Constantinos Daskalakis

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 153

Top Venues

CoRR

COLT

NeurIPS

Publications

Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty
Smooth Nash Equilibria: Algorithms and Complexity. ITCS (2024)
Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich
From External to Swap Regret 2.0: An Efficient Reduction and Oblivious Adversary for Large Action Spaces. CoRR (2023)
Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty
Smooth Nash Equilibria: Algorithms and Complexity. CoRR (2023)
Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson
Online Learning and Solving Infinite Games with an ERM Oracle. CoRR (2023)
Itai Ashlagi, Constantinos Daskalakis, Nima Haghpanah
Sequential Mechanisms with Ex Post Individual Rationality. Oper. Res. 71 (1) (2023)
Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang
The Complexity of Markov Equilibrium in Stochastic Games. COLT (2023)
Constantinos Daskalakis, Noah Golowich, Stratis Skoulakis, Emmanouil Zampetakis
STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games. COLT (2023)
Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. NeurIPS (2023)
Panos Stinis, Constantinos Daskalakis, Paul J. Atzberger
SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics. CoRR (2023)
Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell K. Fishelson
Online Learning and Solving Infinite Games with an ERM Oracle. COLT (2023)
Anthimos Vardis Kandiros, Constantinos Daskalakis, Yuval Dagan, Davin Choo
Learning and Testing Latent-Tree Ising Models Efficiently. COLT (2023)
Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
What Makes a Good Fisherman? Linear Regression under Self-Selection Bias. STOC (2023)
Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. CoRR (2023)
Yang Cai, Constantinos Daskalakis
Recommender Systems meet Mechanism Design. EC (2022)
Liu Yang, Constantinos Daskalakis, George E. Karniadakis
Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models. SIAM J. Sci. Comput. 44 (1) (2022)
Constantinos Daskalakis, Noah Golowich, Stratis Skoulakis, Manolis Zampetakis
STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games. CoRR (2022)
Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
Estimation of Standard Auction Models. EC (2022)
Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy
Multi-Item Nontruthful Auctions Achieve Good Revenue. SIAM J. Comput. 51 (6) (2022)
Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
Estimation of Standard Auction Models. CoRR (2022)
Constantinos Daskalakis
Equilibrium Computation, Deep Learning, and Multi-Agent Reinforcement Learning (Invited Talk). ICALP (2022)
Davin Choo, Yuval Dagan, Constantinos Daskalakis, Anthimos Vardis Kandiros
Learning and Testing Latent-Tree Ising Models Efficiently. CoRR (2022)
Yuval Dagan, Constantinos Daskalakis, Anthimos Vardis Kandiros
EM's Convergence in Gaussian Latent Tree Models. CoRR (2022)
Constantinos Daskalakis, Noah Golowich
Fast rates for nonparametric online learning: from realizability to learning in games. STOC (2022)
Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems. CoRR (2022)
Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos
How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI (2022)
Yuval Dagan, Anthimos Vardis Kandiros, Constantinos Daskalakis
EM's Convergence in Gaussian Latent Tree Models. COLT (2022)
Constantinos Daskalakis, Vasilis Syrgkanis
Learning in auctions: Regret is hard, envy is easy. Games Econ. Behav. 134 (2022)
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina, Maxwell Fishelson, Noah Golowich, Tuomas Sandholm
Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games. STOC (2022)
Constantinos Daskalakis, Patroklos Stefanou, Rui Yao, Manolis Zampetakis
Efficient Truncated Linear Regression with Unknown Noise Variance. CoRR (2022)
Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang
The Complexity of Markov Equilibrium in Stochastic Games. CoRR (2022)
Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
What Makes A Good Fisherman? Linear Regression under Self-Selection Bias. CoRR (2022)
Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis
Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems. ICML (2022)
Constantinos Daskalakis, Vasilis Kontonis, Christos Tzamos, Emmanouil Zampetakis
A Statistical Taylor Theorem and Extrapolation of Truncated Densities. COLT (2021)
Yang Cai, Constantinos Daskalakis
Recommender Systems meet Mechanism Design. CoRR (2021)
Constantinos Daskalakis, Qinxuan Pan
Sample-optimal and efficient learning of tree Ising models. STOC (2021)
Constantinos Daskalakis, Stratis Skoulakis, Manolis Zampetakis
The complexity of constrained min-max optimization. STOC (2021)
Mucong Ding, Constantinos Daskalakis, Soheil Feizi
GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences. AISTATS (2021)
Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization. AISTATS (2021)
Anthimos Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis
Statistical Estimation from Dependent Data. ICML (2021)
Constantinos Daskalakis, Noah Golowich
Fast Rates for Nonparametric Online Learning: From Realizability to Learning in Games. CoRR (2021)
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina, Maxwell Fishelson, Noah Golowich, Tuomas Sandholm
Near-Optimal No-Regret Learning for Correlated Equilibria in Multi-Player General-Sum Games. CoRR (2021)
Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich
Near-Optimal No-Regret Learning in General Games. CoRR (2021)
Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich
Near-Optimal No-Regret Learning in General Games. NeurIPS (2021)
Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos
How Good are Low-Rank Approximations in Gaussian Process Regression? CoRR (2021)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Anthimos Vardis Kandiros
Learning Ising models from one or multiple samples. STOC (2021)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Surbhi Goel, Anthimos Vardis Kandiros
Statistical Estimation from Dependent Data. CoRR (2021)
Constantinos Daskalakis, Patroklos Stefanou, Rui Yao, Emmanouil Zampetakis
Efficient Truncated Linear Regression with Unknown Noise Variance. NeurIPS (2021)
Fotini Christia, Michael J. Curry, Constantinos Daskalakis, Erik D. Demaine, John P. Dickerson, MohammadTaghi Hajiaghayi, Adam Hesterberg, Marina Knittel, Aidan Milliff
Scalable Equilibrium Computation in Multi-agent Influence Games on Networks. AAAI (2021)
Constantinos Daskalakis, Dylan J. Foster, Noah Golowich
Independent Policy Gradient Methods for Competitive Reinforcement Learning. CoRR (2021)
Constantinos Daskalakis
Technical perspective: The quest for optimal multi-item auctions. Commun. ACM 64 (8) (2021)
Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis
A Theoretical and Practical Framework for Regression and Classification from Truncated Samples. AISTATS (2020)
Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis
Constant-Expansion Suffices for Compressed Sensing with Generative Priors. CoRR (2020)
Constantinos Daskalakis, Stratis Skoulakis, Manolis Zampetakis
The Complexity of Constrained Min-Max Optimization. CoRR (2020)
Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis
Truncated Linear Regression in High Dimensions. NeurIPS (2020)
Constantinos Daskalakis, Manolis Zampetakis
More Revenue from Two Samples via Factor Revealing SDPs. EC (2020)
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis
Computationally and Statistically Efficient Truncated Regression. CoRR (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis
Tight last-iterate convergence rates for no-regret learning in multi-player games. CoRR (2020)
Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization. CoRR (2020)
Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy
Simple, Credible, and Approximately-Optimal Auctions. EC (2020)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Logistic-Regression with peer-group effects via inference in higher order Ising models. CoRR (2020)
Johannes Brustle, Yang Cai, Constantinos Daskalakis
Multi-Item Mechanisms without Item-Independence: Learnability via Robustness. EC (2020)
Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis
Truncated Linear Regression in High Dimensions. CoRR (2020)
Constantinos Daskalakis, Dylan J. Foster, Noah Golowich
Independent Policy Gradient Methods for Competitive Reinforcement Learning. NeurIPS (2020)
Qi Lei, Jason D. Lee, Alex Dimakis, Constantinos Daskalakis
SGD Learns One-Layer Networks in WGANs. ICML (2020)
Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis
Constant-Expansion Suffices for Compressed Sensing with Generative Priors. NeurIPS (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. COLT (2020)
Constantinos Daskalakis, Qinxuan Pan
Tree-structured Ising models can be learned efficiently. CoRR (2020)
Mucong Ding, Constantinos Daskalakis, Soheil Feizi
Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs. CoRR (2020)
Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy
Simple, Credible, and Approximately-Optimal Auctions. CoRR (2020)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Anthimos Vardis Kandiros
Estimating Ising Models from One Sample. CoRR (2020)
Liu Yang, Constantinos Daskalakis, George Em Karniadakis
Generative Ensemble-Regression: Learning Stochastic Dynamics from Discrete Particle Ensemble Observations. CoRR (2020)
Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos
Faster Gaussian Processes via Deep Embeddings. CoRR (2020)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Logistic regression with peer-group effects via inference in higher-order Ising models. AISTATS (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis
Tight last-iterate convergence rates for no-regret learning in multi-player games. NeurIPS (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. CoRR (2020)
Qi Lei, Jason D. Lee, Alexandros G. Dimakis, Constantinos Daskalakis
SGD Learns One-Layer Networks in WGANs. CoRR (2019)
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis
Computationally and Statistically Efficient Truncated Regression. COLT (2019)
Constantinos Daskalakis, Ioannis Panageas
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization. ITCS (2019)
Johannes Brustle, Yang Cai, Constantinos Daskalakis
Multi-Item Mechanisms without Item-Independence: Learnability via Robustness. CoRR (2019)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
Learning from weakly dependent data under Dobrushin's condition. CoRR (2019)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
Learning from Weakly Dependent Data under Dobrushin's Condition. COLT (2019)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Regression from dependent observations. STOC (2019)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Regression from Dependent Observations. CoRR (2019)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Testing Ising Models. IEEE Trans. Inf. Theory 65 (11) (2019)
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis
Efficient Statistics, in High Dimensions, from Truncated Samples. FOCS (2018)
Shipra Agrawal, Constantinos Daskalakis, Vahab S. Mirrokni, Balasubramanian Sivan
Robust Repeated Auctions under Heterogeneous Buyer Behavior. CoRR (2018)
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
Learning and Testing Causal Models with Interventions. CoRR (2018)
Constantinos Daskalakis, Gautam Kamath, John Wright
Which Distribution Distances are Sublinearly Testable? Electron. Colloquium Comput. Complex. 25 (2018)
Constantinos Daskalakis, Ioannis Panageas
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization. CoRR (2018)
Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons. NeurIPS (2018)
Constantinos Daskalakis, Nikhil R. Devanur, S. Matthew Weinberg
Revenue Maximization and Ex-Post Budget Constraints. ACM Trans. Economics and Comput. 6 (3-4) (2018)
Constantinos Daskalakis, Christos Tzamos, Manolis Zampetakis
A converse to Banach's fixed point theorem and its CLS-completeness. STOC (2018)
Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng
Training GANs with Optimism. ICLR (Poster) (2018)
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis
Efficient Statistics, in High Dimensions, from Truncated Samples. CoRR (2018)
Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons. CoRR (2018)
Constantinos Daskalakis, Gautam Kamath, John Wright
Which Distribution Distances are Sublinearly Testable? SODA (2018)
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy
Learning and Testing Causal Models with Interventions. NeurIPS (2018)
Constantinos Daskalakis, Nishanth Dikkala, Nick Gravin
Testing Symmetric Markov Chains From a Single Trajectory. COLT (2018)
Constantinos Daskalakis, Ioannis Panageas
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization. CoRR (2018)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Testing Ising Models. SODA (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Constantinos Daskalakis