Information theoretic properties of Markov random fields, and their algorithmic applications L Hamilton, F Koehler, A Moitra Advances in Neural Information Processing Systems, 2463-2472, 2017 | 30 | 2017 |

Optimal batch schedules for parallel machines F Koehler, S Khuller Workshop on Algorithms and Data Structures, 475-486, 2013 | 22 | 2013 |

Provable algorithms for inference in topic models S Arora, R Ge, F Koehler, T Ma, A Moitra International Conference on Machine Learning, 2859-2867, 2016 | 21 | 2016 |

Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective V Jain, F Koehler, A Risteski Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 10 | 2019 |

Learning restricted Boltzmann machines via influence maximization G Bresler, F Koehler, A Moitra Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 9 | 2019 |

The mean-field approximation: Information inequalities, algorithms, and complexity V Jain, F Koehler, E Mossel arXiv preprint arXiv:1802.06126, 2018 | 9 | 2018 |

The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure F Koehler, A Risteski International Conference on Learning Representations, 2018 | 6* | 2018 |

Busy time scheduling on a bounded number of machines F Koehler, S Khuller Workshop on Algorithms and Data Structures, 521-532, 2017 | 4 | 2017 |

How many subpopulations is too many? Exponential lower bounds for inferring population histories Y Kim, F Koehler, A Moitra, E Mossel, G Ramnarayan International Conference on Research in Computational Molecular Biology, 136-157, 2019 | 3 | 2019 |

Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay F Koehler Advances in Neural Information Processing Systems, 8331-8341, 2019 | 3 | 2019 |

Approximating partition functions in constant time V Jain, F Koehler, E Mossel arXiv preprint arXiv:1711.01655, 2017 | 3 | 2017 |

Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation V Jain, F Koehler, J Liu, E Mossel arXiv preprint arXiv:1905.10031, 2019 | 2 | 2019 |

Learning some popular Gaussian graphical models without condition number bounds J Kelner, F Koehler, R Meka, A Moitra arXiv preprint arXiv:1905.01282, 2019 | 2 | 2019 |

The vertex sample complexity of free energy is polynomial V Jain, F Koehler, E Mossel arXiv preprint arXiv:1802.06129, 2018 | 2 | 2018 |

A Spectral Condition for Spectral Gap: Fast Mixing in High-Temperature Ising Models R Eldan, F Koehler, O Zeitouni arXiv preprint arXiv:2007.08200, 2020 | 1 | 2020 |

From Boltzmann Machines to Neural Networks and Back Again S Goel, A Klivans, F Koehler arXiv preprint arXiv:2007.12815, 2020 | | 2020 |

A Note on Minimax Learning of Tree Models F Koehler | | 2020 |

Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability S Chen, F Koehler, A Moitra, M Yau arXiv preprint arXiv:2006.04787, 2020 | | 2020 |

A Phase Transition in Arrow's Theorem F Koehler, E Mossel arXiv preprint arXiv:2004.12580, 2020 | | 2020 |

Busy Time Scheduling on a Bounded Number of Machines (Extended Abstract)⋆ F Koehler, S Khuller | | |