The Science Academy Society of Turkey - Bilim Akademisi Electrical-Electronic Engineering
Asuman Ozdaglar mostly deals with Mathematical optimization, Subgradient method, Rate of convergence, Convergence and Optimization problem. Asuman Ozdaglar has included themes like Distributed algorithm, Multi-agent system and Convex optimization in her Mathematical optimization study. Her Subgradient method research is multidisciplinary, incorporating elements of Duality, Unconstrained optimization, Regular polygon, Slater's condition and Constraint.
Her research in Rate of convergence tackles topics such as Computation which are related to areas like Acceleration, Proximal Gradient Methods and Differentiable function. Her Convergence research incorporates elements of Voter model, Asynchronous communication and Artificial intelligence. Her research investigates the connection with Optimization problem and areas like Stochastic process which intersect with concerns in Sequence learning, Bounded function, Information cascade, Path and Integer programming.
The scientist’s investigation covers issues in Mathematical optimization, Rate of convergence, Mathematical economics, Convergence and Microeconomics. Her study in Mathematical optimization is interdisciplinary in nature, drawing from both Distributed algorithm, Function and Convex optimization. Her Rate of convergence study integrates concerns from other disciplines, such as Convex function, Regular polygon, Computation and Applied mathematics.
Her work deals with themes such as Class, Bounded function and Artificial intelligence, which intersect with Mathematical economics. Her study connects Algorithm and Convergence. Asuman Ozdaglar has researched Oligopoly in several fields, including Telecommunications network and Arbitrarily large.
Her primary areas of investigation include Applied mathematics, Rate of convergence, Mathematical optimization, Saddle point and Nash equilibrium. The study incorporates disciplines such as Proximal point method, Convergence, Quadratic equation, Condition number and Robustness in addition to Applied mathematics. Her Convergence study which covers Function that intersects with Empirical risk minimization.
The Rate of convergence study combines topics in areas such as Optimization problem, Convex function, System of linear equations and Convex optimization. Her Mathematical optimization research is multidisciplinary, incorporating perspectives in Stability, Enhanced Data Rates for GSM Evolution and Network formation. Her Saddle point study also includes fields such as
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Distributed Subgradient Methods for Multi-Agent Optimization
A. Nedic;A. Ozdaglar.
IEEE Transactions on Automatic Control (2009)
Convex Analysis and Optimization
Dimitri P. Bertsekas;Angelia Nedić;Asuman E. Ozdaglar.
The Network Origins of Aggregate Fluctuations
Daron Acemoglu;Vasco M. Carvalho;Asuman E. Ozdaglar;Alireza Tahbaz-Salehi.
Constrained Consensus and Optimization in Multi-Agent Networks
A. Nedic;A. Ozdaglar;P.A. Parrilo.
IEEE Transactions on Automatic Control (2010)
Systemic risk and stability in financial networks
Daron Acemoglu;Asuman Ozdaglar;Alireza Tahbaz-Salehi.
The American Economic Review (2015)
Bayesian Learning in Social Networks
Daron Acemoglu;Munther A. Dahleh;Ilan Lobel;Asuman Ozdaglar.
The Review of Economic Studies (2011)
On distributed averaging algorithms and quantization effects
A. Nedic;A. Olshevsky;A. Ozdaglar;J.N. Tsitsiklis.
conference on decision and control (2008)
Opinion Dynamics and Learning in Social Networks
Daron Acemoglu;Asuman E. Ozdaglar.
Dynamic Games and Applications (2011)
Spread of (mis)information in social networks
Daron Acemoglu;Asuman E. Ozdaglar;Ali Parandehgheibi.
Games and Economic Behavior (2010)
Opinion Fluctuations and Disagreement in Social Networks
Daron Acemoğlu;Giacomo Como;Fabio Fagnani;Asuman Ozdaglar.
Mathematics of Operations Research (2013)
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