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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

Sener Ozonder

Associate Professor at Istinye University

artificial intelligence 2020, data science 2020, acm 2020, artificial intelligence 2020, artificial neural network, association for computing machinery, atom, atomic nucleus, autoencoder, boltzmann distribution, boolean satisfiability problem, cluster analysis, complexity class, computational complexity theory, computer science, conceptual model, copernican heliocentrism, data science, decision problem, deep learning, electrical resistivity and conductivity, electron, entropy, expert, geocentric model, hall effect, heat, heliocentrism, history of physics, hydrogen atom, kalman filter, kdd2020 tutorials, kepler's laws of planetary motion, light, machine learning, mechanics, neural network, newton's law of universal gravitation, nondeterministic turing machine, orbit, p (complexity), physics, quantum entanglement, quantum field theory, quantum hall effect, quantum mechanics, quantum state, regularization (mathematics), second law of thermodynamics, statistical mechanics, supervised learning, time complexity, unsupervised learning, wave, wave function

Hongning Wang

Professor in the Department of Computer Science at University of Virginia

artificial intelligence 2020, computer science 2020, acceleration, algorithm, anonymity, artificial intelligence 2020, association for computing machinery, average, bias, boston, calculus, calendar, change detection, coffeemaker, collaborative filtering, collaborative learning, communication, computer science, computer science 2020, computer science conference, computer science event 2020, computer vision, confidence interval, constrained optimization, contract, covid-19 pandemic, data science 2020, decision-making, deep learning, deep learning 2020, design, differential privacy, emoji, ethics, evaluation, exfoliation (cosmetology), expected value, facebook, factorization, function (mathematics), ground truth, health, health care, horse, hyperparameter (machine learning), information, infrastructure, intelligence, interval (mathematics), intuition, ipod, kdd 2020, kdd2020 tutorials, knowledge, learning, learning by exploration, leverage (statistics), likelihood-ratio test, local differential privacy, lock (water navigation), love, machine, machine learning, machine learning 2020, mathematical optimization, matter, meritocracy, money, motivation, multi-armed bandit, music, narrative, neon, online and offline, paradigm, parameter, paris, password, perturbation theory, pleasure, prediction, printer (computing), privacy, privacy engineering, probability, property, real-time computing, reason, recommender system, recursion, regression analysis, regularization (mathematics), reputation, research, risk, security hacker, sequential analysis, server (computing), simulation, social network, solution, space, square root, stationary process, statistics, swamp, system, technology, theory, tikhonov regularization, truth, utility, weight, weighted arithmetic mean, word problem for groups

Huazheng Wang

CS PhD Student at University of Virginia

artificial intelligence 2020, computer science 2020, acceleration, algorithm, anonymity, artificial intelligence 2020, association for computing machinery, average, bias, boston, calculus, calendar, change detection, coffeemaker, collaborative filtering, collaborative learning, communication, computer science, computer science 2020, computer science conference, computer science event 2020, computer vision, confidence interval, constrained optimization, contract, covid-19 pandemic, data science 2020, decision-making, deep learning, deep learning 2020, design, differential privacy, emoji, ethics, evaluation, exfoliation (cosmetology), expected value, facebook, factorization, function (mathematics), ground truth, health, health care, horse, hyperparameter (machine learning), information, infrastructure, intelligence, interval (mathematics), intuition, ipod, kdd 2020, kdd2020 tutorials, knowledge, learning, learning by exploration, leverage (statistics), likelihood-ratio test, local differential privacy, lock (water navigation), love, machine, machine learning, machine learning 2020, mathematical optimization, matter, meritocracy, money, motivation, multi-armed bandit, music, narrative, neon, online and offline, paradigm, parameter, paris, password, perturbation theory, pleasure, prediction, printer (computing), privacy, privacy engineering, probability, property, real-time computing, reason, recommender system, recursion, regression analysis, regularization (mathematics), reputation, research, risk, security hacker, sequential analysis, server (computing), simulation, social network, solution, space, square root, stationary process, statistics, swamp, system, technology, theory, tikhonov regularization, truth, utility, weight, weighted arithmetic mean, word problem for groups

Qingyun Wu

Postdoc researcher at Microsoft Research NYC

artificial intelligence 2020, computer science 2020, acceleration, algorithm, anonymity, artificial intelligence 2020, association for computing machinery, average, bias, boston, calculus, calendar, change detection, coffeemaker, collaborative filtering, collaborative learning, communication, computer science, computer science 2020, computer science conference, computer science event 2020, computer vision, confidence interval, constrained optimization, contract, covid-19 pandemic, data science 2020, decision-making, deep learning, deep learning 2020, design, differential privacy, emoji, ethics, evaluation, exfoliation (cosmetology), expected value, facebook, factorization, function (mathematics), ground truth, health, health care, horse, hyperparameter (machine learning), information, infrastructure, intelligence, interval (mathematics), intuition, ipod, kdd 2020, kdd2020 tutorials, knowledge, learning, learning by exploration, leverage (statistics), likelihood-ratio test, local differential privacy, lock (water navigation), love, machine, machine learning, machine learning 2020, mathematical optimization, matter, meritocracy, money, motivation, multi-armed bandit, music, narrative, neon, online and offline, paradigm, parameter, paris, password, perturbation theory, pleasure, prediction, printer (computing), privacy, privacy engineering, probability, property, real-time computing, reason, recommender system, recursion, regression analysis, regularization (mathematics), reputation, research, risk, security hacker, sequential analysis, server (computing), simulation, social network, solution, space, square root, stationary process, statistics, swamp, system, technology, theory, tikhonov regularization, truth, utility, weight, weighted arithmetic mean, word problem for groups

Muhammad Aurangzeb Ahmad

Principal Research Scientist at KenSci

artificial intelligence 2020, data science 2020, acm 2020, artificial intelligence 2020, artificial neural network, assessment of kidney function, association for computing machinery, atom, atomic nucleus, autoencoder, bias, boltzmann distribution, boolean satisfiability problem, chronic condition, clinical psychology, cluster analysis, comorbidity, complexity class, computational complexity theory, computer science, computer science event 2020, conceptual model, copernican heliocentrism, data science, decision problem, deep learning, disparate impact, electrical resistivity and conductivity, electron, electronic health record, emergency department, entropy, entropy (information theory), expert, fairness (machine learning), generalized entropy index, geocentric model, hall effect, health economics, heat, heliocentrism, history of physics, hospital readmission, hydrogen atom, income inequality metrics, information theory, intensive care unit, k-nearest neighbors algorithm, kalman filter, kdd2020 tutorials, kepler's laws of planetary motion, light, machine learning, mechanics, mental health, neural network, newton's law of universal gravitation, nondeterministic turing machine, orbit, p (complexity), physics, psychological evaluation, quantum entanglement, quantum field theory, quantum hall effect, quantum mechanics, quantum state, regularization (mathematics), sampling (statistics), second law of thermodynamics, sensitivity and specificity, statistical classification, statistical mechanics, statistics, supervised learning, therapy, time complexity, unsupervised learning, wave, wave function

Estevam Hruschka

Interim Head of Research at Megagon Labs

association for computing machinery, computer scienc, computer vision, kdd2020 tutorials

Chenhui Hu

Data Scientist at Microsoft

machine learning, acm 2020, artificial intelligence, artificial neural network, autoregressive integrated moving average, autoregressive model, computer hardware, computer science 2020, computer science event 2020, computer vision, convolutional neural network, correlation and dependence, cross-validation (statistics), data science, data transformation, deep learning, errors and residuals, inventory, kdd2020, kdd2020 tutorials, long short-term memory, machine learning, memory, moving-average model, neural network, prediction, predictive modelling, real-time computing, recurrent neural network, seasonality, time series, training, validation, and test sets, variance

Vanja Paunic

Data Science at Microsoft

machine learning, acm 2020, artificial intelligence, artificial neural network, autoregressive integrated moving average, autoregressive model, computer hardware, computer science 2020, computer science event 2020, computer vision, convolutional neural network, correlation and dependence, cross-validation (statistics), data science, data transformation, deep learning, errors and residuals, inventory, kdd2020, kdd2020 tutorials, long short-term memory, machine learning, memory, moving-average model, neural network, prediction, predictive modelling, real-time computing, recurrent neural network, seasonality, time series, training, validation, and test sets, variance

Kush Varshney

Distinguished Research Staff Member and Manager at IBM Thomas J. Watson Research Center

acm 2020, artificial intelligence, artificial intelligence in healthcare, computer science 2020, computer science event 2020, computer vision, conceptual model, convolutional neural network, correlation and dependence, data science, deep learning, electronic health record, evidence-based medicine, expert, explainable artificial intelligence, health informatics, hidden markov model, international classification of diseases, kdd2020, kdd2020 tutorials, machine learning, medical diagnosis, medical ethics, medical history, neural network, pharmacovigilance, physician burnout, regression analysis, regularization (mathematics), reliability engineering, sensitivity analysis, user-centered design, visualization (graphics)

Daby Sow

Director, Hybrid Cloud Services at IBM Research

acm 2020, artificial intelligence, artificial intelligence in healthcare, computer science 2020, computer science event 2020, computer vision, conceptual model, convolutional neural network, correlation and dependence, data science, deep learning, electronic health record, evidence-based medicine, expert, explainable artificial intelligence, health informatics, hidden markov model, international classification of diseases, kdd2020, kdd2020 tutorials, machine learning, medical diagnosis, medical ethics, medical history, neural network, pharmacovigilance, physician burnout, regression analysis, regularization (mathematics), reliability engineering, sensitivity analysis, user-centered design, visualization (graphics)

Kenney Ng

Principal Research Staff Member at IBM Research at IBM

acm 2020, artificial intelligence, artificial intelligence in healthcare, computer science 2020, computer science event 2020, computer vision, conceptual model, convolutional neural network, correlation and dependence, data science, deep learning, electronic health record, evidence-based medicine, expert, explainable artificial intelligence, health informatics, hidden markov model, international classification of diseases, kdd2020, kdd2020 tutorials, machine learning, medical diagnosis, medical ethics, medical history, neural network, pharmacovigilance, physician burnout, regression analysis, regularization (mathematics), reliability engineering, sensitivity analysis, user-centered design, visualization (graphics)

Daniel Gruen

Founder and Principal Consultant at Gruen Design Research LLC

Amit Dhurandhar

Principal Research Staff Member at IBM TJ Watson

Sanjoy Dey

Research Staff Membe at IBM

Bum Chul Kwon

Research Scientist of Data Visualization at IBM T.J. Watson Research

Prithwish Chakraboty

Research Staff Member, IBM Research at IBM

Bo Long

Vice President of Engineering at JD.COM

acm 2020, anomaly detection, artificial intelligence, artificial neural network, autoencoder, computer science 2020, computer science event 2020, computer vision, data compression, data science, deep learning, generative model, image segmentation, kdd2020, kdd2020 tutorials, kullback–leibler divergence, lane departure warning system, likelihood function, machine learning, one-class classification, overfitting, prior probability, real-time computing, self-driving car, semi-supervised learning, singular value decomposition, standard score, statistical inference, statistics, traffic, unsupervised learning, variational bayesian methods, vehicular automation

Yang Yang

Software Engineer at Pinterest

acm 2020, anomaly detection, artificial intelligence, artificial neural network, autoencoder, computer science 2020, computer science event 2020, computer vision, data compression, data science, deep learning, generative model, image segmentation, kdd2020, kdd2020 tutorials, kullback–leibler divergence, lane departure warning system, likelihood function, machine learning, one-class classification, overfitting, prior probability, real-time computing, self-driving car, semi-supervised learning, singular value decomposition, standard score, statistical inference, statistics, traffic, unsupervised learning, variational bayesian methods, vehicular automation

Tie Wang

Engineering Manager- Relevance Engineering at LinkedIn

acm 2020, anomaly detection, artificial intelligence, artificial neural network, autoencoder, computer science 2020, computer science event 2020, computer vision, data compression, data science, deep learning, generative model, image segmentation, kdd2020, kdd2020 tutorials, kullback–leibler divergence, lane departure warning system, likelihood function, machine learning, one-class classification, overfitting, prior probability, real-time computing, self-driving car, semi-supervised learning, singular value decomposition, standard score, statistical inference, statistics, traffic, unsupervised learning, variational bayesian methods, vehicular automation

Xinwei Gong

Staff Software Engineer at LinkedIn

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