Mehryar Mohri mainly focuses on Algorithm, Theoretical computer science, Artificial intelligence, Mathematical optimization and Automaton. His studies deal with areas such as Discrete mathematics, Kernel method, Kernel, Distribution and Simple as well as Algorithm. His Theoretical computer science research is multidisciplinary, relying on both Finite-state machine, Programming language, String, Key and Natural language.
The concepts of his Artificial intelligence study are interwoven with issues in Ranking, Machine learning, Natural language processing and Pattern recognition. His Mathematical optimization study incorporates themes from Regularization, Training set and Regression, Regression problems. The study incorporates disciplines such as Representation, Speech processing and Minification in addition to Automaton.
Mehryar Mohri mostly deals with Algorithm, Artificial intelligence, Theoretical computer science, Automaton and Discrete mathematics. His Algorithm research includes elements of Semiring and Support vector machine. His studies examine the connections between Artificial intelligence and genetics, as well as such issues in Speech recognition, with regards to Rule-based machine translation.
His Theoretical computer science study combines topics in areas such as Context, Key, Series and Regret. His Automaton research incorporates elements of Pseudocode, String and Minification. His Discrete mathematics research is multidisciplinary, incorporating perspectives in Generalization, Rademacher complexity and Combinatorics.
Mehryar Mohri mainly investigates Algorithm, Theoretical computer science, Regret, Artificial intelligence and Machine learning. His work blends Algorithm and Multiple source studies together. His Theoretical computer science study also includes fields such as
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Structure and Generalization. His work on Model selection as part of general Machine learning research is frequently linked to Online learning, Special case and Exploit, bridging the gap between disciplines. His work deals with themes such as Automaton, Computation, Online algorithm and Rademacher complexity, which intersect with Key.
His scientific interests lie mostly in Artificial intelligence, Machine learning, Theoretical computer science, Mathematical optimization and Federated learning. Artificial intelligence is frequently linked to Structure in his study. His Machine learning research incorporates themes from Classifier, Personalization and Class.
As part of one scientific family, Mehryar Mohri deals mainly with the area of Theoretical computer science, narrowing it down to issues related to the Optimization problem, and often Stochastic algorithms, Contrast, Inference and Set. Mehryar Mohri works mostly in the field of Mathematical optimization, limiting it down to concerns involving Simplicity and, occasionally, Distributed computing. Mehryar Mohri connects Function with Algorithm in his research.
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Foundations of Machine Learning
Mehryar Mohri;Afshin Rostamizadeh;Afshin Rostamizadeh;Ameet Talwalkar;Ameet Talwalkar.
(2012)
Finite-state transducers in language and speech processing
Mehryar Mohri.
Computational Linguistics (1997)
Weighted finite-state transducers in speech recognition
Mehryar Mohri;Fernando Pereira;Michael Riley.
Computer Speech & Language (2002)
Advances and open problems in federated learning
Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet.
Foundations and Trends® in Machine Learning (2021)
Advances and Open Problems in Federated Learning
Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet.
arXiv: Learning (2019)
OpenFst: a general and efficient weighted finite-state transducer library
Cyril Allauzen;Michael Riley;Johan Schalkwyk;Wojciech Skut.
international conference on implementation and application of automata (2007)
AUC Optimization vs. Error Rate Minimization
Corinna Cortes;Mehryar Mohri.
neural information processing systems (2003)
Multi-armed bandit algorithms and empirical evaluation
Joannès Vermorel;Mehryar Mohri.
european conference on machine learning (2005)
Domain adaptation: Learning bounds and algorithms
Yishay Mansour;Mehryar Mohri;Afshin Rostamizadeh.
conference on learning theory (2009)
Domain Adaptation with Multiple Sources
Yishay Mansour;Mehryar Mohri;Afshin Rostamizadeh.
neural information processing systems (2008)
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