Kristjan H. Greenewald

According to our database, Kristjan H. Greenewald authored at least 59 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training.

Kristjan H. Greenewald, Yuancheng Yu, Hao Wang, Kai Xu

CoRR, 2024

Domain Adaptable Prescriptive AI Agent for Enterprise.

Piero Orderique, Wei Sun, Kristjan H. Greenewald

CoRR, 2024

Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead.

Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon

CoRR, 2024

Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior.

Anming Gu, Edward Chien, Kristjan H. Greenewald

CoRR, 2024

Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking.

Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Youssef Mroueh

CoRR, 2024

Distributional Preference Alignment of LLMs via Optimal Transport.

Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross

CoRR, 2024

Score Distillation via Reparametrized DDIM.

Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Campagnolo Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin Solomon

CoRR, 2024

Synthetic Census Data Generation via Multidimensional Multiset Sum.

Cynthia Dwork, Kristjan H. Greenewald, Manish Raghavan

CoRR, 2024

PresAIse, A Prescriptive AI Solution for Enterprises.

Wei Sun, Scott McFaddin, Linh Ha Tran, Shivaram Subramanian, Kristjan H. Greenewald, Yeshi Tenzin, Zack Xue, Youssef Drissi, Markus Ettl

CoRR, 2024

Sharper Rates of Convergence for the Tensor Graphical Lasso Estimator.

Shuheng Zhou, Kristjan H. Greenewald

Proceedings of the IEEE International Symposium on Information Theory, 2024

Asymmetry in Low-Rank Adapters of Foundation Models.

Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Thermometer: Towards Universal Calibration for Large Language Models.

Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Risk Aware Benchmarking of Large Language Models.

Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jarret Ross

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Slicing Mutual Information Generalization Bounds for Neural Networks.

Kimia Nadjahi, Kristjan H. Greenewald, Rickard Brüel Gabrielsson, Justin Solomon

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

k-Mixup Regularization for Deep Learning via Optimal Transport.

Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien

Trans. Mach. Learn. Res., 2023

Risk Assessment and Statistical Significance in the Age of Foundation Models.

Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jerret Ross

CoRR, 2023

Identifiability Guarantees for Causal Disentanglement from Soft Interventions.

Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Post-processing Private Synthetic Data for Improving Utility on Selected Measures.

Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan H. Greenewald, Akash Srivastava

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Max-Sliced Mutual Information.

Dor Tsur, Ziv Goldfeld, Kristjan H. Greenewald

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction.

Kristjan H. Greenewald, Brian Kingsbury, Yuancheng Yu

Proceedings of the IEEE International Symposium on Information Theory, 2023

Learning Proximal Operators to Discover Multiple Optima.

Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier.

Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

$k$-Variance: A Clustered Notion of Variance.

Justin Solomon, Kristjan H. Greenewald, Haikady N. Nagaraja

SIAM J. Math. Data Sci., 2022

Outlier-Robust Group Inference via Gradient Space Clustering.

Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin

CoRR, 2022

$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension.

Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets.

Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin M. Solomon

Proceedings of the International Conference on Machine Learning, 2022

Entropic Causal Inference: Graph Identifiability.

Spencer Compton, Kristjan H. Greenewald, Dmitriy A. Katz, Murat Kocaoglu

Proceedings of the International Conference on Machine Learning, 2022

2021

Improving approximate optimal transport distances using quantization.

Gaspard Beugnot, Aude Genevay, Kristjan H. Greenewald, Justin Solomon

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Sliced Mutual Information: A Scalable Measure of Statistical Dependence.

Ziv Goldfeld, Kristjan H. Greenewald

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Measuring Generalization with Optimal Transport.

Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation.

Kristjan H. Greenewald, Karthikeyan Shanmugam, Dmitriy A. Katz-Rogozhnikov

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Convergence of Smoothed Empirical Measures With Applications to Entropy Estimation.

Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Niles-Weed, Yury Polyanskiy

IEEE Trans. Inf. Theory, 2020

Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity.

Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020

High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation.

Kristjan H. Greenewald, Dmitriy A. Katz-Rogozhnikov, Karthik Shanmugam

CoRR, 2020

Active Structure Learning of Causal DAGs via Directed Clique Tree.

Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

CoRR, 2020

The Computational Limits of Deep Learning.

Neil C. Thompson, Kristjan H. Greenewald, Keeheon Lee, Gabriel F. Manso

CoRR, 2020

Active Structure Learning of Causal DAGs via Directed Clique Trees.

Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance.

Ziv Goldfeld, Kristjan H. Greenewald, Kengo Kato

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Entropic Causal Inference: Identifiability and Finite Sample Results.

Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency.

Ziv Goldfeld, Kristjan H. Greenewald

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

BreGMN: scaled-Bregman Generative Modeling Networks.

Akash Srivastava, Kristjan H. Greenewald, Farzaneh Mirzazadeh

CoRR, 2019

Statistical Model Aggregation via Parameter Matching.

Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sample Efficient Active Learning of Causal Trees.

Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Optimality of the Plug-in Estimator for Differential Entropy Estimation under Gaussian Convolutions.

Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Weed, Yury Polyanskiy

Proceedings of the IEEE International Symposium on Information Theory, 2019

Bayesian Nonparametric Federated Learning of Neural Networks.

Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni

Proceedings of the 36th International Conference on Machine Learning, 2019

Estimating Information Flow in Deep Neural Networks.

Ziv Goldfeld, Ewout van den Berg, Kristjan H. Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Ensemble Estimation of Information Divergence ^†.

Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III

Entropy, 2018

Estimating Information Flow in Neural Networks.

Ziv Goldfeld, Ewout van den Berg, Kristjan H. Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy

CoRR, 2018

2017

Similarity Function Tracking Using Pairwise Comparisons.

Kristjan H. Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III

IEEE Trans. Signal Process., 2017

Action Centered Contextual Bandits.

Kristjan H. Greenewald, Ambuj Tewari, Susan A. Murphy, Predrag V. Klasnja

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Time-dependent spatially varying graphical models, with application to brain fMRI data analysis.

Kristjan H. Greenewald, Seyoung Park, Shuheng Zhou, Alexander Giessing

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Robust SAR STAP via Kronecker decomposition.

Kristjan H. Greenewald, Edmund G. Zelnio, Alfred O. Hero III

IEEE Trans. Aerosp. Electron. Syst., 2016

Distance Metric Tracking.

Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III

CoRR, 2016

Improving convergence of divergence functional ensemble estimators.

Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III

Proceedings of the IEEE International Symposium on Information Theory, 2016

Dynamic metric learning from pairwise comparisons.

Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015

Robust Kronecker Product PCA for Spatio-Temporal Covariance Estimation.

Kristjan H. Greenewald, Alfred O. Hero III

IEEE Trans. Signal Process., 2015

2014

Kronecker PCA Based Spatio-Temporal Modeling of Video for Dismount Classification.

Kristjan H. Greenewald, Alfred O. Hero III

CoRR, 2014

Regularized block Toeplitz covariance matrix estimation via Kronecker product expansions.

Kristjan H. Greenewald, Alfred O. Hero III

Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

2013

Kronecker sum decompositions of space-time data.

Kristjan H. Greenewald, Theodoros Tsiligkaridis, Alfred O. Hero III

Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013