Titlebook: Learning Theory; 17th Annual Conferen John Shawe-Taylor,Yoram Singer Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 2004 Boo

formation

書目名稱Learning Theory影響因子(影響力)




書目名稱Learning Theory影響因子(影響力)學(xué)科排名




書目名稱Learning Theory網(wǎng)絡(luò)公開度




書目名稱Learning Theory網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Learning Theory被引頻次




書目名稱Learning Theory被引頻次學(xué)科排名




書目名稱Learning Theory年度引用




書目名稱Learning Theory年度引用學(xué)科排名




書目名稱Learning Theory讀者反饋




書目名稱Learning Theory讀者反饋學(xué)科排名

Cervical-Spine

A Function Representation for Learning in Banach Spacesh spaces and show how this function representation naturally arises in that problem. Furthermore, we provide circumstances in which these representations are dense relative to the uniform norm and discuss how the parameters in such representations may be used to fit data.

刺穿

LASH

Regret Bounds for Hierarchical Classification with Linear-Threshold Functions the number of training examples and depends in a detailed way on the interaction between the process parameters and the taxonomy structure. Preliminary experiments on real-world data provide support to our theoretical results.

Limpid

AGONY

Concentration Bounds for Unigrams Language Modelarning algorithm is its expected per-word log-loss. We show that the leave-one-out method can be used for estimating the log-loss of the unigrams model with a PAC error of approximately ., for any distribution..We also bound the log-loss a priori, as a function of various parameters of the distribution.

跑過(guò)

ineluctable

Learning Classes of Probabilistic Automata stochastic languages. We show that a MA may generate a stochastic language that cannot be generated by a PFA, but we show also that it is undecidable whether a MA generates a stochastic language. Finally, we propose a learning algorithm for a subclass of PFA, called PRFA.

憤怒事實(shí)

connoisseur