Titlebook: Algorithmic Learning Theory - ALT ‘92; Third Workshop, ALT Shuji Doshita,Koichi Furukawa,Toyaki Nishida Conference proceedings 1993 Spring

GLAZE

書目名稱Algorithmic Learning Theory - ALT ‘92影響因子(影響力)




書目名稱Algorithmic Learning Theory - ALT ‘92影響因子(影響力)學(xué)科排名




書目名稱Algorithmic Learning Theory - ALT ‘92網(wǎng)絡(luò)公開度




書目名稱Algorithmic Learning Theory - ALT ‘92網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Algorithmic Learning Theory - ALT ‘92被引頻次




書目名稱Algorithmic Learning Theory - ALT ‘92被引頻次學(xué)科排名




書目名稱Algorithmic Learning Theory - ALT ‘92年度引用




書目名稱Algorithmic Learning Theory - ALT ‘92年度引用學(xué)科排名




書目名稱Algorithmic Learning Theory - ALT ‘92讀者反饋




書目名稱Algorithmic Learning Theory - ALT ‘92讀者反饋學(xué)科排名

噱頭

From inductive inference to algorithmic learning theory,ucing apparently “senseless” hypotheses can solve problems unsolvable by “reasonable” learning strategies) and learning from good examples (“much less” information can lead to much more learning power). Recently, it has been shown that these phenomena also hold in the world of polynomial-time algori

cringe

哥哥噴涌而出

On learning systolic languages,s a kind of network consisting of uniformly connected processors(finite automata)..In this article, we show that the class of binary systolic tree languages is learnable in polynomial time from the learning protocol what is called minimally adequate teacher..Since the class of binary systolic tree l

止痛藥

A note on the query complexity of learning DFA,te — the query complexity — the number of membership and equivalence queries for learning deterministic finite automata. We first show two lower bounds in two different learning situations. Then we investigate the query complexity in general setting, and show some trade-off phenomenon between the nu

使人煩燥

Polynomial-time MAT learning of multilinear logic programs,. that the teacher has, with membership queries and equivalence queries. In the class of multilinear programs, we show some programs which have not been proved to be MAT learnable previously. If a multilinear program .. represents .. that the teacher has, then the total running time of our learning

GROSS

Iterative weighted least squares algorithms for neural networks classifiers,itly calculated for the network with only one neuron. It can be interpreted as a weighted covariance matrix of input vectors. A learning algorithm is presented on the basis of Fisher‘s scoring method. It is shown that the algorithm can be interpreted as iterations of weighted least square method. Th

Allure

incredulity

conservative