The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Social media, Artificial neural network and Mathematical optimization. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Pattern recognition, Generalized linear model, Information retrieval and Natural language processing. The various areas that Lyle H. Ungar examines in his Machine learning study include Task and Natural language.
His Social media study combines topics in areas such as Cognitive psychology, Well-being, Psychiatry, Disengagement theory and Mental illness. His research integrates issues of Network model, Extrapolation and Nonlinear system in his study of Artificial neural network. His Mathematical optimization research integrates issues from Bidding, Combinatorial auction, Estimation theory and Auction algorithm.
Lyle H. Ungar focuses on Artificial intelligence, Social media, Machine learning, Natural language processing and Data mining. His Artificial intelligence research incorporates elements of Task and Pattern recognition. His Social media study incorporates themes from Public health, Cognitive psychology and Social psychology, Personality.
Big Five personality traits is the focus of his Personality research. Lyle H. Ungar works in the field of Natural language processing, focusing on Sentence in particular.
His scientific interests lie mostly in Social media, Artificial intelligence, Natural language processing, Task and Social psychology. His work carried out in the field of Social media brings together such families of science as Health care, Anxiety, Public health, Personality and Mental health. He usually deals with Artificial intelligence and limits it to topics linked to Machine learning and Quality and Regression.
His Natural language processing research incorporates themes from Context based, Word and Adverse drug reaction. Lyle H. Ungar has included themes like Range, Cognitive psychology and Cluster analysis in his Task study. When carried out as part of a general Social psychology research project, his work on Big Five personality traits and Set is frequently linked to work in Trait, therefore connecting diverse disciplines of study.
His primary areas of study are Social media, Artificial intelligence, Mental health, Social psychology and Natural language processing. His Social media research includes elements of Language model, Big Five personality traits, Personality, Data science and Depression. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, Arabic, Core and State.
His Machine learning research includes themes of Task and Regression. His work is dedicated to discovering how Social psychology, Stress are connected with Adaptation and Control and other disciplines. While the research belongs to areas of Natural language processing, Lyle H. Ungar spends his time largely on the problem of Word, intersecting his research to questions surrounding Task and Debiasing.
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System and method for scheduling broadcast of and access to video programs and other data using customer profiles
Frederick Herz;Lyle Ungar;Jian Zhang;David Wachob.
Methods and metrics for cold-start recommendations
Andrew I. Schein;Alexandrin Popescul;Lyle H. Ungar;David M. Pennock.
international acm sigir conference on research and development in information retrieval (2002)
Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach
H. Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern;Lukasz Dziurzynski.
PLOS ONE (2013)
Efficient clustering of high-dimensional data sets with application to reference matching
Andrew McCallum;Kamal Nigam;Lyle H. Ungar.
knowledge discovery and data mining (2000)
Clustering Methods for Collaborative Filtering
Lyle H. Ungar;Dean P. Foster.
national conference on artificial intelligence (1998)
A hybrid neural network‐first principles approach to process modeling
Dimitris C. Psichogios;Lyle H. Ungar.
Aiche Journal (1992)
Automatic personality assessment through social media language.
Gregory Park;H. Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern.
Journal of Personality and Social Psychology (2015)
Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments
Alexandrin Popescul;Lyle H. Ungar;David M. Pennock;Steve Lawrence.
uncertainty in artificial intelligence (2001)
Psychological Language on Twitter Predicts County-Level Heart Disease Mortality
Johannes C. Eichstaedt;Hansen Andrew Schwartz;Margaret L. Kern;Gregory Park.
Psychological Science (2015)
Iterative Combinatorial Auctions: Theory and Practice
David C. Parkes;Lyle H. Ungar.
national conference on artificial intelligence (2000)
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