Entropic causal inference: Identifiability and finite sample results S Compton, M Kocaoglu, K Greenewald, D Katz Advances in Neural Information Processing Systems 33, 14772-14782, 2020 | 17 | 2020 |
Entropic causal inference: Graph identifiability S Compton, K Greenewald, DA Katz, M Kocaoglu International Conference on Machine Learning, 4311-4343, 2022 | 14 | 2022 |
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier S Compton, D Katz, B Qi, K Greenewald, M Kocaoglu International Conference on Artificial Intelligence and Statistics, 10445-10469, 2023 | 7 | 2023 |
New partitioning techniques and faster algorithms for approximate interval scheduling S Compton, S Mitrović, R Rubinfeld arXiv preprint arXiv:2012.15002, 2020 | 7 | 2020 |
Edge matching with inequalities, triangles, unknown shape, and two players J Bosboom, C Chen, L Chung, S Compton, M Coulombe, ED Demaine, ... Journal of Information Processing 28, 987-1007, 2020 | 7 | 2020 |
A Tighter Approximation Guarantee for Greedy Minimum Entropy Coupling S Compton 2022 IEEE International Symposium on Information Theory (ISIT), 168-173, 2022 | 5 | 2022 |
Embedding Probability Distributions into Low Dimensional : Tree Ising Models via Truncated Metrics M Charikar, S Compton, C Pabbaraju arXiv preprint arXiv:2312.02435, 2023 | | 2023 |
Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances S Compton, G Valiant arXiv preprint arXiv:2312.02417, 2023 | | 2023 |