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Show (62)

Josh Wills

Developer Without Affiliation

apache hadoop, autocomplete, backup, cache (computing), categorization, central processing unit, compartmental models in epidemiology, computer data storage, computer programming, database, deep learning, education, elasticsearch, electronic health record, email, epidemiology, ethics, feedback, github, gradient descent, hard coding, hyperparameter (machine learning), influenza, influenza pandemic, information retrieval, instruction pipelining, learning to rank, logistic regression, lyft, machine learning, mapreduce, markov chain, markov chain monte carlo, mean, median, metropolis–hastings algorithm, mind, negative-feedback amplifier, neural network, nosql, open source, organization, parallel computing, parameter, prediction, programming language, public health, python (programming language), random forest, random-access memory, reddit, replication (computing), retail, search engine indexing, search engine results page, severe acute respiratory syndrome coronavirus 2, slack (software), software , software bug, software development, source code, spanish flu, statistical hypothesis testing, structure, textbook, time, twitter, uncertainty, understanding, user-generated content, version control, web application, wikipedia, world wide web

Aaron Zweig

Student at New York University

algorithm, bijection, complexity, expert, future, information, isomorphism, john brunner (novelist), linear independence, map, markov chain, measure (mathematics), metric (mathematics), motivation, observation, pixel, polynomial, singular value decomposition, space, state space, total variation, upper and lower bounds

Tom Zahavy

Research Scientist at DeepMind

algorithm, batiste, bias of an estimator, bomb, complexity, conversation, cooking banana, coupling from the past, data, decision tree, decision-making, design, energy, estimator, euro, eye, eye (cyclone), feature selection, function (mathematics), gradient, immokalee, florida, language interpretation, manuscript, markov chain, matrix (mathematics), money, mortality rate, mysticism, number, paper, patient, plumbing, rainforest, rice, shampoo, simulation, space, stationary state, symbol, temperature, time complexity, tree

Lalit Jain

Assistant Professor at University of Washington

algorithm, bias, centrality, complexity, diagonal matrix, diffusion, experiment, function (mathematics), graph (discrete mathematics), information, logistic regression, markov chain, matrix (mathematics), maximum likelihood estimation, observation, pairwise comparison, regression analysis, regularization (mathematics), similarity measure, space, statistical classification, strongly connected component, trade-off, variance, weight

Eric Hansen

Student at Mississippi State University

algorithm, belief, benders decomposition, constraint (mathematics), convex function, convex hull, convex set, dual linear program, euclidean vector, heuristic, knowledge, linear programming, markov chain, mathematical optimization, number, observation, pain, probability, probability distribution, rhythm, sequence, subroutine, two-dimensional space, vector space

Hermanni Hälvä

Student at University of Helsinki

air conditioning, correlation and dependence, equation, exponential family, feature learning, function (mathematics), goal, hidden markov model, independent component analysis, interval (mathematics), latent variable, learning, lighting, likelihood function, markov chain, markov model, mean, nonlinear system, parameter, simulation, solution, stationary process, time series, truth, unsupervised learning

Ioan Gabriel Bucur

Machine Learning Engineer at Radboud University

aldh2, bayesian inference, cardiovascular disease, causal graph, causality, complexity, compound probability distribution, computational complexity theory, confounding, correlation and dependence, function (biology), function (mathematics), genome-wide association study, instrumental variables estimation, laplace's method, likelihood function, marginal likelihood, markov chain, markov chain monte carlo, mathematical optimization, mixture, normal distribution, parameter, risk, shrinkage (statistics)

Liang Zhang

Global Sales Strategy & Operations at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, apache spark, api, application software, applications at linkedin, array data structure, array data type, art, artificial intelligence tutorial, artificial neural network, assembly language, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), color, common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data conversion, data science tutorial, data type, debugging, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , file system, film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, library (computing), likelihood function, linear combination, linearity, linkedin, literature, loader (computing), logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parameter (computer programming), parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, preprocessor, protein–protein interaction, python (programming language), radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , source lines of code, space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, string (computer science), subroutine, summation, supervised learning, support-vector machine, temporal topic localization, tensor, texas, three-dimensional space, training, validation, and test sets, transcription (linguistics), transformer (machine learning model), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Di Wen

Staff Software Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Yijie Dylan Wang

Software Engineering Manager at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, closed captioning, code-division multiple access, codec, coherence (physics), compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, film frame, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, likelihood function, linearity, linkedin, literature, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimodality, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, sms, social networking service, softmax function, space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video search, video search engine, video understanding, weight, youtube

Bharat Jain

Data Scientist at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Nikita Gupta

Senior Applied Research Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Suhit Sinha

Senior Applied Research Engineer at LinkedIn

Sumit Srivastava

Staff Applied Research Engineer at LinkedIn

Sirjan Kafle

Senior Machine Learning Engineer, Multimedia AI at LinkedIn

Aman Gupta

Senior Machine Learning Scientist at LinkedIn Multimedia AI

Ananth Sankar

Principal Staff Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, ai, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), automatic summarization, average, baby talk, backpropagation, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, black box, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, cross entropy, data, data compression, data science, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, encoding (memory), energy, engine, english language, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , feedforward neural network, film frame, finite set, four-dimensional space, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mind, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, natural language processing, nature, navigation, neural network, neural networks, news, non-local networks and slowfast, nothing, number, object detection, odsc, odsc india, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, semantics, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, vanishing gradient problem, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, vocabulary, weight, youtube

Nitesh Chawla

Founding Director of Lucy Family Institute for Data and Society and Frank M Freeman Professor of Computer Science and Engineering at University of Notre Dame

accuracy and precision, acm 2020, android (operating system), artificial intelligence, artificial neural network, association for computing machinery, computer science 2020, computer science event 2020, computer security, computer vision, convolutional neural network, correlation and dependence, data science, database, deep learning, fake news, internet, kdd2020, machine learning, malware, markov chain, matrix (mathematics), mobile app, multimodality, recommender system, semi-supervised learning, sentiment analysis, social media, social network, twitter, unsupervised learning, world wide web

Yanfang (Fanny) Ye

Associate Professor at Case Western Reserve University

accuracy and precision, acm 2020, android (operating system), artificial intelligence, artificial neural network, association for computing machinery, computer science 2020, computer science event 2020, computer security, computer vision, convolutional neural network, correlation and dependence, data science, database, deep learning, fake news, internet, kdd2020, machine learning, malware, markov chain, matrix (mathematics), mobile app, multimodality, recommender system, semi-supervised learning, sentiment analysis, social media, social network, twitter, unsupervised learning, world wide web

Xiangliang Zhang

Associate Professor at King Abdullah University of Science and Technology, Saudi Arabia

accuracy and precision, acm 2020, android (operating system), artificial intelligence, artificial neural network, association for computing machinery, computer science 2020, computer science event 2020, computer security, computer vision, convolutional neural network, correlation and dependence, data science, database, deep learning, fake news, internet, kdd2020, machine learning, malware, markov chain, matrix (mathematics), mobile app, multimodality, recommender system, semi-supervised learning, sentiment analysis, social media, social network, twitter, unsupervised learning, world wide web

Chuxu Zhang

Assistant Professor at Brandeis University

Meng Jiang

Assistant Professor at University of Notre Dame

computer science event 2020, data science, accuracy and precision, acm 2020, amazon (company), android (operating system), annotation, antibiotic, artificial intelligence, artificial neural network, association for computing machinery, attention, automation, bacteria, big data, biologist, cancer, case study, censorship, central processing unit, clinical trial, cluster analysis, computer, computer science, computer science 2020, computer science event 2020, computer security, computer vision, convolutional neural network, coronavirus, coronavirus disease 2019, correlation and dependence, covid-19, data, data mining, data model, data science, database, deep learning, deep learning 2020, design, digital library, dilution (neural networks), disease, dvd, engineer, engineering, english language, evidence, expert, fake news, feature selection, gif, goal, graphics processing unit, homogeneity and heterogeneity, humour, hypothesis, idea, image segmentation, infection, inference, information, information retrieval, insight, international monetary fund, internet, kdd2020, kdd2020 tutorials, knowledge, knowledge base, knowledge extraction, knowledge graph, language, language model, learning, library, long short-term memory, machine learning, machine translation, malaria, malware, markov chain, matrix (mathematics), medicine, memory, metadata, mind, mining, mobile app, models of scientific inquiry, multimodality, music, named-entity recognition, natural language processing, network motif, news, observation, pdf, philosophy, prediction, protein, pubmed, question, question answering, reason, recommender system, research, reserved word, science, self, semi-supervised learning, sentiment analysis, severe acute respiratory syndrome coronavirus 2, shortest path problem, social media, social network, space, standard deviation, statistical classification, system, tax, taxonomy (biology), taxonomy (general), technology, temperature, temporary work, text messaging, tf–idf, translation, twitter, united express, united parcel service, unstructured data, unsupervised learning, virus, visualization (graphics), weak supervision, world wide web

Finale Doshi-Velez

Gordon McKay Professor in Computer Science at Harvard University

africa, antimicrobial resistance, burden of proof (law), central processing unit, confounding, data, decision-making, dna sequencing, energy, estimator, europe, evaluation, evidence, evolution, expert, future, genomics, health care, hiv, hospital, information, intelligence, knowledge, management of hiv/aids, markov chain, model selection, mutation, paracetamol, patient, pessimism, pizza, promise, reason, sequencing, temperature, tsunami, united states, youtube

Mijung Kim

Medical Data Analysis at Samsung Medical Center

algorithm, attention, data, data set, disease, health care, heterogeneous condition, hidden markov model, homogeneity and heterogeneity, input–output model, markov chain, markov model, medication, movement disorders, number, observation, parkinson's disease, patient, prediction, rating scale, signs and symptoms, society, tool, trajectory, wheel

Homin Park

Doctoral student at Ghent University

algorithm, attention, data, data set, disease, health care, heterogeneous condition, hidden markov model, homogeneity and heterogeneity, input–output model, markov chain, markov model, medication, movement disorders, number, observation, parkinson's disease, patient, prediction, rating scale, signs and symptoms, society, tool, trajectory, wheel

Emma Brunskill

Assistant professor of computer science at Stanford University

burden of proof (law), central processing unit, confounding, data, decision-making, energy, estimator, evaluation, evidence, expert, future, health care, hospital, intelligence, knowledge, markov chain, model selection, paracetamol, patient, pessimism, promise, reason, temperature, youtube

Sreeramana Mavilla

Product Owner at Intel

algorithm, ambiguity, analytics, cloud computing, computer, customer experience, data, deep learning, intelligence, machine learning, markov chain, memory, monte carlo method, multi-agent system, natural language processing, nlp, prediction, propaganda, reinforcement learning, research, software , speech, supervised learning, use case, web template system, website, world wide web

Arpita Sur

Assistant Vice President at Ugam

captain america, categorization, cluster analysis, computer vision, convolutional neural network, database, gpt-2, machine learning, markov chain, online shopping, optical character recognition, portable network graphics, products , reason, retail, search engine, search engine optimization, sense, statistical classification, statistical inference, statistical model, statistics, tag (metadata), team, unsupervised learning, user interface

Vinay Mony

Principal Decision Scientist at Ugam

captain america, categorization, cluster analysis, computer vision, convolutional neural network, database, gpt-2, machine learning, markov chain, online shopping, optical character recognition, portable network graphics, products , reason, retail, search engine, search engine optimization, sense, statistical classification, statistical inference, statistical model, statistics, tag (metadata), team, unsupervised learning, user interface

Garth Baughman

Economist Payment Systems Studies section at Federal Reserve Board

altcoin, arbitrage, bitcoin, bitcoin 101, bitcoincash, bitcoinmining, bitcoinnews, bitcoinprice, bitcoins, bitcointrading, blockchain, blockchain conference, blockchain education, blockchaintechnology, btc, business, cesc, credit, crypto, cryptocurrencies, cryptocurrency, cryptoeconomics, cryptonews, cryptotrading, digital currency, discounts and allowances, economic bubble, education, eth, ethereum, euro, financial transaction, foreign exchange market, hong kong dollar, inflation, invest, investing, investment, investor, litecoin, mark carney, market (economics), market liquidity, markov chain, monetary policy, money, money laundering, payment system, renminbi, san francisco blockchain week, sf blockchain week, sfbw19, sfbw2020, speculation, terrorism financing, trader, trading, united states dollar, utility, value (economics)