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Maria Liakata
Associate Professor at University of Warwick
attention, bipolar disorder, cancer, cognition, community, condition monitoring, disability, disease, evaluation, health, language, language processing in the brain, mental health, mood (psychology), natural language processing, personal computer, prediction, social media, time perception, transformer (machine learning model), user-generated content, variance, word embedding
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
Jiawei Han
Professor at University of Illinois at Urbana-Champaign
acm 2020, artificial intelligence, automatic summarization, categorical distribution, cluster analysis, computer programming, computer science 2020, computer science event 2020, computer vision, convolutional neural network, cosine similarity, data analysis, data model, data science, deep learning, feature selection, hyperparameter (machine learning), hyperparameter optimization, information extraction, kdd2020, kdd2020 tutorials, latent dirichlet allocation, machine learning, monte carlo method, natural language processing, spanning tree, supervised learning, topic model, transformer (machine learning model), variational bayesian methods, word embedding, wordnet
Yu Huang
PhD Student at University of Illinois Urbana-Champaign
acm 2020, artificial intelligence, automatic summarization, categorical distribution, cluster analysis, computer programming, computer science 2020, computer science event 2020, computer vision, convolutional neural network, cosine similarity, data analysis, data model, data science, deep learning, feature selection, hyperparameter (machine learning), hyperparameter optimization, information extraction, kdd2020, kdd2020 tutorials, latent dirichlet allocation, machine learning, monte carlo method, natural language processing, spanning tree, supervised learning, topic model, transformer (machine learning model), variational bayesian methods, word embedding, wordnet
Yu Meng
Research Assistant at University of Illinois at Urbana-Champaign
acm 2020, artificial intelligence, automatic summarization, categorical distribution, cluster analysis, computer programming, computer science 2020, computer science event 2020, computer vision, convolutional neural network, cosine similarity, data analysis, data model, data science, deep learning, feature selection, hyperparameter (machine learning), hyperparameter optimization, information extraction, kdd2020, kdd2020 tutorials, latent dirichlet allocation, machine learning, monte carlo method, natural language processing, spanning tree, supervised learning, topic model, transformer (machine learning model), variational bayesian methods, word embedding, wordnet
Artem Ryasik
Advanced Analytics Engineer at Redfield AB
autocomplete, bert, cloud computing, computer vision, confusion matrix, data compression, datascience, deep learning, english language, gender, german language, grammatical case, grammatical gender, graphics processing unit, knime, knime analytics platform, language, machine code, machinelearning, neural network, noun, opensource, pronoun, random forest, statistical classification, statistics, tensorflow, text classification, transfer learning, transformer (machine learning model), translation, word
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