ICML 2008 -- Tutorial on Theory and Applications of Online Learning
ICML 2008 Tutorial on Theory and Applications of Online Learning Shai Shalev-Shwartz and Yoram Singer Tutorial Description | Slides | Presenters | References Tutorial Description Online learning is a well established learning paradigm which has both theoretical and practical appeals. The goal of online learning is to make a sequence of accurate predictions given knowledge of the correct answer to
SELECT Lab::Tutorial at ICML 2008: Beyond Convexity - Submodularity in Machine Learning
Beyond Convexity: Submodularity in Machine Learning Description Convex optimization has become a main workhorse for many machine learning algorithms during the past ten years. When minimizing a convex loss function for, e.g., training a Support Vector Machine, we can rest assured to efficiently find an optimal solution, even for large problems. In recent years, another fundamental problem st
GSLT: Machine Learning: Generalized Linear Classifiers
Generalized Linear Classifiers in NLP For the better part of a decade machine learning methods like maximum entropy and support vector machines have been a major part of many NLP applications such as parsing, semantic role labeling, ontology induction, machine translation, and summarization. Many of these models fall into the class of Generalized Linear Classifiers, which are characterized by defi
1
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Sign in - Google Accounts
Tutorial Main Page - SSL Tutorial: ACL 2008
NIPS : Conferences : 2007 : Program : NIPS 2007 Schedule
VideoLectures - exchange ideas & share knowledge
(OLD) DMSS2006 and JSAI Special Issue on DM and SS Homepage (OLD)