Statements (70)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
computer scientist
|
| gptkbp:affiliatedWith |
gptkb:Princeton_University
|
| gptkbp:author |
Freund,_Yoav
|
| gptkbp:awardedBy |
ACM Fellow
Ph.D. Gödel Prize |
| gptkbp:birthYear |
1963
|
| gptkbp:bornIn |
gptkb:New_York_City
|
| gptkbp:contributedTo |
machine learning
|
| gptkbp:fieldOfStudy |
Artificial Intelligence
|
| gptkbp:hasArtwork |
gptkb:IBM_Research
gptkb:Microsoft_Research AT&T Labs |
| gptkbp:hasCharacter |
numerous_PhD_students
|
| gptkbp:hasClient |
gptkb:explainable_AI
computer vision deep learning natural language processing online learning active learning bioinformatics data mining reinforcement learning unsupervised learning game theory information retrieval recommendation systems social network analysis transfer learning ensemble methods pattern recognition AI ethics algorithmic fairness classification algorithms regression algorithms semi-supervised learning theory of neural networks computational learning theory adversarial machine learning federated learning theoretical foundations of machine learning multi-instance learning multi-label learning theory of Bayesian networks theory of bias-variance tradeoff theory of clustering theory of decision trees theory of dimensionality reduction theory of ensemble learning theory of feature selection theory of generalization theory of graphical models theory of model selection theory of overfitting theory of probabilistic models theory of reinforcement learning. theory of support vector machines theory_of_Markov_models theory_of_underfitting |
| gptkbp:hasCollaboratedWith |
gptkb:Robert_E._Schapire
|
| gptkbp:hasPublications |
over 100 papers
|
| https://www.w3.org/2000/01/rdf-schema#label |
Robert E. Schapire
|
| gptkbp:influenced |
many machine learning researchers
|
| gptkbp:influencedBy |
Vladimir Vapnik
|
| gptkbp:knownFor |
gptkb:AdaBoost
boosting algorithms |
| gptkbp:nationality |
American
|
| gptkbp:patentDescription |
Theoretical Analysis of Boosting Algorithms
|
| gptkbp:publishedIn |
gptkb:Journal_of_Machine_Learning_Research
|
| gptkbp:researchFocus |
statistical learning theory
|