Probabilistic and Frequency Finite-State Transducers Kaspars Balodis Anda Berina Gleb Borovitsky Rusins Freivalds Ginta Garkaje Vladimirs Kacs Janis Kalejs.

Slides:



Advertisements
Similar presentations
The Contest between Simplicity and Efficiency in Asynchronous Byzantine Agreement Allison Lewko The University of Texas at Austin TexPoint fonts used in.
Advertisements

Size of Quantum Finite State Transducers Ruben Agadzanyan, Rusins Freivalds.
Random non-local games Andris Ambainis, Artūrs Bačkurs, Kaspars Balodis, Dmitry Kravchenko, Juris Smotrovs, Madars Virza University of Latvia.
School of Computing Clemson University Mathematical Reasoning  Goal: To prove correctness  Method: Use a reasoning table  Prove correctness on all valid.
WS Algorithmentheorie 03 – Randomized Algorithms (Primality Testing) Prof. Dr. Th. Ottmann.
COM 5336 Cryptography Lecture 7a Primality Testing
Formal Language, chapter 9, slide 1Copyright © 2007 by Adam Webber Chapter Nine: Advanced Topics in Regular Languages.
Randomized Algorithms Randomized Algorithms CS648 Lecture 1 1.
Quantum and probabilistic finite multitape automata Ginta Garkaje and Rusins Freivalds Riga, Latvia.
Probably Approximately Correct Learning Yongsub Lim Applied Algorithm Laboratory KAIST.
61 Nondeterminism and Nodeterministic Automata. 62 The computational machine models that we learned in the class are deterministic in the sense that the.
Fall 2004COMP 3351 Recursively Enumerable and Recursive Languages.
Finite Automata Finite-state machine with no output. FA consists of States, Transitions between states FA is a 5-tuple Example! A string x is recognized.
Computability and Complexity 7-1 Computability and Complexity Andrei Bulatov Recursion Theorem.
Recursively Enumerable and Recursive Languages
PRESENTED BY NASIR ABBAS. FLOW CHART CONTENTS What is a flow chart? Flow chart symbols.
Randomized Algorithms Prof. Dr. Th. Ottmann University of Freiburg
Complexity 19-1 Complexity Andrei Bulatov More Probabilistic Algorithms.
Quantum Automata Formalism. These are general questions related to complexity of quantum algorithms, combinational and sequential.
True/False. False True Subject May Go Here True / False ? Type correct answer here. Type incorrect answer here.
An Introduction to Algorithmic Information Theory Nuri Taşdemir
Fall 2005Costas Busch - RPI1 Recursively Enumerable and Recursive Languages.
Determine whether each curve below is the graph of a function of x. Select all answers that are graphs of functions of x:
Ch 1.3: Quantifiers Open sentences, or predicates, are sentences that contain one or more variables. They do not have a truth value until variables are.
PSPACE  IP Proshanto Mukherji CSC 486 April 23, 2001.
Computer Based Data Acquisition Basics. Outline Basics of data acquisition Analog to Digital Conversion –Quantization –Aliasing.
Regular Model Checking Ahmed Bouajjani,Benget Jonsson, Marcus Nillson and Tayssir Touili Moran Ben Tulila
On Probabilistic Snap-Stabilization Karine Altisen Stéphane Devismes University of Grenoble.
Randomized Turing Machines
On Probabilistic Snap-Stabilization Karine Altisen Stéphane Devismes University of Grenoble.
computer
Computation Model and Complexity Class. 2 An algorithmic process that uses the result of a random draw to make an approximated decision has the ability.
. CLASSES RP AND ZPP By: SARIKA PAMMI. CONTENTS:  INTRODUCTION  RP  FACTS ABOUT RP  MONTE CARLO ALGORITHM  CO-RP  ZPP  FACTS ABOUT ZPP  RELATION.
PROBABILISTIC COMPUTATION By Remanth Dabbati. INDEX  Probabilistic Turing Machine  Probabilistic Complexity Classes  Probabilistic Algorithms.
Data Stream Algorithms Ke Yi Hong Kong University of Science and Technology.
Worst case analysis of non-local games
Umans Complexity Theory Lectures Lecture 7b: Randomization in Communication Complexity.
BOOLEAN ALGEBRA Only involves in calculations of TRUE and FALSE; either be inputs or output. When a logic statement is TRUE it is assigned a Boolean logic.
September1999 CMSC 203 / 0201 Fall 2002 Week #15 – 2/4/6 December 2002 Prof. Marie desJardins.
NP-Completness Turing Machine. Hard problems There are many many important problems for which no polynomial algorithms is known. We show that a polynomial-time.
Recursively Enumerable and Recursive Languages
Which list of numbers is ordered from least to greatest? 10 –3, , 1, 10, , 1, 10, 10 2, 10 – , 10 –3, 1, 10, , 10 –3,
Problem of the Day Fractions, Decimals, Percents.

Turing Machines. The next level of Machine… PDAs improved on FSAs by adding memory. We make the memory more flexible to do more complicated tasks.
1 Recursively Enumerable and Recursive Languages.
Turing’s Thesis.
Non Deterministic Automata
Busch Complexity Lectures: Reductions
Linear Bounded Automata LBAs
Reductions Costas Busch - LSU.
LESSON 3.
Turing’s Thesis Costas Busch - RPI.
Uncountable Classical and Quantum Complexity Classes
CSE322 The Chomsky Hierarchy
Computers & Programming Languages
دانشگاه شهیدرجایی تهران
Non-Deterministic Finite Automata
تعهدات مشتری در کنوانسیون بیع بین المللی
Non Deterministic Automata
Chapter Nine: Advanced Topics in Regular Languages
بسمه تعالی کارگاه ارزشیابی پیشرفت تحصیلی
The Off-Line Machine Input File read-only (once) Input string
True or False: {image} is one-to-one function.
Variations of the Turing Machine
Homing sequence: to identify the final state.
CS21 Decidability and Tractability
Pre-Algebra FSA Review Session
Lecture 2-6 Complexity for Computing Influence Spread
True or False True or False
Presentation transcript:

Probabilistic and Frequency Finite-State Transducers Kaspars Balodis Anda Berina Gleb Borovitsky Rusins Freivalds Ginta Garkaje Vladimirs Kacs Janis Kalejs Ilja Kucevalovs Janis Rocans Madars Virza

Probabilistic transducers We explore so-called Las Vegas transducers, which give a false answer with probability 0, and prove theorems, such as if any Las Vegas transducer can compute a relation with probability greater than ½, then this relation can be computed with a deterministic transducer.

Deterministic transducers with help symbols We observe deterministic transducers where one or more added help symbols are viewable at any time during the computation of a relation, and compare these with Las Vegas transducers, proving that, for example, if you need n help symbols to compute a relation, a Las Vegas transducer can compute this relation with probability 1 / n,

Frequency transducers A frequency transducer is a transducer, which has n input tapes with unique inputs and n output tapes, that (m,n)-calculates a relation on all the tapes in a way, that at least m out of the n output tapes produce a correct result.

Thank you for your attention