Input: Here, accuracy is measured by error rate, which is defined as:

accuracy

error rate


Input: From this perspective, SVM is closely related to other fundamental classification algorithms such as regularized least-squares logistic regression.

SVM

regularized least-squares

logistic regression

classification algorithms


Input: Brion James portrays Leon Kowalski, a combat and laborer replicant, and Joanna Cassidy portrays Zhora, an assassin replicant.

Brion James

Leon Kowalski

Joanna Cassidy

Zhora


Input: The first picture to be scanned, stored, and recreated in digital pixels was displayed on the Standards Eastern Automatic Computer (SEAC) at NIST.

Standards Eastern Automatic Computer

SEAC

NIST


Input: Segmenting the text into topics or discourse turns might be useful in some natural processing tasks: it can improve information retrieval or speech recognition significantly (by indexing / recognizing documents more precisely or by giving the specific part of a document corresponding to the query as a result).

Segmenting the text into topics

information retrieval

speech recognition

discourse turns


Input: At Indiana University in 1999 he organized such a symposium, and in April 2000, he organized a larger symposium entitled Spiritual Robots at Stanford University, in which he moderated a panel consisting of Ray Kurzweil, Hans Moravec, Kevin Kelly, Ralph Merkle, Bill Joy, Frank Drake, John Henry Holland and John Koza.

Indiana University

Stanford University

Spiritual Robots

Ray Kurzweil

Hans Moravec

Kevin Kelly

Ralph Merkle

Bill Joy

Frank Drake

John Henry Holland

John Koza


Input: It considers both the precision p and the recall r of the test to compute the score: p is the number of correct positive results divided by the number of all positive results returned by the classifier, and r is the number of correct positive results divided by the number of all relevant samples (all samples that should have been identified as positive).

precision

p

recall

r

p

r


Input: Since the Google acquisition, the company has notched up a number of significant achievements, perhaps the most notable being the creation of AlphaGo, a program that defeated world champion Lee Sedol at the complex game of Go.

Google

AlphaGo

Lee Sedol

Go


Input: Representing words considering their context through fixed size dense vectors (word embedding s) has become one the most fundamental blocks in several NLP systems. an unsupervised disambiguation system uses the similarity between word senses in a fixed context window to select the most suitable word sense using a pre-trained word embedding model and WordNet.

word embedding

word sense

word embedding

NLP

unsupervised disambiguation system

WordNet


Input: Machine learning techniques, either Supervised learning or Unsupervised learning, have been used to induce such rules automatically.

Machine learning

Supervised learning

Unsupervised learning


Input: In 1969, Scheinman invented the Stanford arm,

Scheinman

Stanford arm


Input: Since the Log loss is differentiable, a gradient-based method can be used to optimize the model.

Log loss

gradient-based method


Input: In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with learning algorithm s that analyze data used for classification and regression analysis.

machine learning

supervised learning

support-vector machines

SVMs

support-vector networks

classification

regression analysis


Input: , (2002) as the automatic metric for Machine translation (MT) evaluation, many other methods have been proposed to revise or improve it, such as TER, METEOR, Banerjee and Lavie, (2005) etc.

Machine translation

MT

TER

METEOR

Banerjee

Lavie


Input: It includes an upper ontology, created by the IEEE working group P1600.1 (originally by Ian Niles and Adam Pease).

upper ontology

IEEE

Ian Niles

Adam Pease


Input: In Cryo Electron Tomography, where the limited number of projections are acquired due to the hardware limitations and to avoid the biological specimen damage, it can be used along with compressive sensing techniques or regularization functions (e.g. Huber loss) to improve the reconstruction for better interpretation.

Cryo Electron Tomography

compressive sensing techniques

regularization functions

Huber loss


Input: An implementation of several whitening procedures in R, including ZCA-whitening and PCA whitening but also CCA whitening, is available in the whitening R package published on CRAN.

whitening

R

ZCA-whitening

PCA whitening

CCA whitening

whitening R package

CRAN


Input: Today, the field has become even more daunting and complex with the addition of circuit, systems and signal analysis and design languages and software, from MATLAB and Simulink to NumPy, VHDL, PSpice, Verilog and even Assembly language.

MATLAB

Simulink

NumPy

VHDL

PSpice

Verilog

Assembly language


Input: The company was founded by Kiichiro Toyoda in 1937, as a spinoff from Sakichi Toyoda company Toyota Industries to create automobiles.

Kiichiro Toyoda

Sakichi Toyoda

Toyota Industries

automobiles


Input: Unsupervised learning, on the other hand, assumes training data that has not been hand-labeled, and attempts to find inherent patterns in the data that can then be used to determine the correct output value for new data instances .. A combination of the two that has recently been explored is semi-supervised learning, which uses a combination of labeled and unlabeled data (typically a small set of labeled data combined with a large amount of unlabeled data).

Unsupervised learning

semi-supervised learning


Input: Despite those humanoid robots for utilitarian uses, there are some humanoid robots which aims at entertainment uses, such as Sony' s QRIO and Wow Wee' s RoboSapien.

Sony

Wow Wee

QRIO

RoboSapien


Input: Webber became a Fellow of the Association for the Advancement of Artificial Intelligence in 1991,

Webber

Association for the Advancement of Artificial Intelligence


Input: With this company he was developing data-mining and database technology, more specific high-level ontologies for intelligence and automated natural language understanding.

data-mining

database

automated natural

language understanding


Input: However, in the last years, one can observe appearing of different e-services and related initiatives in developing countries such as Project Nemmadi, MCA21 Mission Mode Project or Digital India even more, in India; Electronic Government Directorate in Pakistan; etc.

Project Nemmadi

MCA21 Mission Mode Project

Digital India

India

Pakistan

Electronic Government Directorate


Input: He received a PhD in Radio Physics and Electronics from the Rajabazar Science College campus of University of Calcutta in 1979 as a student of Indian Statistical Institute, and another PhD in Electrical Engineering along with Diploma of the Imperial College from Imperial College, University of London, in 1982.

PhD

PhD

Diploma of the Imperial College

Radio Physics

Electronics

Electrical Engineering

Rajabazar Science College

University of Calcutta

Indian Statistical Institute

Imperial College

University of London


Input: Expo II was announced as being the locale for the world premiere of several films never before seen in 3D, including The Diamond Wizard and the Universal short, Hawaiian Nights with Mamie Van Doren and Pinky Lee.

Expo II

The Diamond Wizard

Hawaiian Nights

Mamie Van Doren

Pinky Lee


Input: The maximum subarray problem was proposed by Ulf Grenander in 1977 as a simplified model for maximum likelihood estimation of patterns in digitized images.

Ulf Grenander

maximum likelihood estimation


Input: The iPhone 4S, iPad 3, iPad Mini 1G, iPad Air, iPad Pro 1G, iPod Touch 5G and later, all come with a more advanced voice assistant called Siri.

iPhone 4S

iPad 3

iPad Mini 1G

iPad Air

iPad Pro 1G

iPod Touch 5G

Siri


Input: It's easy to check that the logistic loss and binary cross entropy loss (Log loss) are in fact the same (up to a multiplicative constant math \ frac {1} {\ log (2)} / math) .The cross entropy loss is closely related to the Kullback-Leibler divergence between the empirical distribution and the predicted distribution.

logistic loss

binary cross entropy loss

Log loss

cross entropy loss

Kullback-Leibler divergence


Input: The EM algorithm is used to find (local) maximum likelihood parameters of a statistical model in cases where the equations cannot be solved directly.

EM algorithm

maximum likelihood


Input: This research was fundamental to the development of modern techniques of speech synthesis, reading machines for the blind, the study of speech perception and speech recognition, and the development of the motor theory of speech perception.

speech synthesis

reading machines for the blind

speech perception

speech recognition

motor theory of speech perception


Input: The Arduino integrated development environment (IDE) is a cross-platform application (for Windows, macOS, and Linux) that is written in the programming language Java.

Arduino

Windows

macOS

Linux

integrated development environment

IDE

cross-platform application

Java


Input: Neural network research stagnated after the publication of machine learning research by Marvin Minsky and Seymour Papert (1969).

Neural network

machine learning

Marvin Minsky

Seymour Papert


Input: Only a few non-Japanese companies ultimately managed to survive in this market, the major ones being: Adept Technology, Stäubli, the Sweden - Switzerland company ABB Asea Brown Boveri, the Germany company KUKA Robotics and the Italy company Comau.

Adept Technology

Stäubli

ABB Asea Brown Boveri

KUKA Robotics

Comau

Sweden

Switzerland

Germany

Italy


Input: The research activities include an annual research conference, the RuleML Symposium, also known as RuleML for short.

RuleML Symposium

RuleML


Input: Concepts are used as formal tools or models in mathematics, computer science, databases and artificial intelligence where they are sometimes called classes, schema or categories.

mathematics

computer science

databases

artificial intelligence


Input: He has won awards from the American Psychological Association, the National Academy of Sciences, the Royal, the Cognitive Neuroscience Society and the American Humanist Association.

American Psychological Association

National Academy of Sciences

Royal

Cognitive Neuroscience Society

American Humanist Association


Input: Starring Harrison Ford, Rutger Hauer and Sean Young, it is loosely based on Philip K. Dick' s novel Do Androids Dream of Electric Sheep? (1968).

Harrison Ford

Rutger Hauer

Sean Young

Philip K. Dick

Do Androids Dream of Electric Sheep?


Input: Image segmentation using k-means clustering algorithms has long been used for pattern recognition, object detection, and medical imaging.

Image segmentation

object detection

k-means clustering algorithms

pattern recognition

medical imaging


Input: General sampling from the truncated normal can be achieved using approximations to the normal CDF and the probit function, and R has a function codertnorm () / code for generating truncated-normal samples.

CDF

probit function

R


Input: He has also received honorary doctorates from the universities of Newcastle, Surrey, Tel Aviv University,, Simon Fraser University and the University of Tromsø.

universities of Newcastle

Surrey

Tel Aviv University

Simon Fraser University

University of Tromsø


Input: A Java implementation using zero based array indexes along with a convenience method for printing the solved order of operations:

Java


Input: Such networks are commonly trained under a Cross entropy (or cross-entropy) regime, giving a non-linear variant of multinomial logistic regression.

Cross entropy

cross-entropy

multinomial logistic regression


Input: The ACL has a European (European Chapter of the Association for Computational Linguistics)

ACL

European Chapter of the Association for Computational Linguistics

European


Input: Two professors, Hal Abelson and Gerald Jay Sussman, chose to remain neutral - their group was referred to variously as Switzerland and Project MAC for the next 30 years.

Hal Abelson

Gerald Jay Sussman

Switzerland

Project MAC


Input: Following his PhD, Ghahramani moved to the University of Toronto in 1995 as an ITRC Postdoctoral Fellow in the Artificial Intelligence Lab, working with Geoffrey Hinton.

PhD

Ghahramani

Geoffrey Hinton

University of Toronto

ITRC

Artificial Intelligence Lab


Input: Subsequent works focused on addressing these problems, but it was not until the advent of the modern computer and the popularisation of Maximum Likelihood (MLE) parameterisation techniques that research really took off.

Maximum Likelihood

MLE


Input: The series was produced by David Fincher, and starred Kevin Spacey.

David Fincher

Kevin Spacey


Input: Due to limits in computing power, current in silico methods usually must trade speed for accuracy; e.g., use rapid protein docking methods instead of computationally costly free energy calculation s.

accuracy

protein docking

free energy calculation


Input: It had over 30 locations in the U.S., Canada, Mexico, Brazil and Argentina.

U.S.

Canada

Mexico

Brazil

Argentina


Input: An example of a typical computer vision computation pipeline for Facial recognition system using k -NN including feature extraction and dimension reduction pre-processing steps (usually implemented with OpenCV):

computer vision

Facial recognition system

OpenCV

k -NN

feature extraction

dimension reduction


Input: It has a rich set of features, libraries for constraint logic programming, multithreading, unit testing, GUI, interfacing to Java, ODBC and others, literate programming, a web server, SGML, RDF, RDFS, developer tools (including an IDE with a GUI debugger and GUI profiler), and extensive documentation.

constraint logic programming

literate programming

multithreading

unit testing

GUI

web server

SGML

RDF

RDFS

IDE

GUI debugger

GUI profiler

Java

ODBC


Input: In computer vision and image processing, the notion of scale space representation and Gaussian derivative operators is as a canonical multi-scale representation.

computer vision

image processing

scale space representation

Gaussian derivative operators

canonical multi-scale representation


Input: He is also the President of the Neural Information Processing Systems Foundation, a non-profit organization that oversees the annual Conference on Neural Information Processing Systems Conference.

Neural Information Processing Systems Foundation

Conference on Neural Information Processing Systems Conference


Input: For regression analysis problems the squared error can be used as a loss function, for classification the cross entropy can be used.

regression analysis

classification

squared error

cross entropy

loss function


Input: Lafferty served many prestigious positions, including: 1) program co-chair and general co-chair of the Neural Information Processing Systems (Conference on Neural Information Processing Systems) Foundation conferences; 2) co-director of CMU's new Ph.D. Machine Learning Ph.D. Program; 3) associate editor of the Journal of Machine Learning Research

Lafferty

Neural Information Processing Systems

Conference on Neural Information Processing Systems

Journal of Machine Learning Research

CMU

Machine Learning


Input: Convex algorithms, such as AdaBoost and LogitBoost, can be defeated by random noise such they can't learn basic and learnable combinations of weak hypotheses.

Convex algorithms

AdaBoost

LogitBoost


Input: Apertium is a shallow-transfer machine translation system, which uses finite state transducer s for all of its lexical transformations, and hidden Markov model s for part-of-speech tagging or word category disambiguation.

Apertium

shallow-transfer machine translation system

finite state transducer

hidden Markov model

part-of-speech tagging

word category disambiguation


Input: The natural gradient of mathE f (x) / math, complying with the Fisher information metric (an informational distance measure between probability distributions and the curvature of the relative entropy), now reads

natural gradient

Fisher information metric

relative entropy


Input: The S programming language inspired the systems' S' -PLUS and R.

S programming language

R

' S' -PLUS


Input: The most influential implementation of Planner was the subset of Planner, called Micro-Planner, implemented by Gerald Jay Sussman, Eugene Charniak and Terry Winograd.

Planner

Planner

Micro-Planner

Gerald Jay Sussman

Eugene Charniak

Terry Winograd


Input: In 1779 the Germany - Denmark scientist Christian Gottlieb Kratzenstein won the first prize in a competition announced the Russian Imperial Academy of Sciences and Arts for models he built of the human vocal tract that could produce the five long vowel sounds (in International Phonetic Alphabet notation:

Germany

Denmark

Christian Gottlieb Kratzenstein

Russian

vocal tract

vowel sounds

International Phonetic Alphabet

Imperial Academy of Sciences and Arts


Input: New features in Office XP include smart tags, a selection-based search feature that recognizes different types of text in a document so that users can perform additional actions; a task pane interface that consolidates popular menu bar commands on the right side of the screen to facilitate quick access to them; new document collaboration capabilities, support for MSN Groups and SharePoint; and integrated handwriting recognition and speech recognition capabilities.

Office XP

MSN Groups

SharePoint

smart tags

selection-based search feature

task pane interface

document collaboration

handwriting recognition

speech recognition


Input: In many applications the units of these networks apply a sigmoid function as an activation function.

sigmoid function

activation function


Input: In 2001, Mehler was elected a foreign honorary member of the American Academy of Arts and Sciences, and in 2003, he was elected a Fellow of the American Association for the Advancement of Science.

Mehler

American Academy of Arts and Sciences

American Association for the Advancement of Science


Input: The extension of this concept to non-binary classifications yields the confusion matrix.

non-binary classifications

confusion matrix


Input: An updated measurement noise variance estimate can be obtained from the maximum likelihood calculation

maximum likelihood


Input: In machine learning, the perceptron is an algorithm for supervised learning of binary classification.

machine learning

supervised learning

perceptron

binary classification


Input: She has also served as Area Chair of several machine learning and vision conferences including Conference on Neural Information Processing Systems, International Conference on Learning Representations, Conference on Computer Vision and Pattern Recognition, International Conference on Computer Vision, and European Conference on Computer Vision.

machine learning

vision

Conference on Neural Information Processing Systems

International Conference on Learning Representations

Conference on Computer Vision and Pattern Recognition

International Conference on Computer Vision

European Conference on Computer Vision


Input: The condensation algorithm has also been used for facial recognition system in a video sequence.

condensation algorithm

facial recognition system


Input: Information Dissemination is also part of ELRA's missions which is carried through both the organisation of the conference LREC and the Language Resources and Evaluation Journal edited by Springer.

Information Dissemination

ELRA

LREC

Language Resources and Evaluation Journal

Springer


Input: In linear time-invariant (LTI) system theory, control theory, and in digital signal processing or signal processing, the relationship between the input signal, math \ displaystyle x (t) / math, to output signal, math \ displaystyle y (t) / math, of an LTI system is governed by a convolution operation:

linear time-invariant (LTI) system theory

control theory

digital signal processing

signal processing

LTI system

convolution


Input: Due to its generality, the field is studied in many other disciplines, such as game theory, control theory, operations research, information theory, simulation-based optimization, multi-agent systems, swarm intelligence, statistics and genetic algorithm s.

game theory

control theory

operations research

information theory

simulation-based optimization

swarm intelligence

statistics

multi-agent systems

genetic algorithm


Input: Stochastic gradient descent is a popular algorithm for training a wide range of models in machine learning, including (linear) support vector machine s, logistic regression (see, e.g., Vowpal Wabbit) and graphical model s.Jenny Rose Finkel, Alex Kleeman, Christopher D. Manning (2008).

Stochastic gradient descent

support vector machine

logistic regression

Vowpal Wabbit

graphical model

machine learning

s.Jenny Rose Finkel

Alex Kleeman

Christopher D. Manning


Input: In August 2011, it was announced that Hitachi would donate an electron microscope to each of five universities in Indonesia (the University of North Sumatra in Medan, the Indonesian Christian University in Jakarta, Padjadjaran University in Bandung, Jenderal Soedirman University in Purwokerto and Muhammadiyah University in Malang).

Hitachi

electron microscope

Indonesia

University of North Sumatra

Indonesian Christian University

Padjadjaran University

Jenderal Soedirman University

Muhammadiyah University

Medan

Jakarta

Bandung

Purwokerto

Malang


Input: Optimization techniques of operations research such as linear programming or dynamic programming are often impractical for large scale software engineering problems because of their computational complexity.

Optimization

operations research

software engineering

linear programming

dynamic programming

computational complexity


Input: Sensitivity is not the same as the precision or positive predictive value (ratio of TRUE positives to combined TRUE and FALSE positives), which is as much a statement about the proportion of actual positives in the population being tested as it is about the test.

Sensitivity

precision

positive predictive value

TRUE positives

TRUE and FALSE positives


Input: The screenplay by Hampton Fancher! -- Not titled Android initially - See Sammon, pp. 32 and 38 for explanation -- was optioned in 1977. Sammon, pp. 23-30 Producer Michael Deeley became interested in Fancher's draft and convinced director Ridley Scott to film it.

Hampton Fancher

Sammon

Sammon

Michael Deeley

Fancher

Ridley Scott

Android


Input: Text analysis involves information retrieval, lexical analysis to study word frequency distributions, pattern recognition, tagging / annotation, information extraction, data mining techniques including link and association analysis, visualization, and predictive analytics.

Text analysis

pattern recognition

data mining

information retrieval

lexical analysis

tagging / annotation

information extraction

link and association analysis

visualization

predictive analytics

word frequency distributions


Input: Several metrics use WordNet, a manually constructed lexical database of English words.

WordNet

English


Input: The system uses a combination of techniques from computational linguistics, information retrieval and knowledge representation for finding answers.

computational linguistics

information retrieval

knowledge representation for finding answers


Input: As a performance metric, the uncertainty coefficient has the advantage over simple accuracy in that it is not affected by the relative sizes of the different classes.

uncertainty coefficient

accuracy


Input: Researchers have attempted a number of methods such as optical flow, Kalman filtering, Hidden Markov model s, etc.

optical flow

Kalman filtering

Hidden Markov model


Input: She has held the positions of President, Vice President, and Secretary-Treasurer of the Association for Computational Linguistics and has been a board member and secretary of the board of the Computing Research Association.

Association for Computational Linguistics

Computing Research Association


Input: Like other similar languages such as APL and MATLAB, R supports matrix arithmetic.

APL

R

MATLAB

matrix arithmetic


Input: On 7 June 2014, in a Turing test competition at the Royal Society, organised by Kevin Warwick of the University of Reading to mark the 60th anniversary of Turing's death, Goostman won after 33% of the judges were convinced that the bot was human.

Turing test

60th anniversary of Turing's death

Royal Society

Kevin Warwick

Goostman

University of Reading


Input: A collaborative robot or cobot is a robot that can safely and effectively interact with human workers while performing simple industrial tasks.

collaborative robot

cobot


Input: This overall framework has been applied to a large variety of problems in computer vision, including feature detection, feature classification, image segmentation, image matching, motion estimation, computation of shape cues and object recognition.

computer vision

feature detection

feature classification

image segmentation

image matching

motion estimation

computation of shape cues

object recognition


Input: In many practical applications, parameter estimation for naive Bayes models uses the method of maximum likelihood; other words, one can work with the naive Bayes model without accepting Bayesian probability or using any Bayesian methods.

parameter estimation

naive Bayes models

maximum likelihood

naive Bayes

Bayesian probability

Bayesian methods


Input: Brothers - Victor Gershevich Katz, American mathematician, professor at the Massachusetts Institute of Technology; Mikhail Gershevich Katz, Israeli mathematician, graduate of Harvard and Columbia (Ph.D., 1984) universities, professor at Bar-Ilan University, author of the monograph Systolic Geometry and Topology (Mathematical Surveys and Monographs, vol.

Victor Gershevich Katz

Mikhail Gershevich Katz

American

Israeli

Ph.D.

Systolic Geometry and Topology

Mathematical Surveys and Monographs

Massachusetts Institute of Technology

Harvard

Columbia

Bar-Ilan University


Input: In 2000 Manuel Toharia, a speaker at previous Campus Parties, and director of Príncipe Felipe's Museum of Sciences in Valencia's City of arts and Sciences suggested that Ragageles expand and make the event more international by moving it to the famous museum.

Manuel Toharia

Ragageles

Campus Parties

Príncipe Felipe's Museum of Sciences

Valencia's City of arts and Sciences


Input: Within 20 minutes, a facial recognition system identifies personal information including family name, ID number and address which are displayed in the street on an advertising screen.

facial recognition system


Input: Recent research has increasingly focused on unsupervised learning and semi-supervised learning algorithms.

unsupervised learning

semi-supervised learning


Input: Computation of this example using Python code:

Python


Input: Today, however, many aspects of speech recognition have been taken over by a deep learning method called Long short-term memory (LSTM), a recurrent neural network published by Sepp Hochreiter & Jürgen Schmidhuber in 1997.

speech recognition

deep learning

Long short-term memory

LSTM

recurrent neural network

Sepp Hochreiter

Jürgen Schmidhuber


Input: In preliminary experimental results with noisy datasets, BrownBoost outperformed AdaBoost' s generalization error; however, LogitBoost performed as well as BrownBoost.

BrownBoost

AdaBoost

LogitBoost

BrownBoost


Input: Evolutionary programming was introduced by Lawrence J. Fogel in the US, while John Henry Holland called his method a genetic algorithm.

Evolutionary programming

genetic algorithm

Lawrence J. Fogel

John Henry Holland

US


Input: The back-of-the-envelope calculations by Doug, Alan, and their colleagues (including Marvin Minsky, Allen Newell, Edward Feigenbaum, and John McCarthy) indicated that that effort would require between 1000 and 3000 person-years of effort, far beyond the standard academic project model.

Doug

Alan

Marvin Minsky

Allen Newell

Edward Feigenbaum

John McCarthy


Input: Common criteria are the Mean Squared Error criterion implemented in MSECriterion and the cross-entropy criterion implemented in NLLCriterion.

Mean Squared Error

MSECriterion

cross-entropy criterion

NLLCriterion


Input: Zurada has served the engineering profession as a long-time volunteer of IEEE: as 2014 IEEE Vice-President-Technical Activities (TAB Chair), as President of IEEE Computational Intelligence Society in 2004-05 and the ADCOM member in 2009-14, 2016-18 and earlier years.

Zurada

IEEE

2014 IEEE Vice-President-Technical Activities

IEEE Computational Intelligence Society

ADCOM


Input: In general, computational linguistics draws upon the involvement of linguists, computer science, experts in artificial intelligence, mathematicians, logicians, philosophers, cognitive scientists, cognitive psychologists, psycholinguists, anthropologists and neuroscientists, among others.

computational linguistics

computer science

artificial intelligence


Input: Techniques such as dynamic Markov Networks, Convolutional neural network and Long short-term memory are often employed to exploit the inter-frame correlations.

dynamic Markov Networks

Convolutional neural network

Long short-term memory


Input: Unimate was the first industrial robot,

Unimate

industrial robot


Input: Together with Geoffrey Hinton and Yann LeCun, Bengio won the 2018 Turing Award.

Geoffrey Hinton

Yann LeCun

Bengio

2018 Turing Award


Input: Additional series were filmed at the UK venue for specific sectors of the global market, including two series of Robot Wars Extreme Warriors with United States competitors for the TNN network (hosted by Mick Foley with Rebecca Grant serving as pit reporter), two of Dutch Robot Wars for distribution in the Netherlands and a single series for Germany.

UK

United States

Netherlands

Germany

Robot Wars Extreme Warriors

Dutch Robot Wars

TNN network

Mick Foley

Rebecca Grant


Input: For many years starting from 1986, Miller directed the development of WordNet, a large computer-readable electronic reference usable in applications such as search engines.

Miller

WordNet

search engines


Input: Since 2009, the recurrent neural network s and deep feedforward neural networks developed in the research group of Jürgen Schmidhuber at the Swiss AI Lab IDSIA have won several international handwriting competitions ..

recurrent neural network

deep feedforward neural networks

Jürgen Schmidhuber

Swiss AI Lab IDSIA

international handwriting competitions


Input: The software is implemented in C + + and it is wrapped for Python.

C + +

Python


Input: In 1857, at the request of the Tokugawa Shogunate, a group of Dutch engineers began work on the Nagasaki Yotetsusho, a modern, Western-style foundry and shipyard near the Dutch settlement of Dejima, at Nagasaki.

Tokugawa Shogunate

Dutch

Nagasaki Yotetsusho

Dutch

Dejima

Nagasaki


Input: We make as well as possible precise by measuring the mean squared error between mathy / math and math \ hat {f} (x; D) / math: we want math (y - \ hat {f} (x; D)) ^ 2 / math to be minimal, both for mathx _ 1, \ dots, x _ n / math and for points outside of our sample.

mean squared error


Input: He subsequently extended an invitation for Wydner to attend the annual meeting of the American Translators Association that following October where the Weidner Machine Translation System hailed a hoped-for breakthrough in machine translation.

Wydner

American Translators Association

Weidner Machine Translation System

machine translation


Input: At the 2018 Conference on Neural Information Processing Systems (NeurIPS) researchers from Google presented the work.

2018 Conference on Neural Information Processing Systems

NeurIPS

Google


Input: The Baum-Welch algorithm uses the well known EM algorithm to find the maximum likelihood estimate of the parameters of a hidden Markov model given a set of observed feature vectors.

Baum-Welch algorithm

EM algorithm

hidden Markov model

maximum likelihood estimate


Input: ) In addition to the taxonomic information contained in OpenCyc, ResearchCyc includes significantly more semantic knowledge (i.e., additional facts and rules of thumb) involving the concepts in its knowledge base; it also includes a large lexicon, English parsing and generation tools, and Java based interfaces for knowledge editing and querying.

OpenCyc

ResearchCyc

large lexicon, English parsing and generation tools

interfaces for knowledge editing and querying

knowledge base

Java


Input: The Hough transform is a feature extraction technique used in image analysis, computer vision, and digital image processing.

Hough transform

feature extraction

image analysis

computer vision

digital image processing


Input: In 1978, the PUMA (Programmable Universal Machine for Assembly) robot was developed by Unimation from Vicarm (Victor Scheinman) and with support from General Motors.

PUMA

Programmable Universal Machine for Assembly

Unimation

Vicarm

General Motors

Victor Scheinman


Input: LSTM was proposed in 1997 by Sepp Hochreiter and Jürgen Schmidhuber.

LSTM

Sepp Hochreiter

Jürgen Schmidhuber


Input: The four outcomes can be formulated in a 2 × 2 contingency table or confusion matrix, as follows:

contingency table

confusion matrix


Input: He also contributed much through the establishment of ELRA and the LREC conference.

ELRA

LREC conference


Input: A popular application for serial robots in today's industry is the pick-and-place assembly robot, called a SCARA robot, which has four degrees of freedom.

assembly

SCARA robot


Input: He was one of the founding members and former chair (2006-2008) of the Special Interest Group on Web as Corpus (SIGWAC) of the Association for Computational Linguistics and also one of the founding organizers of SENSEVAL.

Special Interest Group on Web as Corpus

SIGWAC

Association for Computational Linguistics

SENSEVAL


Input: As a platform, LinguaStream provides an extensive Java API.

LinguaStream

Java API


Input: The robot kit is Android-based, and it is programmed using Java, the Blocks programming interface, or other Android programming systems.

Java

Blocks programming interface

Android programming systems


Input: The method of defining the linked list specifies the use of a depth-first search or a breadth-first search.

depth-first search

breadth-first search


Input: These regions could signal the presence of objects or parts of objects in the image domain with application to object recognition and / or object video tracking.

object recognition

object video tracking


Input: An example of a semantic network is WordNet, a lexical database of English.

semantic network

WordNet

English


Input: Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers.

Speech recognition

recognition and translation of spoken language

computer science

computational linguistics


Input: Artificial intelligence has retained the most attention regarding applied ontology in subfields like natural language processing within machine and knowledge representation, but ontology editors are being used often in a range of fields like education without the intent to contribute to AI.

Artificial intelligence

natural language processing

AI

applied ontology

machine

knowledge representation


Input: This update rule is in fact the stochastic gradient descent update for linear regression.

stochastic gradient descent

linear regression


Input: He was elected to the American Academy of Arts and Sciences and the National Academy of Sciences and has received a series of awards:

American Academy of Arts and Sciences

National Academy of Sciences


Input: The most recent school of thought on Honda's strategy was put forward by Gary Hamel and C. K. Prahalad in 1989.

Honda

Gary Hamel

C. K. Prahalad


Input: Where BLEU simply calculates n-gram precision adding equal weight to each one, NIST also calculates how informative a particular n-gram is.

BLEU

n-gram precision

NIST

n-gram


Input: He was honored with the 2019 Lifetime Achievement Award from the Association for Computational Linguistics (ACL).

2019 Lifetime Achievement Award

Association for Computational Linguistics

ACL


Input: Sycara is a Fellow of Institute of Electrical and Electronics Engineers (IEEE), and a Fellow of American Association for Artificial Intelligence (AAAI).

Sycara

Institute of Electrical and Electronics Engineers

IEEE

American Association for Artificial Intelligence

AAAI


Input: The following MATLAB code demonstrates a concrete solution for solving the non-linear system of equations presented in the previous section: See also

MATLAB

non-linear system


Input: Pattern recognition systems are in many cases trained from labeled training data (supervised learning) but when no labeled data are available other algorithms can be used to discover previously unknown patterns (unsupervised learning).

Pattern recognition systems

supervised learning

unsupervised learning


Input: It was first used by Lawrence J. Fogel in the US in 1960 in order to use simulated evolution as a learning process aiming to generate artificial intelligence.

Lawrence J. Fogel

US

artificial intelligence


Input: Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning.

Reinforcement learning

machine learning

supervised learning

unsupervised learning


Input: In such cases, cloud computing and open source programming language R can help smaller banks to adopt risk analytics and support branch level monitoring by applying predictive analytics.

cloud computing

predictive analytics

R


Input: One of the first versions of the theorem was proved by George Cybenko in 1989 for sigmoid function activation functions. Cybenko G. (1989), 2 (4), 303-314.

George Cybenko

Cybenko G.

sigmoid function


Input: In this process, which is known as cross-validation, the MSE is often called the mean squared prediction error, and is computed as

cross-validation

MSE

mean squared prediction error


Input: OMR is generally distinguished from optical character recognition (OCR) by the fact that a complicated pattern recognition engine is not required.

OMR

optical character recognition

OCR

pattern recognition


Input: In 2018 and 2019, the Championship was be held in Houston and Detroit, Michigan at the TCF Center and Ford Field.

Houston

Detroit

Michigan

TCF Center

Ford Field


Input: Classification can be thought of as two separate problems - binary classification and multiclass classification.

Classification

binary classification

multiclass classification


Input: Two examples of popular parallel robots are the Stewart platform and the Delta robot.

parallel robots

Stewart platform

Delta robot


Input: (Nevertheless, the ReLU activation function, which is non-differentiable at 0, has become quite popular, e.g. in AlexNet)

ReLU activation function

AlexNet


Input: The F-score is often used in the field of information retrieval for measuring search, document classification, and query classification performance. and so F_beta is seen in wide application.

F-score

information retrieval

search

document classification

query classification


Input: This is done by modeling the received signal then using a statistical estimation method such as maximum likelihood (ML), majority voting (MV) or maximum a posteriori (MAP) to make a decision about which target in the library best fits the model built using the received signal.

maximum likelihood

ML

majority voting

MV

maximum a posteriori

MAP


Input: Sowa received a BS in mathematics from Massachusetts Institute of Technology in 1962, an MA in applied from Harvard University in 1966, and a PhD in computer science from the Vrije Universiteit Brussel in 1999 on a dissertation titled Knowledge Representation: Logical, Philosophical, and Computational Foundations.

Sowa

BS

MA

PhD

Knowledge Representation: Logical, Philosophical, and Computational Foundations

mathematics

applied

computer science

Massachusetts Institute of Technology

Harvard University

Vrije Universiteit Brussel


Input: Since paraphrase recognition can be posed as a classification problem, most standard evaluations metrics such as accuracy, f1 score, or an ROC curve do relatively well.

paraphrase recognition

classification

accuracy

f1 score

ROC curve


Input: This makes it practical for analyzing large data sets (hundreds or thousands of taxa) and for bootstrapping, for which purposes other means of analysis (e.g. maximum parsimony, maximum likelihood) may be computation ally prohibitive.

bootstrapping

maximum parsimony

maximum likelihood


Input: The 2002 submission of the DAML + OIL language to the World Wide Web Consortium (W3C) the work done by DAML contractors and the European Union / United States ad hoc Joint Committee on Markup Languages.

DAML

OIL

DAML

World Wide Web Consortium

European Union / United States ad hoc Joint Committee on Markup Languages


Input: An example of non-linear normalization is when the normalization follows a sigmoid function, in that case, the normalized image is computed according to the formula

non-linear normalization

normalization

sigmoid function


Input: It has been pointed out that precision is usually twinned with recall to overcome this problem

precision

recall


Input: The commonly used metrics are the mean squared error and root mean squared error, the latter having been used in the Netflix Prize.

mean squared error

root mean squared error

Netflix Prize


Input: In August 2016, a research programme with University College Hospital was announced with the aim of developing an algorithm that can automatically differentiate between healthy and cancerous tissues in head and neck areas.

University College Hospital


Input: The impact of Posner's theoretical and empirical contributions has been recognized through fellowship in the American Psychological Association, the Association for Psychological Science, the Society of Experimental Psychologists, the American Academy of Arts and Sciences, the American Association for the Advancement of Science, and the National Academy of Sciences.

Posner

American Psychological Association

Association for Psychological Science

Society of Experimental Psychologists

American Academy of Arts and Sciences

American Association for the Advancement of Science

National Academy of Sciences


Input: These Intelligent Chatbots make use of all kinds of artificial intelligence like image moderation and natural language understanding (NLU), natural language generation (NLG), machine learning and deep learning.

Chatbots

artificial intelligence

machine learning

deep learning

image moderation

natural language understanding

NLU

natural language generation

NLG


Input: The row ratios are Positive Predictive Value (PPV, aka precision) (TP / (TP + FP)), with complement the FALSE Discovery Rate (FDR) (FP / (TP + FP)); and Negative Predictive Value (NPV) (TN / (TN + FN)), with complement the FALSE Omission Rate (FOR) (FN / (TN + FN)).

Positive Predictive Value

PPV

precision

TP / (TP + FP)

FALSE Discovery Rate

FDR

FP / (TP + FP)

Negative Predictive Value

NPV

TN / (TN + FN)

FALSE Omission Rate

FOR

FN / (TN + FN)


Input: The information is a blend of sitemaps and RSS and is created using the Information Model (IM) and Biomedical Resource Ontology (BRO).

RSS

Information Model

IM

Biomedical Resource Ontology

BRO


Input: Recent text recognition is based on Recurrent neural network (Long short-term memory) and does not require a language model.

text recognition

Recurrent neural network

Long short-term memory

language model


Input: Popular loss functions include the hinge loss (for linear SVMs) and the log loss (for logistic regression).

loss functions

hinge loss

log loss

linear SVMs

logistic regression


Input: SSIM is designed to improve on traditional methods such as peak signal-to-noise ratio (PSNR) and mean squared error (MSE).

SSIM

peak signal-to-noise ratio

PSNR

mean squared error

MSE


Input: His work inspired subsequent generations of robotics researchers such as Rodney Brooks, Hans Moravec and Mark Tilden.

Rodney Brooks

Hans Moravec

Mark Tilden


Input: Further pulse training is not differentiable, eliminating backpropagation -based training methods like gradient descent.

backpropagation

gradient descent


Input: This relations can be easily represented with a confusion matrix, a table which describes the accuracy of a classification model.

confusion matrix

accuracy

classification


Input: At the 2018 Conference on Neural Information Processing Systems (NeurIPS) researchers from Google presented the work

2018 Conference on Neural Information Processing Systems

NeurIPS

Google


Input: During his time at Duke, he worked on an automated crossword solver PROVERB, which won an Outstanding Paper Award in 1999 from AAAI and competed in the American Crossword Puzzle Tournament.

Duke

PROVERB

Outstanding Paper Award

American Crossword Puzzle Tournament

AAAI


Input: Headquartered in Rochester Hills, Michigan, the company had 10 regional locations in the U.S., Canada, Mexico and Brazil.

Rochester Hills

Michigan

the U.S.

Canada

Mexico

Brazil


Input: It joins a collection of historically important robots that includes an early Unimate and the Odetics Odex 1.

Unimate

Odetics Odex 1


Input: A guest editor for that issue will be David's former colleague at NIST, Judah Levine who is the most recent recipient of the I. I. Rabi Award.

David

Judah Levine

NIST

I. I. Rabi Award


Input: These can be arranged into a 2 × 2 contingency table (confusion matrix), conventionally with the test result on the vertical axis and the actual condition on the horizontal axis.

confusion matrix


Input: The Apple iOS operating system used on the iPhone, iPad and iPod Touch uses VoiceOver speech synthesis accessibility.

Apple iOS operating system

iPhone

iPad

iPod Touch

VoiceOver speech synthesis


Input: For example, the best system entering MUC-7 scored 93.39% of F-measure while human annotators scored 97.6% and 96.95%.

F-measure


Input: This is done using standard neural net training algorithms such as stochastic gradient descent with backpropagation.

stochastic gradient descent

backpropagation


Input: Rotten Tomatoes is a top 1000 site, placing around #400 globally and top 150 for the US only, according to website ranker Alexa.

Rotten Tomatoes

US

Alexa


Input: Generally speaking all learning displays incremental change over time, but describes an Sigmoid function which has different appearances depending on the time scale of observation.

Sigmoid function


Input: The SSD is also known as mean squared error.

SSD

mean squared error


Input: Decision tree learning, neural networks, or a naive Bayes classifier could be used in combination with measures of model quality such as balanced accuracy

Decision tree learning

neural networks

naive Bayes classifier

balanced accuracy


Input: He is a past President (1979) and an inaugural Fellow (2011) of the ACL, a co-recipient of the 1992 Association for Computing Machinery Software Systems Award for his contribution to the Interlisp programming system, and a Fellow of the Association for Computing Machinery.

ACL

1992 Association for Computing Machinery

Association for Computing Machinery

Software Systems Award

Interlisp programming system


Input: Along with Geoffrey Hinton and Yann LeCun, Bengio is considered by Cade Metz as one of the three people most responsible for the advancement of deep learning during the 1990s and 2000s.

Geoffrey Hinton

Yann LeCun

Bengio

Cade Metz

deep learning


Input: In information theory and computer science, a code is usually considered as an algorithm that uniquely represents symbols from some source alphabet, by encoded strings, which may be in some other target alphabet.

information theory

computer science


Input: A fairly simple non-linear function, the sigmoid function such as the logistic function also has an easily calculated derivative, which can be important when calculating the weight updates in the network.

sigmoid function

logistic function


Input: Čapek was born in Hronov, Bohemia (Austria-Hungary, later Czechoslovakia, now the Czech Republic) in 1887.

Čapek

Hronov

Bohemia

Austria-Hungary

Czechoslovakia

Czech Republic


Input: Some specialized software can narrate RSS.

RSS


Input: Aspects of ontology editors include: visual navigation possibilities within the knowledge model, inference engine s and extraction; support for modules; the import and export of foreign knowledge representation languages for ontology matching; and the support of meta-ontologies such as OWL-S, Dublin Core, etc.

visual navigation

knowledge model

inference engine

extraction

support for modules

knowledge representation

ontology matching

meta-ontologies

OWL-S

Dublin Core


Input: The FBI has also instituted its Next Generation Identification program to include face recognition, as well as more traditional biometrics like fingerprints and iris scans, which can pull from both criminal and civil databases.

FBI

Next Generation Identification program

fingerprints

iris scans

face recognition

biometrics


Input: For the 2016 season, Samantha Ponder was added as host, replacing Molly McGrath.

Samantha Ponder

Molly McGrath


Input: It is an adversarial search algorithm used commonly for machine playing of two-player games (Tic-tac-toe, Chess, Go, etc.

adversarial search algorithm

Tic-tac-toe

Chess

Go


Input: It involves the fields of computer vision or machine vision, and medical imaging, and makes heavy use of pattern recognition, digital geometry, and signal processing.

computer vision

machine vision

medical imaging

pattern recognition

digital geometry

signal processing


Input: In facial recognition system, for instance, a picture of a person's face would be the input, and the output label would be that person's name.

facial recognition system


Input: Apple Inc introduced Face ID on the flagship iPhone X as a biometric authentication successor to the Touch ID, a fingerprint based system.

Apple Inc

Face ID

iPhone X

Touch ID


Input: Or combine the F-measure with the R-square evaluated for the raw model output and the target; or the cost / gain matrix with the correlation coefficient, and so on.

F-measure

R-square

cost / gain matrix

correlation coefficient


Input: The Spanish edition of Campus Party has been held at the Colegio Miguel Hernández, Ceulaj, and the Municipal Sport Arena of Benalmádena in Málaga, Spain; and at both the Valencia County Fair and the City of Arts and Sciences in Valencia over the past 15 years.

Spanish edition of Campus Party

Colegio Miguel Hernández

Ceulaj

Municipal Sport Arena of Benalmádena

Málaga

Valencia County Fair

City of Arts and Sciences

Valencia

Spain


Input: gnuplot can be used from various programming languages to graph data, including Perl (via PDL and CPAN packages), Python (via).

gnuplot

PDL

CPAN

Perl

Python


Input: The field of spoken dialog systems is quite large and includes research (featured at scientific conferences such as SIGdial and Interspeech) and a large industrial sector (with its own meetings such as SpeechTek and AVIOS).

spoken dialog systems

SIGdial

Interspeech

SpeechTek

AVIOS


Input: Challenges in natural language processing frequently involve speech recognition, natural language understanding, and natural language generation.

natural language processing

speech recognition

natural language understanding

natural language generation


Input: These systems, such as Siri of the iOS operating system, operate on a similar pattern-recognizing technique as that of text-based systems, but with the former, the user input is conducted through speech recognition.

Siri

iOS operating system

speech recognition


Input: More exotic fitness functions that explore model granularity include the area under the ROC curve and rank measure.

exotic fitness functions

ROC curve


Input: The term Semantic Web was coined by Tim Berners-Lee, the inventor of the World Wide Web and director of the World Wide Web Consortium (W3C), which oversees the development of proposed Semantic Web standards.

Semantic Web

World Wide Web

Semantic Web standards

Tim Berners-Lee

World Wide Web Consortium


Input: Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation (MAHT) or interactive translation), is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another.

Machine translation

MT

computer-aided translation

machine-aided human translation

MAHT

interactive translation

computational linguistics


Input: Early interlingual MT systems were also built at Stanford in the 1970s by Roger Schank and Yorick Wilks; the former became the basis of a commercial system for the transfer of funds, and the latter's code is preserved at The Computer Museum at Boston as the first interlingual machine translation system.

interlingual MT systems

interlingual machine translation system

Stanford

Roger Schank

Yorick Wilks

The Computer Museum

Boston


Input: Sycara served as the program chair of the Second International Semantic Web Conference (ISWC 2003); general chair, of the Second International Conference on Autonomous Agents (Agents 98); chair of the Steering Committee of the Agents Conference (1999-2001); scholarship chair of AAAI (1993-1999);

Sycara

Second International Semantic Web Conference

ISWC 2003

Second International Conference on Autonomous Agents

Agents 98

AAAI

Steering Committee of the Agents Conference


Input: In 2016, she was selected as the ACL (Association for Computational Linguistics) Lifetime Achievement Award winner.

ACL

Association for Computational Linguistics

Lifetime Achievement Award


Input: Sepp Hochreiter, Y. Bengio, P. Frasconi, and Jürgen Schmidhuber.

Sepp Hochreiter

Y. Bengio

P. Frasconi

Jürgen Schmidhuber


Input: For example, A.L.I.C.E. uses a markup language called AIML, which is specific to its function as a dialogue system, and has since been adopted by various other developers of, so-called, Alicebot s.

A.L.I.C.E.

dialogue system

Alicebot

markup language

AIML


Input: In 2000, she was elected as a Fellow of the Association for the Advancement of Artificial Intelligence.

Association for the Advancement of Artificial Intelligence


Input: Learning classifier systems (LCS) are a family of rule-based machine learning algorithms that combine a discovery component, typically a genetic algorithm, with a learning component, performing either supervised learning, reinforcement learning, or unsupervised learning.

Learning classifier systems

LCS

rule-based machine learning algorithms

genetic algorithm

supervised learning

reinforcement learning

unsupervised learning


Input: The unknown parameters in each vector βsubk / sub are typically jointly estimated by maximum a posteriori (MAP) estimation, which is an extension of maximum likelihood using regularization of the weights to prevent pathological solutions (usually a squared regularizing function, which is equivalent to placing a zero-mean Gaussian prior distribution on the weights, but other distributions are also possible).

maximum a posteriori

MAP

maximum likelihood

squared regularizing function

regularization

zero-mean Gaussian prior distribution


Input: The hierarchical structure of words has been explicitly mapped in George Miller' s Wordnet.

George Miller

Wordnet


Input: An illustration of their capabilities is given by the ImageNet Large Scale Visual Recognition Challenge; this is a benchmark in object classification and detection, with millions of images and hundreds of object classes.

ImageNet Large Scale Visual Recognition Challenge

object classification and detection


Input: In science fiction, female-appearing robots are often produced for use as domestic servants and sexual slaves, as seen in the film Westworld, Paul J. McAuley' s novel Fairyland (1995), and Lester del Rey' s short story Helen O'Loy (1938), and sometimes as warriors, killers, or laborers.

science fiction

Westworld

Fairyland

Helen O'Loy

Paul J. McAuley

Lester del Rey


Input: question answering, speech recognition, and machine translation.

question answering

speech recognition

machine translation


Input: In his seminal paper, Harry Blum of the Air Force Cambridge Research Laboratories at Hanscom Air Force Base, in Bedford, Massachusetts, defined a medial axis for computing a skeleton of a shape, using an intuitive model of fire propagation on a grass field, where the field has the form of the given shape.

Harry Blum

Air Force Cambridge Research Laboratories

Hanscom Air Force Base

Bedford

Massachusetts


Input: However, in contrast to boosting algorithms that analytically minimize a convex loss function (e.g. AdaBoost and LogitBoost), BrownBoost solves a system of two equations and two unknowns using standard numerical methods.

AdaBoost

LogitBoost

BrownBoost


Input: Getoor has multiple best paper awards, an NSF Career Award, and is an Association for the Advancement of Artificial Intelligence (AAAI) Fellow.

Getoor

NSF Career Award

Association for the Advancement of Artificial Intelligence

AAAI


Input: ACM Fellow (2015) br Association for Computational Linguistics Fellow (2011) br AAAI Fellow (1994) br International Speech Communication Association Fellow (2011) br Honorary Doctorate (Hedersdoktor) KTH Royal Institute of Technology (2007) br Columbia Engineering School Alumni Association Distinguished Faculty Teaching award (2009) br IEEE James L. Flanagan Speech and Audio Processing Award (2011) br ISCA Medal for Scientific Achievement (2011)

ACM Fellow

Association for Computational Linguistics Fellow

AAAI Fellow

International Speech Communication Association Fellow

Honorary Doctorate

Columbia Engineering School Alumni Association Distinguished Faculty Teaching award

IEEE James L. Flanagan Speech and Audio Processing Award

ISCA Medal for Scientific Achievement

KTH Royal Institute of Technology


Input: A frustrating outcome of the same study by Stanford (and other attempts to improve named recognition translation) is that many times, a decrease in the Bilingual evaluation understudy scores for translation will result from the inclusion of methods for named entity translation.

Stanford

named recognition translation

named entity translation

Bilingual evaluation understudy


Input: Medtronic is using the collected PM data and is working with researchers at Johns Hopkins Hospital and Washington University School of Medicine in order to help answer specific questions about heart disease, such as whether weak hearts cause arrhythmias or vice versa.

Medtronic

Johns Hopkins Hospital

Washington University School of Medicine


Input: Following that was Paramount's first feature, Sangaree with Fernando Lamas and Arlene Dahl.

Paramount

Sangaree

Fernando Lamas

Arlene Dahl


Input: KRL is a knowledge representation language, developed by Daniel G. Bobrow and Terry Winograd while at Xerox PARC and Stanford University, respectively.

KRL

Daniel G. Bobrow

Terry Winograd

Xerox PARC

Stanford University


Input: At the IEEE Conference on Computer Vision and Pattern Recognition in 2006, Qiang Zhu, Shai Avidan, Mei-Chen Yeh, and Kwang-Ting Cheng presented an algorithm to significantly speed up human detection using HOG descriptor methods.

IEEE Conference on Computer Vision and Pattern Recognition

Qiang Zhu

Shai Avidan

Mei-Chen Yeh

Kwang-Ting Cheng

human detection

HOG descriptor methods


Input: Hayes is a charter Fellow of AAAI and of the Cognitive Science Society

Hayes

AAAI

Cognitive Science Society


Input: Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements.

Time series

statistics

signal processing

pattern recognition

econometrics

mathematical finance

weather forecasting

earthquake prediction

electroencephalography

control engineering

astronomy

communications engineering

applied science


Input: In principle, exact recovery can be solved in its feasible range using maximum likelihood, but this amounts to solving a constrained or regularized cut problem such as minimum bisection that is typically NP-complete.

maximum likelihood

NP-complete


Input: in their work for pedestrian detection, that was first described at the BMVC in 2009.

pedestrian detection

BMVC


Input: In 2007, at the International Conference on Computer Vision, Terzopoulos was awarded the inaugural IEEE PAMI Computer Vision Distinguished Researcher Award for pioneering and sustained research on deformable models and their applications.

International Conference on Computer Vision

Terzopoulos

inaugural IEEE PAMI Computer Vision Distinguished Researcher Award


Input: Cluster analysis or cluster analysis involves assigning data points to clusters such that items in the same cluster are as similar as possible, while items belonging to different clusters are as dissimilar as possible.

Cluster analysis

cluster analysis


Input: (2005) we can differ three different perspectives of text mining, namely text mining as information extraction, text mining as text data mining, and text mining as Data mining (Knowledge Discovery in Databases) process.Hotho, A., Nürnberger, A. and Paaß, G. (2005).

text mining

text mining

text mining

data mining

text mining

Data mining

information extraction

Knowledge Discovery

Databases


Input: The Rancho Arm was developed as a robotic arm to help handicapped patients at the Rancho Los Amigos National Rehabilitation Center in Downey, California; this computer-controlled arm was bought by Stanford University in 1963.

Rancho Arm

Rancho Los Amigos National Rehabilitation Center

Downey

California

Stanford University


Input: At UCSD, Norman was a founder of the Institute for Cognitive Science and one of the organizers of the Cognitive Science Society (along with Roger Schank, Allan M. Collins, and others), which held its first meeting at the UCSD campus in 1979.

UCSD

UCSD

Norman

Roger Schank

Allan M. Collins

the Institute for Cognitive Science

Cognitive Science Society


Input: The most commonly used robot configurations are articulated robots, SCARA robots, delta robots and cartesian coordinate robots, (gantry robots or x-y-z robots).

articulated robots

SCARA robots

delta robots

cartesian coordinate robots

gantry robots

x-y-z robots


Input: Alternatively, it can be used directly with the Perl Module TM (which also supports LTM).

Perl

Module TM

LTM


Input: This was won by an United States team from Newton Labs, and the competition was shown on CNN.

United States

Newton Labs

CNN


Input: The Butler's in Love, a short film directed by David Arquette and starring Elizabeth Berkley and Thomas Jane was released on June 23, 2008.

The Butler's in Love

David Arquette

Elizabeth Berkley

Thomas Jane


Input: For instance, WordNet is a resource including a taxonomy, whose elements are meanings of English words.

WordNet

taxonomy

English


Input: Existing humanoid robot systems such as ASIMO and QRIO use many motors to achieve locomotion.

humanoid robot systems

ASIMO

QRIO

locomotion


Input: LEPOR is designed with the factors of enhanced length penalty, precision, n-gram word order penalty, and recall.

LEPOR

precision

recall

n-gram word order penalty


Input: It is based on the Bilingual evaluation understudy metric, but with some alterations.

Bilingual evaluation understudy metric


Input: This is an example implementation in MATLAB / Octave:

MATLAB

Octave


Input: It is designed to be used through a number of computer languages, include Python, Ruby, and Scheme.

Python

Ruby

Scheme


Input: Hayes has served as secretary of AISB, chairman and trustee of IJCAI, associate editor of Artificial Intelligence, a governor of the Cognitive Science Society and president of American Association for Artificial Intelligence.

Hayes

AISB

Cognitive Science Society

American Association for Artificial Intelligence

IJCAI

Artificial Intelligence


Input: Two of them, Now is the Time (to Put On Your Glasses) and Around is Around, were directed by Norman McLaren in 1951 for the National Film Board of Canada.

Now is the Time (to Put On Your Glasses)

Around is Around

Norman McLaren

National Film Board of Canada


Input: A recommender system aims to predict the preference for an item of a target user.

recommender system


Input: Convolution has applications that include probability, statistics, computer vision, natural language processing, image processing and signal processing, engineering, and differential equations.

Convolution

probability

statistics

computer vision

natural language processing

image processing

signal processing

engineering

differential equations


Input: Applications of DSP include audio signal processing, audio compression, digital image processing, video compression, speech processing, speech recognition, digital communication s, digital synthesizer s, radar, sonar, financial signal processing, seismology and biomedicine.

DSP

radar

sonar

financial signal processing

seismology

biomedicine

audio signal processing

audio compression

digital

image

processing

video compression

speech processing

speech recognition

digital communication

digital synthesizer


Input: (February 20, 1912 - August 11, 2011) was an American inventor, best known for creating Unimate, the first industrial robot.

American

Unimate


Input: With David E. Rumelhart and Ronald J. Williams, Hinton was co-author of a highly cited paper published in 1986 that popularized the backpropagation algorithm for training multi-layer neural networks, The dramatic image-recognition milestone of the AlexNet designed by his student Alex Krizhevsky {{cite web

David E. Rumelhart

Ronald J. Williams

Hinton

Alex Krizhevsky

backpropagation algorithm

multi-layer neural networks

AlexNet

image-recognition


Input: When the value being predicted is continuously distributed, the mean squared error, root mean squared error or median absolute deviation could be used to summarize the errors.

mean squared error

root mean squared error

median absolute deviation


Input: Conceptual clustering developed mainly during the 1980s, as a machine learning paradigm for unsupervised learning.

Conceptual clustering

machine learning

unsupervised learning


Input: If named entities cannot be recognized by the machine translator, they may be erroneously translated as common nouns, which would most likely not affect the Bilingual evaluation understudy rating of the translation but would change the text's human readability.

machine translator

Bilingual evaluation understudy


Input: Roger Schank, 1969, A conceptual dependency parser for natural language Proceedings of the 1969 on Computational linguistics, Sång-Säby, Sweden, pages 1-3 This model, partially influenced by the work of Sydney Lamb, was extensively used by Schank's students at Yale University, such as Robert Wilensky, Wendy Lehnert, and Janet Kolodner.

Roger Schank

Sydney Lamb

Schank

Robert Wilensky

Wendy Lehnert

Janet Kolodner

natural language

Proceedings of the 1969 on Computational linguistics

Sång-Säby

Sweden

Yale University


Input: Improved maximum likelihood method (IMLM) is a combination of two MLM (maximum likelihood) estimators.

maximum likelihood method

IMLM

MLM

maximum likelihood


Input: These methods may also analyze a program's output and its usefulness and therefore may involve the analysis of its confusion matrix (or table of confusion).

confusion matrix

table of confusion


Input: SURF was first published by Herbert Bay, Tinne Tuytelaars, and Luc Van Gool, and presented at the 2006 European Conference on Computer Vision.

SURF

Herbert Bay

Tinne Tuytelaars

Luc Van Gool

2006 European Conference on Computer Vision


Input: OCR is a field of research in pattern recognition, artificial intelligence and computer vision.

OCR

pattern recognition

artificial intelligence

computer vision


Input: Continuing the example using the maximum likelihood estimator, the probability density function (pdf) of the noise for one sample mathw n / math is

maximum likelihood estimator

probability density function

pdf


Input: Sub-domains of computer vision include scene reconstruction, event detection, video tracking, object recognition, 3D pose estimation, learning, indexing, motion estimation, visual servoing, 3D scene modeling, and image restoration.

computer vision

scene reconstruction

event detection

video tracking

object recognition

3D pose estimation

learning

indexing

motion estimation

visual servoing

3D scene modeling

image restoration


Input: In 2013, at the International Conference on Computer Vision, Terzopoulos was awarded a Helmholtz Prize for his 1987 ICCV paper with Kass and Witkin on active contour model s.

International Conference on Computer Vision

1987 ICCV

Terzopoulos

Kass

Witkin

Helmholtz Prize

active contour model


Input: If the regularization function Many algorithms exist for solving such problems; popular ones for linear classification include Stochastic gradient descent) gradient descent, L-BFGS, coordinate descent and Newton method s.

linear classification

Stochastic gradient descent

gradient descent

L-BFGS

coordinate descent

Newton method


Input: Long short-term memory (LSTM) networks were invented by Sepp Hochreiter and Jürgen Schmidhuber in 1997 and set accuracy records in multiple applications domains.

Long short-term memory

LSTM

Sepp Hochreiter

Jürgen Schmidhuber


Input: TN was developed at Massachusetts General Hospital and was tested in multiple scenarios including the extraction of smoking status, family history of coronary artery disease, identifying patients with sleep disorders,

TN

Massachusetts General Hospital


Input: In 1960, Devol personally sold the first Unimate robot, which was shipped in 1961 to General Motors.

Devol

Unimate

General Motors


Input: The Campus Party Europe was held April 14-18, 2010 at the Caja Mágica in Madrid, Spain with 800 participants from each of the 27 European Union member states.

Campus Party Europe

Caja Mágica

Madrid

Spain

European Union


Input: In July 2016, a collaboration between DeepMind and Moorfields Eye Hospital was announced to develop AI applications for healthcare.

DeepMind

Moorfields Eye Hospital

AI applications for healthcare


Input: They ended up awarding eleven PR2s to different institutions, including University of Freiburg, Bosch, Georgia Tech, KU Leuven, MIT, Stanford, Technical University of Munich, UC Berkeley, U Penn, USC, and University of Tokyo.

University of Freiburg

Bosch

Georgia Tech

KU Leuven

MIT

Stanford

Technical University of Munich

UC Berkeley

U Penn

USC

University of Tokyo


Input: The counts of TP, TN, FP, and FN are usually kept on a table known as the confusion matrix.

TP

TN

FP

FN

confusion matrix


Input: As feature set, information gain, cross entropy, mutual information, and odds ratio are usually used.

information gain

cross entropy

mutual information

odds ratio


Input: It has been applied successfully to various problems, including robot control, elevator scheduling, telecommunications,, checkers and Go (AlphaGo).

robot control

elevator scheduling

telecommunications

checkers

Go

AlphaGo


Input: In 2018, the inaugural year of mission 8, the American Venue was held on the campus of the Georgia Institute of Technology in Atlanta, Georgia, and the Asia / Pacific Venue was conducted at Beihang University Gymnasium in Beijing China.

American

Georgia Institute of Technology

Atlanta

Georgia

Asia / Pacific

Beihang University Gymnasium

Beijing

China


Input: Machine learning is strongly related to pattern recognition and originates from artificial intelligence.

Machine learning

pattern recognition

artificial intelligence


Input: It comes with 3 Java games that are controlled with the remote control and displayed to its LCD screen.

Java

LCD screen


Input: A commercially successful but specialized computer vision-based articulated body pose estimation technique is optical motion capture.

computer vision-based articulated body pose estimation

optical motion capture


Input: The SMC is very similar to the more popular Jaccard index.

SMC

Jaccard index


Input: The PUMA (Programmable Universal Machine for Assembly, or Programmable Universal Manipulation Arm) is an industrial robot robotic arm developed by Victor Scheinman at pioneering robot company Unimation.

PUMA

Programmable Universal Machine for Assembly

Programmable Universal Manipulation Arm

Victor Scheinman

Unimation


Input: It is written in Python.

Python


Input: Bandwidth in hertz is a central concept in many fields, including electronics, information theory, digital communication s, radio communication s, signal processing, and spectroscopy and is one of the determinants of the capacity of a given communication channel.

Bandwidth

hertz

electronics

information theory

digital communication

radio communication

signal processing

spectroscopy


Input: If a convex loss is utilized (as in AdaBoost, LogitBoost, and all members of the AnyBoost family of algorithms) then an example with higher margin will receive less (or equal) weight than an example with lower margin.

AdaBoost

LogitBoost

AnyBoost family of algorithms


Input: Sepp Hochreiter' s diploma thesis of 1991 Sepp Hochreiter.

Sepp Hochreiter

Sepp Hochreiter


Input: Typical discriminative models include logistic regression (LR), support vector machine s (SVM), conditional random fields (CRFs) (specified over an undirected graph), decision trees, neural networks, and many others.

logistic regression

LR

support vector machine

SVM

conditional random fields

CRFs

undirected graph

decision trees

neural networks


Input: Then it is also possible to use these probabilities and evaluate the mean squared error (or some other similar measure) between the probabilities and the actual values, then combine this with the confusion matrix to create very efficient fitness functions for logistic regression.

mean squared error

confusion matrix


Input: VoiceOver was for the first time featured in 2005 in Mac OS X Tiger (10.4).

VoiceOver

Mac OS X Tiger


Input: In practice, machine learning algorithms cope with that either by employing a convex approximation to the 0-1 loss function (like hinge loss for Support vector machine), which is easier to optimize, or by imposing assumptions on the distribution mathP (x, y) / math (and thus stop being agnostic learning algorithms to which the above result applies).

convex approximation

Support vector machine

loss function

agnostic learning algorithms

hinge loss


Input: Westworld (1973) was the first feature film to use the digital image processing to photography to simulate an android's point of view.

Westworld

digital image processing

android


Input: It is now also commonly used in speech recognition, speech synthesis, diarization, Xavier Anguera et al.

speech recognition

speech synthesis

diarization

Xavier Anguera


Input: Here, math \ sigma / math is an element-wise activation function such as a sigmoid function or a rectified linear unit.

element-wise activation function

sigmoid function

rectified linear unit


Input: Traditional phonetic-based (i.e., all Hidden Markov model -based model) approaches required separate components and training for the pronunciation, acoustic and language model.

Hidden Markov model

pronunciation

acoustic

language model


Input: The Roberts cross operator is used in image processing and computer vision for edge detection.

Roberts cross operator

image processing

computer vision

edge detection


Input: The values of sensitivity and specificity are agnostic to the percent of positive cases in the population of interest (as opposed to, for example, precision).

sensitivity

specificity

precision


Input: But perceptron models were made very unpopular by the book Perceptrons by Marvin Minsky and Seymour Papert, published in 1969.

perceptron models

Perceptrons

Marvin Minsky

Seymour Papert


Input: The Document Understanding Conferences, conducted annually by NIST, have developed sophisticated evaluation criteria for techniques accepting the multi-document summarization challenge.

Document Understanding Conferences

NIST

multi-document summarization


Input: A parallel manipulator is designed so that each chain is usually short, simple and can thus be rigid against unwanted movement, compared to a serial manipulator.

parallel manipulator

serial manipulator


Input: The manipulator is what makes the robot move, and the design of these systems can be categorized into several common types, such as SCARA and cartesian coordinate robot, which use different coordinate systems to direct the arms of the machine.

SCARA

cartesian coordinate robot


Input: In the United States he is a Member of the National Academy of Sciences, the American Academy of Arts and Sciences, the Linguistic Society of America, the American Philosophical Association, and the American Association for the Advancement of Science.

United States

National Academy of Sciences

American Academy of Arts and Sciences

Linguistic Society of America

American Philosophical Association

American Association for the Advancement of Science


Input: They rose to great prominence with the popularity of the support vector machine (SVM) in the 1990s, when the SVM was found to be competitive with neural networks on tasks such as handwriting recognition.

support vector machine

SVM

SVM

neural networks

handwriting recognition


Input: An empirical whitening transform is obtained by estimating the covariance (e.g. by maximum likelihood) and subsequently constructing a corresponding estimated whitening matrix (e.g. by Cholesky decomposition).

whitening transform

covariance

whitening matrix

maximum likelihood

Cholesky decomposition


Input: IAI is the world's largest manufacturer of cartesian coordinate robot s and is an established leader in low cost, high performance SCARA robot s.

IAI

cartesian coordinate robot

SCARA robot


Input: Formal concept analysis finds practical application in fields including data mining, text mining, machine learning, knowledge management, semantic web, software development, chemistry and biology.

data mining

text mining

machine learning

knowledge management

semantic web

software development

chemistry

biology


Input: In computer science, computational learning theory (or just learning theory) is a subfield of artificial intelligence devoted to studying the design and analysis of machine learning algorithms.

computer science

computational learning theory

learning theory

artificial intelligence

machine learning


Input: Collaborative filtering (CF) is a technique used by recommender system s.

Collaborative filtering

CF

recommender system


Input: The FALSE positive rate is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present.

FALSE positive rate


Input: In VLDB' 8: Proceedings of the 34th International Conference on Very Large Data Bases, pages 422--433. showed that the given values for mathC / math and mathK / math generally imply relatively low accuracy of iteratively computed SimRank scores.

VLDB

Proceedings of the 34th International Conference on Very Large Data Bases

accuracy

SimRank


Input: The science fiction drama Sense8 debuted in June 2015, which was written and produced by The Wachowskis and J. Michael Straczynski.

science fiction drama

The Wachowskis

J. Michael Straczynski


Input: While Eurotra never delivered a working MT system, the project made a far-reaching long-term impact on the nascent language industries in European member states, in particular among the southern countries of Greece, Italy, Spain, and Portugal.

Eurotra

European

MT system

Greece

Italy

Spain

Portugal


Input: Autoencoder has been successfully applied to the machine translation of human languages which is usually referred to as neural machine translation (NMT).

Autoencoder

machine translation

neural machine translation

NMT


Input: Popular examples of fitness functions based on the probabilities include maximum likelihood estimation and hinge loss.

maximum likelihood estimation

hinge loss


Input: Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning.

Data mining

unsupervised learning

exploratory data analysis


Input: Collaborative filtering encompasses techniques for matching people with similar interests and making recommender system on this basis.

Collaborative filtering

recommender system


Input: A number of WordNet-based word similarity algorithms are implemented in a Perl package called WordNet :: Similarity.

WordNet-based word similarity algorithms

Perl

WordNet :: Similarity


Input: Another paper, presented at the CVPR (CVPR) 2000 by Erik Miller, Nicholas Matsakis, and Paul Viola will also be discussed.

CVPR

CVPR

Erik Miller

Nicholas Matsakis

Paul Viola


Input: QC has not been evaluated against traditional modern clustering algorithms, aside from Jaccard index.

QC

clustering algorithms

Jaccard index


Input: During the VEX Robotics World Championship, a Parade of Nations is held in Freedom Hall that includes hundreds of students from more than 30 countries.

VEX Robotics World Championship

Parade of Nations

Freedom Hall


Input: Other measures of accuracy include Single Word Error Rate (SWER) and Command Success Rate (CSR).

Single Word Error Rate

SWER

Command Success Rate

CSR


Input: They presented their method and results in SIGGRAPH 2000.

SIGGRAPH 2000


Input: The KDD Conference grew from KDD (Knowledge Discovery and Data Mining) workshops at AAAI conferences, which were started by Gregory I. Piatetsky-Shapiro in 1989, 1991, and 1993, and Usama Fayyad in 1994. Machinery | ACM.

KDD Conference

KDD

Knowledge Discovery and Data Mining

AAAI conferences

Machinery | ACM

Gregory I. Piatetsky-Shapiro

Usama Fayyad


Input: He has been elected a Fellow of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers (IEEE), the International Association for Pattern Recognition (IAPR), the Association for the Advancement of Artificial Intelligence (AAAI), American Association for Advancement of Science (AAAS), and the Society for Optics and Photonics Technology (SPIE).

Association for Computing Machinery

ACM

International Association for Pattern Recognition

IAPR

Association for the Advancement of Artificial Intelligence

AAAI

American Association for Advancement of Science

AAAS

Society for Optics and Photonics Technology

SPIE

Institute of Electrical and Electronics Engineers

IEEE


Input: Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).

Machine learning

data mining

machine learning

data mining

knowledge discovery in databases


Input: Indy is written in Java and therefore runs on most modern operating system s.

Indy

Java

operating system


Input: NMF is an instance of nonnegative quadratic programming (NQP), just like the support vector machine (SVM).

NMF

nonnegative quadratic programming

NQP

support vector machine

SVM


Input: The method is based on estimating the conditional probabilities using the nonparametric maximum likelihood method which leads

conditional probabilities

nonparametric maximum likelihood


Input: The basic concepts involved in spectral estimation include autocorrelation, multi-D Fourier transform, mean square error and entropy.

autocorrelation

multi-D Fourier transform

mean square error

entropy


Input: Application areas of kernel methods are diverse and include geostatistics, kriging, inverse distance weighting, 3D reconstruction, bioinformatics, chemoinformatics, information extraction and handwriting recognition.

kernel methods

kriging

inverse distance weighting

geostatistics

bioinformatics

chemoinformatics

3D reconstruction

information extraction

handwriting recognition


Input: Robots can be autonomous or semi-autonomous and range from humanoids such as Honda' s Advanced Step in Innovative Mobility (ASIMO) and TOSY' s TOSY Ping Pong Playing Robot (TOPIO) to industrial robot s, medical operating robot s, patient assist robots, dog therapy robots, collectively programmed swarm robots, UAV drones such as General Atomics MQ-1 Predator, and even microscopic nano robots.

Honda

TOSY

Advanced Step in Innovative Mobility

ASIMO

TOSY Ping Pong Playing Robot

TOPIO

industrial robot

medical operating robot

patient assist robots

dog therapy robots

swarm robots

UAV drones

General Atomics MQ-1 Predator

microscopic nano robots


Input: Freddy and Freddy II were robots built at the University of Edinburgh School of Informatics by Pat Ambler, Robin Popplestone, Austin Tate, and Donald Mitchie, and were capable of assembling wooden blocks in a period of several hours.

Freddy

Freddy II

University of Edinburgh School of Informatics

Pat Ambler

Robin Popplestone

Austin Tate

Donald Mitchie


Input: He spent his childhood years in Paris, France, where his parents had emigrated from Lithuania in the early 1920s.

Paris

France

Lithuania


Input: Previously, Dr. Paulos held the Cooper-Siegel Associate Professor Chair in the School of Computer Science at Carnegie Mellon University where he was faculty within the Human-Computer Interaction Institute with courtesy faculty appointments in the Robotics Institute and in the Entertainment Technology Center.

Dr. Paulos

Cooper-Siegel Associate Professor Chair

School of Computer Science

Carnegie Mellon University

Human-Computer Interaction Institute

Robotics Institute

Entertainment Technology Center


Input: In 1969 Victor Scheinman at Stanford University invented the Stanford arm, an all-electric, 6-axis articulated robot designed to permit an arm solution.

Victor Scheinman

Stanford University

Stanford arm

6-axis articulated robot

arm solution


Input: The creation and implementation of chatbots is still a developing area, heavily related to artificial intelligence and machine learning, so the provided solutions, while possessing obvious advantages, have some important limitations in terms of functionalities and use cases.

chatbots

artificial intelligence

machine learning


Input: In terms of freely available resources, Carnegie Mellon University' s Sphinx toolkit is one place to start to both learn about speech recognition and to start experimenting.

Carnegie Mellon University

Sphinx toolkit

speech recognition


Input: The formal RoboCup competition was preceded by the (often unacknowledged) first International Micro Robot World Cup Soccer Tournament (MIROSOT) held by KAIST in Taejon, Korea, in November 1996.

RoboCup competition

International Micro Robot World Cup Soccer Tournament

MIROSOT

KAIST

Taejon

Korea


Input: In addition to the standard hinge loss math (1-yf (x)) _ + / math for labeled data, a loss function math (-1 | f (x) |) _ + / math is introduced over the unlabeled data by letting mathy = \ operatorname {sign} {f (x)} / math.

hinge loss

loss function


Input: In particular, RLS is designed to minimize the mean squared error between the predicted values and the TRUE labels, subject to regularization.

RLS

mean squared error


Input: Essentially, this combines maximum likelihood estimation with a regularization procedure that favors simpler models over more complex models.

maximum likelihood estimation

regularization procedure


Input: The true-positive rate is also known as sensitivity, recall or probability of detection math to the discrimination threshold) of the detection probability in the y-axis versus the cumulative distribution function of the false-alarm probability on the x-axis.

true-positive rate

sensitivity

recall

probability of detection

false-alarm probability

discrimination threshold

cumulative distribution function


Input: In English, WordNet is an example of a semantic network.

English

WordNet


Input: Prolonged use of speech recognition software in conjunction with word processor s has shown benefits to short-term-memory restrengthening in brain AVM patients who have been treated with resection.

speech recognition software

word processor

brain AVM


Input: Its founding editor-in-chiefs were Ron Sun, Vasant Honavar, and Gregg Oden (from 1999 to 2014).

Ron Sun

Vasant Honavar

Gregg Oden


Input: Their' parallel' distinction, as opposed to a serial manipulator, is that the end effector (or' hand') of this linkage (or' arm') is directly connected to its base by a number of (usually three or six) separate and independent linkages working simultaneously.

serial manipulator

end effector


Input: His thesis advisor was Professor Cordell Green, and his thesis / oral committee included Professors Edward Feigenbaum Joshua Lederberg, Paul Cohen, Allen Newell, Herbert Simon,.

Cordell Green

Edward Feigenbaum

Joshua Lederberg

Paul Cohen

Allen Newell

Herbert Simon


Input: Such functions include the mean squared error, root mean squared error, mean absolute error, relative squared error, root relative squared error, relative absolute error, and others.

mean squared error

root mean squared error

mean absolute error

relative squared error

root relative squared error

relative absolute error


Input: There are bindings in Python, Java and MATLAB / OCTAVE.

Python

Java

OCTAVE

MATLAB


Input: An implementation in MATLAB can be found on the.

MATLAB


Input: John McCarthy is one of the founding fathers of artificial intelligence, together with Alan Turing, Marvin Minsky, Allen Newell, and Herbert A. Simon.

John McCarthy

Alan Turing

Marvin Minsky

Allen Newell

Herbert A. Simon

artificial intelligence


Input: A parallel manipulator is a mechanical system that uses several serial manipulator s to support a single platform, or end-effector.

serial manipulator

end-effector


Input: GATE includes an information extraction system called ANNIE (A Nearly-New Information Extraction System) which is a set of modules comprising a tokenizer, a gazetteer, a sentence splitter, a Part-of-speech tagging, a Named entity recognition transducer and a coreference tagger.

GATE

ANNIE

A Nearly-New Information Extraction System

Named entity recognition transducer

coreference tagger

information extraction

Part-of-speech tagging

tokenizer

gazetteer

sentence splitter


Input: He graduated from Moscow State University and in November 1978, he left for the United States thanks to the personal intervention of Senator Edward M. Kennedy ..

Moscow State University

United States

Senator Edward M. Kennedy


Input: In 2017, the DeepMind AlphaGo team received the inaugural IJCAI Marvin Minsky medal for Outstanding Achievements in AI.

DeepMind AlphaGo team

inaugural IJCAI Marvin Minsky medal

AI


Input: Other ways anomalous propagation is recorded is by troposcatter s causing irregularities in the troposphere, scattering due to meteor s, refraction in the ionized regions and layers of the ionosphere, and reflection from the ionosphere.

anomalous propagation

troposcatter

troposphere

ionized regions

ionosphere

ionosphere


Input: Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.

Natural language processing

NLP

linguistics

computer science

information engineering

artificial intelligence


Input: Other active youth-led climate groups include Extinction Rebellion, the Sunrise Movement, SustainUS, the, among others working at both the transnational and local levels.

Extinction Rebellion

Sunrise Movement

SustainUS