盛會啦,不過稍微瞄了下簡報檔,覺得這本書裡面的題材都蠻有意思的,比如說下面第一個圖提到克服隱私權疑慮的嘗試,和第二個圖 Tree Ensembles 的說明。



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