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Constantinos Daskalakis

Constantinos Daskalakis

D-Index & Metrics

Computer Science

D-Index
53
Citations
9913
World Ranking
4877
National Ranking
2268

Research.com Recognitions

  • 2018 - ACM Grace Murray Hopper Award For seminal contributions to the complexity of Nash Equilibria.
  • 2018 - Rolf Nevanlinna Prize "For transforming our understanding of the computational complexity of fundamental problems in markets, auctions, equilibria, and other economic structures. His work provides both efficient algorithms and limits on what can be performed efficiently in these domains."[14]
  • 2010 - Fellow of Alfred P. Sloan Foundation

Overview

Constantinos Daskalakis is a researcher affiliated with MIT in the United States, focused primarily on Computer Science. Their work spans several subfields, including Artificial Intelligence, Management Science and Operations Research, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, and Computational Mechanics.

The main research topics covered by Constantinos Daskalakis include:

  • Advanced Bandit Algorithms Research
  • Auction Theory and Applications
  • Sparse and Compressive Sensing Techniques
  • Machine Learning and Algorithms
  • Gaussian Processes and Bayesian Inference
  • Game Theory and Applications
  • Bayesian Modeling and Causal Inference

Publications by this scientist have appeared primarily in the venue arXiv (Cornell University), with 46 contributions. Other publication venues include:

  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Proceedings of the 23rd ACM Conference on Economics and Computation
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SIAM Journal on Scientific Computing

Selected recent papers by Constantinos Daskalakis include:

  • "Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models," 2022, SIAM Journal on Scientific Computing
  • "Independent Policy Gradient Methods for Competitive Reinforcement Learning," 2021, arXiv (Cornell University)
  • "Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems," 2020, arXiv (Cornell University)

Frequent collaborators of Constantinos Daskalakis include:

  • Noah Golowich
  • Manolis Zampetakis
  • Yuval Dagan
  • Maxwell Fishelson
  • Yeshwanth Cherapanamjeri

The scientist has received multiple awards recognizing their contributions, including the Rolf Nevanlinna Prize in 2018 for work on computational complexity in markets, auctions, and economic structures. They were also granted the ACM Grace Murray Hopper Award in 2018 for contributions related to the complexity of Nash Equilibria. Earlier in their career, they became a Fellow of the Alfred P. Sloan Foundation in 2010.

Best Publications

  • The Complexity of Computing a Nash Equilibrium

    Constantinos Daskalakis;Paul W. Goldberg;Christos H. Papadimitriou

  • Training GANs with Optimism

    Constantinos Daskalakis;Andrew Ilyas;Vasilis Syrgkanis;Haoyang Zeng

  • A note on approximate Nash equilibria

    Constantinos Daskalakis;Aranyak Mehta;Christos Papadimitriou

  • Three-Player Games Are Hard

    Constantinos Daskalakis;Christos H. Papadimitriou

  • Optimal Multi-dimensional Mechanism Design: Reducing Revenue to Welfare Maximization

    Yang Cai;Constantinos Daskalakis;S. Matthew Weinberg

  • The Robust Manifold Defense: Adversarial Training using Generative Models

    Andrew Ilyas;Ajil Jalal;Eirini Asteri;Constantinos Daskalakis

  • An algorithmic characterization of multi-dimensional mechanisms

    Yang Cai;Constantinos Daskalakis;S. Matthew Weinberg

  • Near-optimal no-regret algorithms for zero-sum games

    Constantinos Daskalakis;Alan Deckelbaum;Anthony Kim

  • Progress in approximate nash equilibria

    Constantinos Daskalakis;Aranyak Mehta;Christos Papadimitriou

  • The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization

    Constantinos Daskalakis;Ioannis Panageas

  • Message-Passing Algorithms and Improved LP Decoding

    S. Arora;C. Daskalakis;D. Steurer

  • Optimal testing for properties of distributions

    Jayadev Acharya;Constantinos Daskalakis;Gautam Kamath

  • The complexity of optimal mechanism design

    Constantinos Daskalakis;Alan Deckelbaum;Christos Tzamos

  • First to market is not everything: an analysis of preferential attachment with fitness

    Christian Borgs;Jennifer Chayes;Constantinos Daskalakis;Sebastien Roch

  • Symmetries and optimal multi-dimensional mechanism design

    Constantinos Daskalakis;Seth Matthew Weinberg

  • On oblivious PTAS's for nash equilibrium

    Constantinos Daskalakis;Christos H. Papadimitriou

  • Computing Equilibria in Anonymous Games

    C. Daskalakis;C. Papadimitriou

  • Continuous local search

    Constantinos Daskalakis;Christos Papadimitriou

  • Mechanism design via optimal transport

    Constantinos Daskalakis;Alan Deckelbaum;Christos Tzamos

  • Optimum Statistical Estimation with Strategic Data Sources

    Yang Cai;Constantinos Daskalakis;Christos H. Papadimitriou

  • Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization

    Constantinos Daskalakis;Ioannis Panageas

  • Proceedings of the 2017 ACM Conference on Economics and Computation

    Constantinos Daskalakis;Moshe Babaioff;Hervé Moulin

  • Independent Policy Gradient Methods for Competitive Reinforcement Learning

    Constantinos Daskalakis;Dylan J. Foster;Noah Golowich

Frequent Co-Authors

Christos H. Papadimitriou
Christos H. Papadimitriou Columbia University
Ilias Diakonikolas
Ilias Diakonikolas University of Wisconsin–Madison
Rocco A. Servedio
Rocco A. Servedio Columbia University
Gregory Valiant
Gregory Valiant Stanford University
Alexandros G. Dimakis
Alexandros G. Dimakis The University of Texas at Austin
Richard M. Karp
Richard M. Karp University of California, Berkeley
Avinatan Hassidim
Avinatan Hassidim Bar-Ilan University
Mihalis Yannakakis
Mihalis Yannakakis Columbia University

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