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ORCIDConstantinos Daskalakis
Konstantinos Daskalakis – Costis Daskalakis
Person information
- affiliation: MIT
- affiliation (former): University of California, Berkeley, USA
- award: Nevanlinna Prize, 2018
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2020 – today
- 2024
[c125]Fan Chen, Constantinos Daskalakis, Noah Golowich, Alexander Rakhlin:
Near-Optimal Learning and Planning in Separated Latent MDPs. COLT 2024: 995-1067- [c124]Constantinos Daskalakis, Noah Golowich:
Is Efficient PAC Learning Possible with an Oracle That Responds "Yes" or "No"? COLT 2024: 1263-1307 - [c123]Giannis Daras, Alex Dimakis, Constantinos Daskalakis:
Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data. ICML 2024 - [c122]Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty:
Smooth Nash Equilibria: Algorithms and Complexity. ITCS 2024: 37:1-37:22 - [c121]Yuval Dagan
, Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich:
From External to Swap Regret 2.0: An Efficient Reduction for Large Action Spaces. STOC 2024: 1216-1222 - [i112]Yang Cai, Constantinos Daskalakis, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Tractable Local Equilibria in Non-Concave Games. CoRR abs/2403.08171 (2024) - [i111]Giannis Daras, Alexandros G. Dimakis, Constantinos Daskalakis:
Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data. CoRR abs/2404.10177 (2024) - [i110]Fan Chen, Constantinos Daskalakis, Noah Golowich, Alexander Rakhlin:
Near-Optimal Learning and Planning in Separated Latent MDPs. CoRR abs/2406.07920 (2024) - [i109]Constantinos Daskalakis, Noah Golowich:
Is Efficient PAC Learning Possible with an Oracle That Responds 'Yes' or 'No'? CoRR abs/2406.11667 (2024) - [i108]Constantinos Daskalakis, Gabriele Farina, Noah Golowich, Tuomas Sandholm, Brian Hu Zhang:
A Lower Bound on Swap Regret in Extensive-Form Games. CoRR abs/2406.13116 (2024) - [i107]Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich, Robert Kleinberg, Princewill Okoroafor:
Improved bounds for calibration via stronger sign preservation games. CoRR abs/2406.13668 (2024) - [i106]Angelos Assos, Yuval Dagan, Constantinos Daskalakis:
Maximizing utility in multi-agent environments by anticipating the behavior of other learners. CoRR abs/2407.04889 (2024) - 2023
- [j26]Itai Ashlagi, Constantinos Daskalakis, Nima Haghpanah:
Sequential Mechanisms with Ex Post Individual Rationality. Oper. Res. 71(1): 245-258 (2023) - [c120]Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell K. Fishelson:
Online Learning and Solving Infinite Games with an ERM Oracle. COLT 2023: 274-324 - [c119]Anthimos Vardis Kandiros, Constantinos Daskalakis, Yuval Dagan, Davin Choo:
Learning and Testing Latent-Tree Ising Models Efficiently. COLT 2023: 1666-1729 - [c118]Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang:
The Complexity of Markov Equilibrium in Stochastic Games. COLT 2023: 4180-4234 - [c117]Constantinos Daskalakis, Noah Golowich, Stratis Skoulakis, Emmanouil Zampetakis:
STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games. COLT 2023: 5146-5198 - [c116]Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis:
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. NeurIPS 2023 - [c115]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
What Makes a Good Fisherman? Linear Regression under Self-Selection Bias. STOC 2023: 1699-1712 - [i105]Panos Stinis, Constantinos Daskalakis, Paul J. Atzberger:
SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics. CoRR abs/2302.03663 (2023) - [i104]Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis:
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. CoRR abs/2302.09057 (2023) - [i103]Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson:
Online Learning and Solving Infinite Games with an ERM Oracle. CoRR abs/2307.01689 (2023) - [i102]Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty:
Smooth Nash Equilibria: Algorithms and Complexity. CoRR abs/2309.12226 (2023) - [i101]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 abs/2310.19786 (2023) - 2022
- [j25]Constantinos Daskalakis, Vasilis Syrgkanis:
Learning in auctions: Regret is hard, envy is easy. Games Econ. Behav. 134: 308-343 (2022) - [j24]Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy:
Multi-Item Nontruthful Auctions Achieve Good Revenue. SIAM J. Comput. 51(6): 1796-1838 (2022) - [j23]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): 80- (2022) - [c114]Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos:
How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI 2022: 6463-6470 - [c113]Yuval Dagan, Anthimos Vardis Kandiros, Constantinos Daskalakis:
EM's Convergence in Gaussian Latent Tree Models. COLT 2022: 2597-2667 - [c112]Constantinos Daskalakis:
Equilibrium Computation, Deep Learning, and Multi-Agent Reinforcement Learning (Invited Talk). ICALP 2022: 2:1-2:1 - [c111]Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis:
Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems. ICML 2022: 4722-4753 - [c110]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
Estimation of Standard Auction Models. EC 2022: 602-603 - [c109]Yang Cai, Constantinos Daskalakis:
Recommender Systems meet Mechanism Design. EC 2022: 897-914 - [c108]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: 736-749 - [c107]Constantinos Daskalakis, Noah Golowich:
Fast rates for nonparametric online learning: from realizability to learning in games. STOC 2022: 846-859 - [i100]Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang:
The Complexity of Markov Equilibrium in Stochastic Games. CoRR abs/2204.03991 (2022) - [i99]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
Estimation of Standard Auction Models. CoRR abs/2205.02060 (2022) - [i98]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
What Makes A Good Fisherman? Linear Regression under Self-Selection Bias. CoRR abs/2205.03246 (2022) - [i97]Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis:
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems. CoRR abs/2206.09104 (2022) - [i96]Constantinos Daskalakis, Patroklos Stefanou, Rui Yao, Manolis Zampetakis:
Efficient Truncated Linear Regression with Unknown Noise Variance. CoRR abs/2208.12042 (2022) - [i95]Constantinos Daskalakis, Noah Golowich, Stratis Skoulakis, Manolis Zampetakis:
STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games. CoRR abs/2210.09769 (2022) - [i94]Yuval Dagan, Constantinos Daskalakis, Anthimos Vardis Kandiros:
EM's Convergence in Gaussian Latent Tree Models. CoRR abs/2211.11904 (2022) - [i93]Davin Choo, Yuval Dagan, Constantinos Daskalakis, Anthimos Vardis Kandiros:
Learning and Testing Latent-Tree Ising Models Efficiently. CoRR abs/2211.13291 (2022) - 2021
- [j22]Constantinos Daskalakis:
Technical perspective: The quest for optimal multi-item auctions. Commun. ACM 64(8): 108 (2021) - [c106]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: 5277-5285 - [c105]Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan:
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization. AISTATS 2021: 2746-2754 - [c104]Mucong Ding, Constantinos Daskalakis, Soheil Feizi:
GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences. AISTATS 2021: 3709-3717 - [c103]Constantinos Daskalakis, Vasilis Kontonis, Christos Tzamos, Emmanouil Zampetakis:
A Statistical Taylor Theorem and Extrapolation of Truncated Densities. COLT 2021: 1395-1398 - [c102]Anthimos Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis:
Statistical Estimation from Dependent Data. ICML 2021: 5269-5278 - [c101]Constantinos Daskalakis, Patroklos Stefanou, Rui Yao, Emmanouil Zampetakis:
Efficient Truncated Linear Regression with Unknown Noise Variance. NeurIPS 2021: 1952-1963 - [c100]Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich:
Near-Optimal No-Regret Learning in General Games. NeurIPS 2021: 27604-27616 - [c99]Constantinos Daskalakis, Qinxuan Pan:
Sample-optimal and efficient learning of tree Ising models. STOC 2021: 133-146 - [c98]Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Anthimos Vardis Kandiros:
Learning Ising models from one or multiple samples. STOC 2021: 161-168 - [c97]Constantinos Daskalakis, Stratis Skoulakis, Manolis Zampetakis:
The complexity of constrained min-max optimization. STOC 2021: 1466-1478 - [i92]Constantinos Daskalakis, Dylan J. Foster, Noah Golowich:
Independent Policy Gradient Methods for Competitive Reinforcement Learning. CoRR abs/2101.04233 (2021) - [i91]Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Surbhi Goel, Anthimos Vardis Kandiros:
Statistical Estimation from Dependent Data. CoRR abs/2107.09773 (2021) - [i90]Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich:
Near-Optimal No-Regret Learning in General Games. CoRR abs/2108.06924 (2021) - [i89]Yang Cai, Constantinos Daskalakis:
Recommender Systems meet Mechanism Design. CoRR abs/2110.12558 (2021) - [i88]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 abs/2111.06008 (2021) - [i87]Constantinos Daskalakis, Noah Golowich:
Fast Rates for Nonparametric Online Learning: From Realizability to Learning in Games. CoRR abs/2111.08911 (2021) - 2020
- [c96]Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas:
Logistic regression with peer-group effects via inference in higher-order Ising models. AISTATS 2020: 3653-3663 - [c95]Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis:
A Theoretical and Practical Framework for Regression and Classification from Truncated Samples. AISTATS 2020: 4463-4473 - [c94]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: 1758-1784 - [c93]Qi Lei, Jason D. Lee, Alex Dimakis, Constantinos Daskalakis:
SGD Learns One-Layer Networks in WGANs. ICML 2020: 5799-5808 - [c92]Constantinos Daskalakis, Dylan J. Foster, Noah Golowich:
Independent Policy Gradient Methods for Competitive Reinforcement Learning. NeurIPS 2020 - [c91]Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis:
Truncated Linear Regression in High Dimensions. NeurIPS 2020 - [c90]Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis:
Constant-Expansion Suffices for Compressed Sensing with Generative Priors. NeurIPS 2020 - [c89]Noah Golowich, Sarath Pattathil, Constantinos Daskalakis:
Tight last-iterate convergence rates for no-regret learning in multi-player games. NeurIPS 2020 - [c88]Constantinos Daskalakis, Manolis Zampetakis:
More Revenue from Two Samples via Factor Revealing SDPs. EC 2020: 257-272 - [c87]Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy:
Simple, Credible, and Approximately-Optimal Auctions. EC 2020: 713 - [c86]Johannes Brustle, Yang Cai, Constantinos Daskalakis:
Multi-Item Mechanisms without Item-Independence: Learnability via Robustness. EC 2020: 715-761 - [i86]Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar:
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. CoRR abs/2002.00057 (2020) - [i85]Constantinos Daskalakis, Maxwell Fishelson, Brendan Lucier, Vasilis Syrgkanis, Santhoshini Velusamy:
Simple, Credible, and Approximately-Optimal Auctions. CoRR abs/2002.06702 (2020) - [i84]Mucong Ding, Constantinos Daskalakis, Soheil Feizi:
Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs. CoRR abs/2003.00652 (2020) - [i83]Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas:
Logistic-Regression with peer-group effects via inference in higher order Ising models. CoRR abs/2003.08259 (2020) - [i82]Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos:
Faster Gaussian Processes via Deep Embeddings. CoRR abs/2004.01584 (2020) - [i81]Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Anthimos Vardis Kandiros:
Estimating Ising Models from One Sample. CoRR abs/2004.09370 (2020) - [i80]Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis:
Constant-Expansion Suffices for Compressed Sensing with Generative Priors. CoRR abs/2006.04237 (2020) - [i79]Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis:
Truncated Linear Regression in High Dimensions. CoRR abs/2007.14539 (2020) - [i78]Liu Yang, Constantinos Daskalakis, George Em Karniadakis:
Generative Ensemble-Regression: Learning Stochastic Dynamics from Discrete Particle Ensemble Observations. CoRR abs/2008.01915 (2020) - [i77]Constantinos Daskalakis, Stratis Skoulakis, Manolis Zampetakis:
The Complexity of Constrained Min-Max Optimization. CoRR abs/2009.09623 (2020) - [i76]Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis:
Computationally and Statistically Efficient Truncated Regression. CoRR abs/2010.12000 (2020) - [i75]Noah Golowich, Sarath Pattathil, Constantinos Daskalakis:
Tight last-iterate convergence rates for no-regret learning in multi-player games. CoRR abs/2010.13724 (2020) - [i74]Constantinos Daskalakis, Qinxuan Pan:
Tree-structured Ising models can be learned efficiently. CoRR abs/2010.14864 (2020) - [i73]Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan:
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization. CoRR abs/2011.00364 (2020)
2010 – 2019
- 2019
- [j21]Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath:
Testing Ising Models. IEEE Trans. Inf. Theory 65(11): 6829-6852 (2019) - [c85]Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti:
Learning from Weakly Dependent Data under Dobrushin's Condition. COLT 2019: 914-928 - [c84]Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis:
Computationally and Statistically Efficient Truncated Regression. COLT 2019: 955-960 - [c83]Constantinos Daskalakis, Ioannis Panageas:
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization. ITCS 2019: 27:1-27:18 - [c82]Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas:
Regression from dependent observations. STOC 2019: 881-889 - [p1]Tugba Bozcaga, Fotini Christia, Elizabeth Harwood, Constantinos Daskalakis, Christos Papademetriou:
Syrian Refugee Integration in Turkey: Evidence from Call Detail Records. Data for Refugees Challenge 2019: 223-249 - [i72]Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas:
Regression from Dependent Observations. CoRR abs/1905.03353 (2019) - [i71]Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti:
Learning from weakly dependent data under Dobrushin's condition. CoRR abs/1906.09247 (2019) - [i70]Qi Lei, Jason D. Lee, Alexandros G. Dimakis, Constantinos Daskalakis:
SGD Learns One-Layer Networks in WGANs. CoRR abs/1910.07030 (2019) - [i69]Johannes Brustle, Yang Cai, Constantinos Daskalakis:
Multi-Item Mechanisms without Item-Independence: Learnability via Robustness. CoRR abs/1911.02146 (2019) - 2018
- [j20]Costis Daskalakis, Yael Kalai, Sandy Irani:
Special Section on the Forty-Seventh Annual ACM Symposium on Theory of Computing (STOC 2015). SIAM J. Comput. 47(3): 888-889 (2018) - [j19]Constantinos Daskalakis, Nikhil R. Devanur, S. Matthew Weinberg:
Revenue Maximization and Ex-Post Budget Constraints. ACM Trans. Economics and Comput. 6(3-4): 20:1-20:19 (2018) - [c81]Costis Daskalakis, Christos Tzamos, Manolis Zampetakis:
Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model. AISTATS 2018: 2056-2064 - [c80]Constantinos Daskalakis, Nishanth Dikkala, Nick Gravin:
Testing Symmetric Markov Chains From a Single Trajectory. COLT 2018: 385-409 - [c79]Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis:
Efficient Statistics, in High Dimensions, from Truncated Samples. FOCS 2018: 639-649 - [c78]Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng:
Training GANs with Optimism. ICLR (Poster) 2018 - [c77]Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti:
HOGWILD!-Gibbs can be PanAccurate. NeurIPS 2018: 32-41 - [c76]Constantinos Daskalakis, Ioannis Panageas:
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization. NeurIPS 2018: 9256-9266 - [c75]Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy:
Learning and Testing Causal Models with Interventions. NeurIPS 2018: 9469-9481 - [c74]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: 10880-10890 - [c73]Shipra Agrawal, Constantinos Daskalakis, Vahab S. Mirrokni, Balasubramanian Sivan:
Robust Repeated Auctions under Heterogeneous Buyer Behavior. EC 2018: 171 - [c72]Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath:
Testing Ising Models. SODA 2018: 1989-2007 - [c71]Constantinos Daskalakis, Gautam Kamath, John Wright:
Which Distribution Distances are Sublinearly Testable? SODA 2018: 2747-2764 - [c70]Constantinos Daskalakis, Christos Tzamos, Manolis Zampetakis:
A converse to Banach's fixed point theorem and its CLS-completeness. STOC 2018: 44-50 - [i68]Shipra Agrawal, Constantinos Daskalakis, Vahab S. Mirrokni, Balasubramanian Sivan:
Robust Repeated Auctions under Heterogeneous Buyer Behavior. CoRR abs/1803.00494 (2018) - [i67]Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, Saravanan Kandasamy:
Learning and Testing Causal Models with Interventions. CoRR abs/1805.09697 (2018) - [i66]Constantinos Daskalakis, Ioannis Panageas:
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization. CoRR abs/1807.03907 (2018) - [i65]Constantinos Daskalakis, Ioannis Panageas:
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization. CoRR abs/1807.04252 (2018) - [i64]Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, Manolis Zampetakis:
Efficient Statistics, in High Dimensions, from Truncated Samples. CoRR abs/1809.03986 (2018) - [i63]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 abs/1810.11896 (2018) - [i62]Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti:
HOGWILD!-Gibbs can be PanAccurate. CoRR abs/1811.10581 (2018) - [i61]Constantinos Daskalakis, Gautam Kamath, John Wright:
Which Distribution Distances are Sublinearly Testable? Electron. Colloquium Comput. Complex. TR18 (2018) - 2017
- [c69]Constantinos Daskalakis, Qinxuan Pan:
Square Hellinger Subadditivity for Bayesian Networks and its Applications to Identity Testing. COLT 2017: 697-703 - [c68]Constantinos Daskalakis, Christos Tzamos, Manolis Zampetakis:
Ten Steps of EM Suffice for Mixtures of Two Gaussians. COLT 2017: 704-710 - [c67]Constantinos Daskalakis, Yasushi Kawase:
Optimal Stopping Rules for Sequential Hypothesis Testing. ESA 2017: 32:1-32:14 - [c66]Yang Cai, Constantinos Daskalakis:
Learning Multi-Item Auctions with (or without) Samples. FOCS 2017: 516-527 - [c65]