找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: ;

[復(fù)制鏈接]
樓主: 到凝乳
21#
發(fā)表于 2025-3-25 13:16:13 | 只看該作者
Katja Kanzler,Brigitte Georgi-Findlayree languages of arbitrarily many dimensions. Via the correspondence between trees and string languages (“yield operation”) this is equivalent to the statement that this way even some string language classes beyond context-freeness have become learnable with respect to Angluin’s learning model as well.
22#
發(fā)表于 2025-3-25 19:52:07 | 只看該作者
,Musterl?sungen zu den übungen,to extract some nontrivial structure in the form of a PDFA with 30-50 states. An additional feature, in fact partly explaining the reduction in sample size, is that our algorithm does not need as input any information about the distinguishability of the target.
23#
發(fā)表于 2025-3-25 21:27:18 | 只看該作者
A Polynomial Algorithm for the Inference of Context Free Languages is based on a generalisation of distributional learning and uses the lattice of context occurrences. The formalism and the algorithm seem well suited to natural language and in particular to the modelling of first language acquisition.
24#
發(fā)表于 2025-3-26 01:03:20 | 只看該作者
25#
發(fā)表于 2025-3-26 07:29:13 | 只看該作者
26#
發(fā)表于 2025-3-26 10:23:04 | 只看該作者
27#
發(fā)表于 2025-3-26 13:50:27 | 只看該作者
Towards Feasible PAC-Learning of Probabilistic Deterministic Finite Automatato extract some nontrivial structure in the form of a PDFA with 30-50 states. An additional feature, in fact partly explaining the reduction in sample size, is that our algorithm does not need as input any information about the distinguishability of the target.
28#
發(fā)表于 2025-3-26 17:18:50 | 只看該作者
Learning Commutative Regular Languagesmmutative regular languages from positive and negative samples, and we show, from experimental results, that far from being a theoretical algorithm, it produces very high recognition rates in comparison with classical inference algorithms.
29#
發(fā)表于 2025-3-26 23:07:39 | 只看該作者
30#
發(fā)表于 2025-3-27 01:36:15 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-6 23:15
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
长治市| 凤台县| 常山县| 象山县| 东兴市| 宁国市| 通许县| 江山市| 甘肃省| 桑日县| 杂多县| 岳西县| 江川县| 库车县| 黄梅县| 婺源县| 景宁| 登封市| 承德市| 织金县| 吉安县| 开鲁县| 密云县| 梨树县| 仁化县| 新沂市| 海南省| 麻阳| 全南县| 东山县| 株洲市| 景洪市| 平定县| 安庆市| 元朗区| 砚山县| 长沙县| 邮箱| 蒲城县| 高阳县| 呼玛县|