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ORCIDKristjan H. Greenewald
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2020 – today
- 2023
[c25]Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu:
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. AISTATS 2023: 10445-10469- [c24]Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon:
Learning Proximal Operators to Discover Multiple Optima. ICLR 2023 - [c23]Kristjan H. Greenewald, Brian Kingsbury, Yuancheng Yu:
High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction. ISIT 2023: 2613-2618 - [i29]Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu:
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. CoRR abs/2302.11838 (2023) - [i28]Kristjan H. Greenewald, Brian Kingsbury, Yuancheng Yu:
High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction. CoRR abs/2305.04712 (2023) - [i27]Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan H. Greenewald, Akash Srivastava:
Post-processing Private Synthetic Data for Improving Utility on Selected Measures. CoRR abs/2305.15538 (2023) - [i26]Jiaqi Zhang, Chandler Squires, Kristjan H. Greenewald, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. CoRR abs/2307.06250 (2023) - 2022
- [j7]Justin Solomon
, Kristjan H. Greenewald, Haikady N. Nagaraja:
$k$-Variance: A Clustered Notion of Variance. SIAM J. Math. Data Sci. 4(3): 957-978 (2022) - [c22]Spencer Compton, Kristjan H. Greenewald, Dmitriy A. Katz, Murat Kocaoglu:
Entropic Causal Inference: Graph Identifiability. ICML 2022: 4311-4343 - [c21]Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin M. Solomon:
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. ICML 2022: 20106-20124 - [c20]Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves:
$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension. NeurIPS 2022 - [i25]Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon:
Learning Proximal Operators to Discover Multiple Optima. CoRR abs/2201.11945 (2022) - [i24]Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin Solomon:
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. CoRR abs/2202.01671 (2022) - [i23]Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves:
k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension. CoRR abs/2206.08526 (2022) - [i22]Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin:
Outlier-Robust Group Inference via Gradient Space Clustering. CoRR abs/2210.06759 (2022) - 2021
- [c19]Kristjan H. Greenewald, Karthikeyan Shanmugam, Dmitriy A. Katz-Rogozhnikov:
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. AISTATS 2021: 2224-2232 - [c18]Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka:
Measuring Generalization with Optimal Transport. NeurIPS 2021: 8294-8306 - [c17]Ziv Goldfeld, Kristjan H. Greenewald:
Sliced Mutual Information: A Scalable Measure of Statistical Dependence. NeurIPS 2021: 17567-17578 - [c16]Gaspard Beugnot, Aude Genevay, Kristjan H. Greenewald, Justin Solomon:
Improving approximate optimal transport distances using quantization. UAI 2021: 290-300 - [i21]Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz:
Entropic Causal Inference: Identifiability and Finite Sample Results. CoRR abs/2101.03501 (2021) - [i20]Gaspard Beugnot, Aude Genevay, Kristjan H. Greenewald, Justin Solomon:
Improving Approximate Optimal Transport Distances using Quantization. CoRR abs/2102.12731 (2021) - [i19]Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien:
k-Mixup Regularization for Deep Learning via Optimal Transport. CoRR abs/2106.02933 (2021) - [i18]Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka:
Measuring Generalization with Optimal Transport. CoRR abs/2106.03314 (2021) - [i17]Ziv Goldfeld, Kristjan H. Greenewald:
Sliced Mutual Information: A Scalable Measure of Statistical Dependence. CoRR abs/2110.05279 (2021) - 2020
- [j6]Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy:
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(1): 18:1-18:22 (2020) - [j5]Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Niles-Weed, Yury Polyanskiy:
Convergence of Smoothed Empirical Measures With Applications to Entropy Estimation. IEEE Trans. Inf. Theory 66(7): 4368-4391 (2020) - [c15]Ziv Goldfeld, Kristjan H. Greenewald:
Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency. AISTATS 2020: 3327-3337 - [c14]Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz:
Entropic Causal Inference: Identifiability and Finite Sample Results. NeurIPS 2020 - [c13]Ziv Goldfeld, Kristjan H. Greenewald, Kengo Kato:
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance. NeurIPS 2020 - [c12]Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam:
Active Structure Learning of Causal DAGs via Directed Clique Trees. NeurIPS 2020 - [i16]Neil C. Thompson, Kristjan H. Greenewald, Keeheon Lee, Gabriel F. Manso:
The Computational Limits of Deep Learning. CoRR abs/2007.05558 (2020) - [i15]Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam:
Active Structure Learning of Causal DAGs via Directed Clique Tree. CoRR abs/2011.00641 (2020) - [i14]Kristjan H. Greenewald, Dmitriy A. Katz-Rogozhnikov, Karthik Shanmugam:
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. CoRR abs/2011.01979 (2020) - [i13]Justin Solomon, Kristjan H. Greenewald, Haikady N. Nagaraja:
k-Variance: A Clustered Notion of Variance. CoRR abs/2012.06958 (2020)
2010 – 2019
- 2019
- [c11]Ziv Goldfeld, Ewout van den Berg, Kristjan H. Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy:
Estimating Information Flow in Deep Neural Networks. ICML 2019: 2299-2308 - [c10]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni:
Bayesian Nonparametric Federated Learning of Neural Networks. ICML 2019: 7252-7261 - [c9]Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Weed, Yury Polyanskiy:
Optimality of the Plug-in Estimator for Differential Entropy Estimation under Gaussian Convolutions. ISIT 2019: 892-896 - [c8]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang:
Statistical Model Aggregation via Parameter Matching. NeurIPS 2019: 10954-10964 - [c7]Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler:
Sample Efficient Active Learning of Causal Trees. NeurIPS 2019: 14279-14289 - [i12]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni:
Bayesian Nonparametric Federated Learning of Neural Networks. CoRR abs/1905.12022 (2019) - [i11]Ziv Goldfeld, Kristjan H. Greenewald, Yury Polyanskiy, Jonathan Weed:
Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation. CoRR abs/1905.13576 (2019) - [i10]Akash Srivastava, Kristjan H. Greenewald, Farzaneh Mirzazadeh:
BreGMN: scaled-Bregman Generative Modeling Networks. CoRR abs/1906.00313 (2019) - [i9]Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy:
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity. CoRR abs/1909.03539 (2019) - [i8]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang:
Statistical Model Aggregation via Parameter Matching. CoRR abs/1911.00218 (2019) - 2018
- [j4]Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III:
Ensemble Estimation of Information Divergence †. Entropy 20(8): 560 (2018) - [i7]Ziv Goldfeld, Ewout van den Berg, Kristjan H. Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy:
Estimating Information Flow in Neural Networks. CoRR abs/1810.05728 (2018) - 2017
- [j3]Kristjan H. Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III:
Similarity Function Tracking Using Pairwise Comparisons. IEEE Trans. Signal Process. 65(21): 5635-5648 (2017) - [c6]Kristjan H. Greenewald, Seyoung Park, Shuheng Zhou, Alexander Giessing:
Time-dependent spatially varying graphical models, with application to brain fMRI data analysis. NIPS 2017: 5832-5840 - [c5]Kristjan H. Greenewald, Ambuj Tewari, Susan A. Murphy, Predrag V. Klasnja:
Action Centered Contextual Bandits. NIPS 2017: 5977-5985 - [i6]Kristjan H. Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III:
Similarity Function Tracking using Pairwise Comparisons. CoRR abs/1701.02804 (2017) - 2016
- [j2]Kristjan H. Greenewald, Edmund G. Zelnio, Alfred O. Hero III:
Robust SAR STAP via Kronecker decomposition. IEEE Trans. Aerosp. Electron. Syst. 52(6): 2612-2625 (2016) - [c4]Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III:
Dynamic metric learning from pairwise comparisons. Allerton 2016: 1327-1334 - [c3]Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III:
Improving convergence of divergence functional ensemble estimators. ISIT 2016: 1133-1137 - [i5]Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III:
Improving Convergence of Divergence Functional Ensemble Estimators. CoRR abs/1601.06884 (2016) - [i4]Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III:
Distance Metric Tracking. CoRR abs/1603.03678 (2016) - [i3]Kristjan H. Greenewald, Edmund G. Zelnio, Alfred O. Hero III:
Robust SAR STAP via Kronecker Decomposition. CoRR abs/1605.01790 (2016) - [i2]Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III:
Dynamic Metric Learning from Pairwise Comparisons. CoRR abs/1610.03090 (2016) - 2015
- [j1]Kristjan H. Greenewald, Alfred O. Hero III:
Robust Kronecker Product PCA for Spatio-Temporal Covariance Estimation. IEEE Trans. Signal Process. 63(23): 6368-6378 (2015) - 2014
- [c2]Kristjan H. Greenewald, Alfred O. Hero III:
Regularized block Toeplitz covariance matrix estimation via Kronecker product expansions. SSP 2014: 9-12 - [i1]Kristjan H. Greenewald, Alfred O. Hero III:
Kronecker PCA Based Spatio-Temporal Modeling of Video for Dismount Classification. CoRR abs/1405.4574 (2014) - 2013
- [c1]Kristjan H. Greenewald, Theodoros Tsiligkaridis, Alfred O. Hero III:
Kronecker sum decompositions of space-time data. CAMSAP 2013: 65-68
Coauthor Index
aka: Justin M. Solomon
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last updated on 2023-09-28 03:13 CEST by the dblp team
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