Kristjan H. Greenewald

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 73

Top Topics

Mutual Information

Pairwise Comparisons

Gaussian Convolution

Top Venues

Publications

Piero Orderique, Wei Sun, Kristjan H. Greenewald
Domain Adaptable Prescriptive AI Agent for Enterprise. CoRR (2024)
Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Youssef Mroueh
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking. CoRR (2024)
Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
Asymmetry in Low-Rank Adapters of Foundation Models. CoRR (2024)
Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross
Distributional Preference Alignment of LLMs via Optimal Transport. CoRR (2024)
Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Campagnolo Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin Solomon
Score Distillation via Reparametrized DDIM. CoRR (2024)
Cynthia Dwork, Kristjan H. Greenewald, Manish Raghavan
Synthetic Census Data Generation via Multidimensional Multiset Sum. CoRR (2024)
Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
Thermometer: Towards Universal Calibration for Large Language Models. CoRR (2024)
Anming Gu, Edward Chien, Kristjan H. Greenewald
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior. CoRR (2024)
Kimia Nadjahi, Kristjan H. Greenewald, Rickard Brüel Gabrielsson, Justin Solomon
Slicing Mutual Information Generalization Bounds for Neural Networks. CoRR (2024)
Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. CoRR (2024)
Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. AISTATS (2023)
Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
k-Mixup Regularization for Deep Learning via Optimal Transport. Trans. Mach. Learn. Res. 2023 (2023)
Dor Tsur, Ziv Goldfeld, Kristjan H. Greenewald
Max-Sliced Mutual Information. CoRR (2023)
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)
Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. NeurIPS (2023)
Kristjan H. Greenewald, Brian Kingsbury, Yuancheng Yu
High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction. CoRR (2023)
Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan H. Greenewald, Akash Srivastava
Post-processing Private Synthetic Data for Improving Utility on Selected Measures. CoRR (2023)
Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. CoRR (2023)
Dor Tsur, Ziv Goldfeld, Kristjan H. Greenewald
Max-Sliced Mutual Information. NeurIPS (2023)
Kristjan H. Greenewald, Brian Kingsbury, Yuancheng Yu
High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction. ISIT (2023)
Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan H. Greenewald, Akash Srivastava
Post-processing Private Synthetic Data for Improving Utility on Selected Measures. NeurIPS (2023)
Jiaqi Zhang, Chandler Squires, Kristjan H. Greenewald, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. CoRR (2023)
Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jerret Ross
Risk Assessment and Statistical Significance in the Age of Foundation Models. CoRR (2023)
Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
Learning Proximal Operators to Discover Multiple Optima. CoRR (2022)
Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin Solomon
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. CoRR (2022)
Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
Outlier-Robust Group Inference via Gradient Space Clustering. CoRR (2022)
Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves
$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension. NeurIPS (2022)
Spencer Compton, Kristjan H. Greenewald, Dmitriy A. Katz, Murat Kocaoglu
Entropic Causal Inference: Graph Identifiability. ICML (2022)
Justin Solomon, Kristjan H. Greenewald, Haikady N. Nagaraja
$k$-Variance: A Clustered Notion of Variance. SIAM J. Math. Data Sci. 4 (3) (2022)
Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin M. Solomon
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. ICML (2022)
Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves
k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension. CoRR (2022)
Gaspard Beugnot, Aude Genevay, Kristjan H. Greenewald, Justin Solomon
Improving Approximate Optimal Transport Distances using Quantization. CoRR (2021)
Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka
Measuring Generalization with Optimal Transport. NeurIPS (2021)
Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka
Measuring Generalization with Optimal Transport. CoRR (2021)
Gaspard Beugnot, Aude Genevay, Kristjan H. Greenewald, Justin Solomon
Improving approximate optimal transport distances using quantization. UAI (2021)
Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
k-Mixup Regularization for Deep Learning via Optimal Transport. CoRR (2021)
Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz
Entropic Causal Inference: Identifiability and Finite Sample Results. CoRR (2021)
Kristjan H. Greenewald, Karthikeyan Shanmugam, Dmitriy A. Katz-Rogozhnikov
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. AISTATS (2021)
Ziv Goldfeld, Kristjan H. Greenewald
Sliced Mutual Information: A Scalable Measure of Statistical Dependence. NeurIPS (2021)
Ziv Goldfeld, Kristjan H. Greenewald
Sliced Mutual Information: A Scalable Measure of Statistical Dependence. CoRR (2021)
Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz
Entropic Causal Inference: Identifiability and Finite Sample Results. NeurIPS (2020)
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) (2020)
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)
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) (2020)
Neil C. Thompson, Kristjan H. Greenewald, Keeheon Lee, Gabriel F. Manso
The Computational Limits of Deep Learning. CoRR (2020)
Ziv Goldfeld, Kristjan H. Greenewald
Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency. AISTATS (2020)
Justin Solomon, Kristjan H. Greenewald, Haikady N. Nagaraja
k-Variance: A Clustered Notion of Variance. CoRR (2020)
Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
Active Structure Learning of Causal DAGs via Directed Clique Tree. CoRR (2020)
Kristjan H. Greenewald, Dmitriy A. Katz-Rogozhnikov, Karthik Shanmugam
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. CoRR (2020)
Ziv Goldfeld, Kristjan H. Greenewald, Kengo Kato
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance. NeurIPS (2020)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
Bayesian Nonparametric Federated Learning of Neural Networks. ICML (2019)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
Statistical Model Aggregation via Parameter Matching. CoRR (2019)
Akash Srivastava, Kristjan H. Greenewald, Farzaneh Mirzazadeh
BreGMN: scaled-Bregman Generative Modeling Networks. CoRR (2019)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
Statistical Model Aggregation via Parameter Matching. NeurIPS (2019)
Ziv Goldfeld, Kristjan H. Greenewald, Yury Polyanskiy, Jonathan Weed
Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation. CoRR (2019)
Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity. CoRR (2019)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
Bayesian Nonparametric Federated Learning of Neural Networks. CoRR (2019)
Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Weed, Yury Polyanskiy
Optimality of the Plug-in Estimator for Differential Entropy Estimation under Gaussian Convolutions. ISIT (2019)
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)
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)
Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
. Entropy 20 (8) (2018)
Ziv Goldfeld, Ewout van den Berg, Kristjan H. Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy
Estimating Information Flow in Neural Networks. CoRR (2018)
Kristjan H. Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III
Similarity Function Tracking Using Pairwise Comparisons. IEEE Trans. Signal Process. 65 (21) (2017)
Kristjan H. Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III
Similarity Function Tracking using Pairwise Comparisons. CoRR (2017)
Kristjan H. Greenewald, Ambuj Tewari, Susan A. Murphy, Predrag V. Klasnja
Action Centered Contextual Bandits. NIPS (2017)
Kristjan H. Greenewald, Seyoung Park, Shuheng Zhou, Alexander Giessing
Time-dependent spatially varying graphical models, with application to brain fMRI data analysis. NIPS (2017)
Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III
Dynamic metric learning from pairwise comparisons. Allerton (2016)
Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III
Dynamic Metric Learning from Pairwise Comparisons. CoRR (2016)
Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
Improving Convergence of Divergence Functional Ensemble Estimators. CoRR (2016)
Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
Improving convergence of divergence functional ensemble estimators. ISIT (2016)
Kristjan H. Greenewald, Edmund G. Zelnio, Alfred O. Hero III
Robust SAR STAP via Kronecker Decomposition. CoRR (2016)
Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III
Distance Metric Tracking. CoRR (2016)
Kristjan H. Greenewald, Edmund G. Zelnio, Alfred O. Hero III
Robust SAR STAP via Kronecker decomposition. IEEE Trans. Aerosp. Electron. Syst. 52 (6) (2016)
Kristjan H. Greenewald, Alfred O. Hero III
Robust Kronecker Product PCA for Spatio-Temporal Covariance Estimation. IEEE Trans. Signal Process. 63 (23) (2015)
Kristjan H. Greenewald, Alfred O. Hero III
Kronecker PCA Based Spatio-Temporal Modeling of Video for Dismount Classification. CoRR (2014)
Kristjan H. Greenewald, Alfred O. Hero III
Regularized block Toeplitz covariance matrix estimation via Kronecker product expansions. SSP (2014)
Kristjan H. Greenewald, Theodoros Tsiligkaridis, Alfred O. Hero III
Kronecker sum decompositions of space-time data. CAMSAP (2013)