Lycos search: learning finite automata

Load average: 6.01: Lycos Feb 17, 1995 catalog, 1892014 unique URLs (see Lycos News)

Found 7473 documents matching at least one search term.
Printing only the first 10 of 34 documents with at least scores of 0.00.

Matching words (number of documents): learning (6146), learningarts (6), learningcenter (2), finite (900), finitebib (1), automata (512), automatability (1), automatable (2), automataelmeleti (5), automataht (1), automatas (3), automatateori (1)

ID1235388: [score 1.0000, 3 of 3 terms, adj 1.0] http://theory.lcs.mit.edu/~mona/class94.html

date: 14-Jan-95
bytes: 1151
links: 2

title: Machine Learning

outline: 6.858/18.428: Machine Learning

keys: automata finite learning

excerpt: Machine Learning 6.858/18.428: Machine Learning This is the web home page for 6.858/18.428, a course being offered at MIT in the 1994 fall semester. Lectures are in 36-839 on Mondays and Wednesdays from 11:00 to 12:30. This course deals with the following topics: * Formal models of machine learning * Learning concepts from examples * Learnable classes of concepts * PAC learning * VC-dimension * Bayesian Inference * Neural Nets * Learning from queries * Learning with noise * Learning finite automata * Hidden Markov Models The following course material is available on-line: * Lecture Notes Ron Rivest (rivest@theory.lcs.mit.edu)

ID1234379: [score 0.9397, 3 of 3 terms, adj 1.0] http://theory.lcs.mit.edu/~dmjones/FOCS/Authors/schapirere.html

date: 06-Feb-95
bytes: 1393
links: 9

title: R. E. Schapire

outline: R. E. Schapire

keys: automata finite learning

excerpt: R. E. Schapire * Diversity-based inference of finite automata. * The strength of weak learnability. * Learning binary relations and total orders. * Exact identification of circuits using fixed points of amplification functions. * a href = Shortcuts:
descriptions:
R. E. Schapire

ID1430671: [score 0.4596, 3 of 3 terms] http://www.cs.duke.edu/colloquia.html

date: 29-Nov-94
bytes: 1980

title: Computer Science Colloquia

outline: Computer Science Colloquia for Spring 1994

keys: automata finite learning

excerpt: Computer Science Colloquia Colloquia are presented in room 130A North Building. The usual time is 4:00pm. Refreshments are usually served in room 212 at 3:30pm. Computer Science Colloquia for Spring 1994 Friday, January 7 Title: What Makes a Problem Easy or Hard for a Genetic Algorithm? Speaker: Melanie Mitchell, Santa Fe Institute Host: Jeff Vitter Monday, January 10 Title: Software Reliability Engineering Speaker: John Musa, AT&T Bell Laboratories Host: John Cocke Lecture Monday, January 17 Title: Monday, January 31

ID1866541: [score 0.2890, 2 of 3 terms, adj 1.0] http://www2.umassd.edu/CISW3/cisdept/CISResearch/ParallelArchAlg/ParallelArchAlgProject.html

date: 03-Feb-95
bytes: 2204
links: 4

title: Parallel Architectures Algorithms Project

outline: Experimental Study of the Relationship Between Parallel Architectures and Parallel Graph Algorithms of Intractable Computational Problems Using Homomorphism Problem of Finite Automata as a Representative Project Description Funding Information Staff Publication

keys: automata finite

excerpt: Parallel Architectures Algorithms Project Experimental Study of the Relationship Between Parallel Architectures and Parallel Graph Algorithms of Intractable Computational Problems Using Homomorphism Problem of Finite Automata as a Representat... Boleslaw Mikolajczak, CIS Department Project Description The purpose of this project is to design and implement a parallel algorithm computing generalized homomorphisms of finite automata using three parallel programming paradigms: result parallelism, specialist parallelism, agenda parallelism using a transputer system. Transputer is a computer unit which permits hardware or software implementation of reconfigurability with different level of multiprocessing depending on the architecture applied. The transputer is a computer

ID1454241: [score 0.2852, 2 of 3 terms, adj 0.9] http://www.cs.washington.edu/research/jair/volume1/schlimmer93a-html/schlimmer93-3.html

date: 11-Feb-95
bytes: 19000
links: 40

outline: 2. Performance Task 3.1 Tokenization 3.2 Learning a Finite-State Machine 3.3 Parsing 3.4 Multiple Finite-State Machines 4. Learning Embedded Classifiers

keys: finite

excerpt: 2. Performance Task 3. Learning a Syntax To implement the two modes of the note taking software, the system internally learns two structures. To characterize the syntax of user's notes, it learns finite-state machines (FSMs). To generate predictions, it learns decision tree classifiers situated at states within the FSMs. In order to construct a graphical user interface, the system converts a FSM into a set of buttons. This section describes the representation and method for learning FSMs. The next section discusses learning of the embedded classifiers. 3.1 Tokenization Prior to learning a finite-state machine, the user's note must first be converted into a sequence of tokens. Useful tokenizers can be domain independent. However, handcrafted domain-specific tokenizers
descriptions:
3. Learning a Syntax
Section 3
Table 1
Table 2

ID1430326: [score 0.2816, 2 of 3 terms, adj 1.0] http://www.cs.dartmouth.edu/courseguide/undergrad/cs_49.html

date: 12-Feb-95
bytes: 808
links: 2

title: Computer Science 49

outline: Computer Science 49: Theory of Computation

keys: automata finite

excerpt: Computer Science 49 Computer Science 49: Theory of Computation This course serves as an introduction to formal models of languages and computation. Topics covered include finite automata, regular languages, context-free languages, pushdown automata, Turing machines, and computability. Prerequisite: Computer Science 23 , or any Mathematics course numbered 20 or above. Pantziou. Back to Dartmouth CS Home Page
descriptions:
49
Theory of Computation

ID1819613: [score 0.2815, 2 of 3 terms, adj 1.0] http://www.umassd.edu/Catalog/CISGradCatalog/GradCISCourseDescriptions.html

date: 25-Jan-95
bytes: 10162
links: 13

title: Master of Computer Science Course Descriptions

outline: Master of Computer Science Course Descriptions

keys: automata

excerpt: Master of Computer Science Course Descriptions University of Massachusetts Dartmouth Master of Computer Science Course Descriptions CIS 521 Computability Theory This course explores more advanced topics in the computation theory, such as: generalized morphisms of finite automata, structural properties of finite automata, alternating automata, alternating Turing machines, recursive functions, uncomputability, computational complexity, NP-completeness, unsolvability and NP-completeness. Prerequisite: CIS 221 or permission of Instructor CIS 522 Algorithms and Complexity Evaluation of algorithms concerning their time and space complexity. Complexity hierarchies, axiomatic approach to computational complexity, NP complete problems and approximation algorithms for
descriptions:
Graduate Courses

ID828609: [score 0.2794, 2 of 3 terms, adj 1.0] http://149.170.198.4/combib/ref109.htm

date: 11-Dec-94
bytes: 1282
links: 13

title: Measures of Complexity: ref109

keys: automata finite

excerpt: Measures of Complexity: ref109 Complexity Reference: ref109 Authors: Banks,JF Sundaram,RK Year: 1990 Title: Repeated Games, Finite Automata and Complexity Journal: Games and Economic Behaviour , 2 , 9...

ID1430056: [score 0.2793, 2 of 3 terms, adj 1.0] http://www.cs.cornell.edu/Info/People/tah/symbolic_model_checking_for_real-time_systems.html

date: 04-Dec-94
bytes: 2035
links: 3

title: Henzinger/Nicollin/Sifakis/Yovine: Symbolic Model Checking for Real-time Systems

outline: Symbolic Model Checking for Real-time Systems

keys: automata finite

excerpt: Henzinger/Nicollin/Sifakis/Yovine: Symbolic Model Checking for Real-time Systems Symbolic Model Checking for Real-time Systems Thomas A. Henzinger , Xavier Nicollin, Joseph Sifakis, and Sergio Yovine We describe finite-state programs over real-numbered time in a guarded-command language with real-valued clocks or, equivalently, as finite automata with real-valued clocks. Model checking answers the question which states of a real-time program satisfy a branching-time specification (given in an extension of CTL with clock variables). We develop an algorithm that computes this set of states symbolically as a fixpoint of a functional on state predicates, without constructing the state space. For this purpose, we introduce a mu-calculus on computation trees over real

ID818650: [score 0.2783, 2 of 3 terms, adj 1.0] gopher://xyz.lanl.gov:70/11/chao-dyn/9310

date: 21-Dec-94
bytes: 1609
links: 8

keys: automata finite

excerpt: Select one of: * Monthly Index for chao-dyn 9310 * Cross-postings for chao-dyn 9310 * 9310001_Regular unimodal systems and factors of finite automata * 9310002_Non recursive proof of the KAM theorem Report-no 93-4-FISROM * 9310003_Truncated horseshoes and formal languages in chaotic scattering * 9310004_Chaotic, regular and unbounded behav...

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Lycos 0.9beta11 17-Feb-95 / 28-Feb-95 / fuzzy@cmu.edu