Kristjan H. Greenewald

99 papers A* 26A 4B 4Journal 60Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Library of LLM Intrinsics for Retrieval-Augmented Generation. CoRR Marina Danilevsky, Kristjan H. Greenewald, R. Chulaka Gunasekara, Maeda F. Hanafi, Lihong He, Yannis Katsis, Krishnateja Killamsetty, Yatin Nandwani, Lucian Popa, Dinesh Raghu, Frederick Reiss, Vraj Shah, Khoi-Nguyen Tran, Huaiyu Zhu, Luis A. Lastras
2025	J	`jnl`	Activated LoRA: Fine-tuned LLMs for Intrinsics. CoRR Kristjan H. Greenewald, Luis A. Lastras, Thomas Parnell, Vraj Shah, Lucian Popa, Giulio Zizzo, R. Chulaka Gunasekara, Ambrish Rawat, David Cox
2025	A*	`conf`	Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. ICML Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2025	J	`jnl`	Efficient Multi-Adapter LLM Serving via Cross-Model KV-Cache Reuse with Activated LoRA. CoRR Allison Li, Kristjan H. Greenewald, Thomas Parnell, Navid Azizan
2025	J	`jnl`	Entropic Causal Inference: Graph Identifiability. CoRR Spencer Compton, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu
2025	J	`jnl`	Know What You Don't Know: Uncertainty Calibration of Process Reward Models. CoRR Young-Jin Park, Kristjan H. Greenewald, Kaveh Alim, Hao Wang, Navid Azizan
2025	A*	`conf`	Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior. ICLR Anming Gu, Edward Chien, Kristjan H. Greenewald
2025	J	`jnl`	Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics. CoRR Anming Gu, Edward Chien, Kristjan H. Greenewald
2025	J	`jnl`	Revisiting Group Relative Policy Optimization: Insights into On-Policy and Off-Policy Training. CoRR Youssef Mroueh, Nicolas Dupuis, Brian Belgodere, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross, Jesus Rios
2025	J	`jnl`	Verify when Uncertain: Beyond Self-Consistency in Black Box Hallucination Detection. CoRR Yihao Xue, Kristjan H. Greenewald, Youssef Mroueh, Baharan Mirzasoleiman
2024	A*	`conf`	Asymmetry in Low-Rank Adapters of Foundation Models. ICML Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
2024	J	`jnl`	Asymmetry in Low-Rank Adapters of Foundation Models. CoRR Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
2024	J	`jnl`	Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. CoRR Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2024	A*	`conf`	Distributional Preference Alignment of LLMs via Optimal Transport. NeurIPS Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jarret Ross
2024	J	`jnl`	Distributional Preference Alignment of LLMs via Optimal Transport. CoRR Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross
2024	J	`jnl`	Domain Adaptable Prescriptive AI Agent for Enterprise. CoRR Piero Orderique, Wei Sun, Kristjan H. Greenewald
2024	A*	`conf`	Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking. NeurIPS Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Youssef Mroueh
2024	J	`jnl`	Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking. CoRR Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Youssef Mroueh
2024	J	`jnl`	Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior. CoRR Anming Gu, Edward Chien, Kristjan H. Greenewald
2024	J	`jnl`	PresAIse, A Prescriptive AI Solution for Enterprises. CoRR Wei Sun, Scott McFaddin, Linh Ha Tran, Shivaram Subramanian, Kristjan H. Greenewald, Yeshi Tenzin, Zack Xue, Youssef Drissi, Markus Ettl
2024	J	`jnl`	PresAIse, a prescriptive AI solution for enterprise. INFOR Inf. Syst. Oper. Res. Wei Sun, Scott McFaddin, Linh Ha Tran, Shivaram Subramanian, Kristjan H. Greenewald, Yeshi Tenzin, Zack Xue, Youssef Drissi, Markus Ettl
2024	A*	`conf`	Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training. NeurIPS Kristjan H. Greenewald, Yuancheng Yu, Hao Wang, Kai Xu
2024	J	`jnl`	Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training. CoRR Kristjan H. Greenewald, Yuancheng Yu, Hao Wang, Kai Xu
2024	A*	`conf`	Risk Aware Benchmarking of Large Language Models. ICML Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jarret Ross
2024	A*	`conf`	Score Distillation via Reparametrized DDIM. NeurIPS Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin M. Solomon
2024	J	`jnl`	Score Distillation via Reparametrized DDIM. CoRR Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Campagnolo Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin Solomon
2024	B	`conf`	Sharper Rates of Convergence for the Tensor Graphical Lasso Estimator. ISIT Shuheng Zhou, Kristjan H. Greenewald
2024	A*	`conf`	Slicing Mutual Information Generalization Bounds for Neural Networks. ICML Kimia Nadjahi, Kristjan H. Greenewald, Rickard Brüel Gabrielsson, Justin Solomon
2024	J	`jnl`	Slicing Mutual Information Generalization Bounds for Neural Networks. CoRR Kimia Nadjahi, Kristjan H. Greenewald, Rickard Brüel Gabrielsson, Justin Solomon
2024	J	`jnl`	Synthetic Census Data Generation via Multidimensional Multiset Sum. CoRR Cynthia Dwork, Kristjan H. Greenewald, Manish Raghavan
2024	A*	`conf`	Thermometer: Towards Universal Calibration for Large Language Models. ICML Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
2024	J	`jnl`	Thermometer: Towards Universal Calibration for Large Language Models. CoRR Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
2023	B	`conf`	High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction. ISIT Kristjan H. Greenewald, Brian Kingsbury, Yuancheng Yu
2023	J	`jnl`	High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction. CoRR Kristjan H. Greenewald, Brian Kingsbury, Yuancheng Yu
2023	A*	`conf`	Identifiability Guarantees for Causal Disentanglement from Soft Interventions. NeurIPS Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
2023	J	`jnl`	Identifiability Guarantees for Causal Disentanglement from Soft Interventions. CoRR Jiaqi Zhang, Chandler Squires, Kristjan H. Greenewald, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
2023	A*	`conf`	Learning Proximal Operators to Discover Multiple Optima. ICLR Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2023	A*	`conf`	Max-Sliced Mutual Information. NeurIPS Dor Tsur, Ziv Goldfeld, Kristjan H. Greenewald
2023	J	`jnl`	Max-Sliced Mutual Information. CoRR Dor Tsur, Ziv Goldfeld, Kristjan H. Greenewald
2023	A	`conf`	Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. AISTATS Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu
2023	J	`jnl`	Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. CoRR Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu
2023	A*	`conf`	Post-processing Private Synthetic Data for Improving Utility on Selected Measures. NeurIPS Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan H. Greenewald, Akash Srivastava
2023	J	`jnl`	Post-processing Private Synthetic Data for Improving Utility on Selected Measures. CoRR Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan H. Greenewald, Akash Srivastava
2023	J	`jnl`	Risk Assessment and Statistical Significance in the Age of Foundation Models. CoRR Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jerret Ross
2023	J	`jnl`	k-Mixup Regularization for Deep Learning via Optimal Transport. Trans. Mach. Learn. Res. Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
2022	A*	`conf`	$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension. NeurIPS Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves
2022	J	`jnl`	$k$-Variance: A Clustered Notion of Variance. SIAM J. Math. Data Sci. Justin Solomon, Kristjan H. Greenewald, Haikady N. Nagaraja
2022	A*	`conf`	Entropic Causal Inference: Graph Identifiability. ICML Spencer Compton, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu
2022	J	`jnl`	Learning Proximal Operators to Discover Multiple Optima. CoRR Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2022	A*	`conf`	Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. ICML Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin M. Solomon
2022	J	`jnl`	Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. CoRR Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin Solomon
2022	J	`jnl`	Outlier-Robust Group Inference via Gradient Space Clustering. CoRR Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
2022	J	`jnl`	k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension. CoRR Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves
2021	J	`jnl`	Entropic Causal Inference: Identifiability and Finite Sample Results. CoRR Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz
2021	A	`conf`	High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. AISTATS Kristjan H. Greenewald, Karthikeyan Shanmugam, Dmitriy A. Katz
2021	J	`jnl`	Improving Approximate Optimal Transport Distances using Quantization. CoRR Gaspard Beugnot, Aude Genevay, Kristjan H. Greenewald, Justin Solomon
2021	A	`conf`	Improving approximate optimal transport distances using quantization. UAI Gaspard Beugnot, Aude Genevay, Kristjan H. Greenewald, Justin Solomon
2021	A*	`conf`	Measuring Generalization with Optimal Transport. NeurIPS Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka
2021	J	`jnl`	Measuring Generalization with Optimal Transport. CoRR Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka
2021	A*	`conf`	Sliced Mutual Information: A Scalable Measure of Statistical Dependence. NeurIPS Ziv Goldfeld, Kristjan H. Greenewald
2021	J	`jnl`	Sliced Mutual Information: A Scalable Measure of Statistical Dependence. CoRR Ziv Goldfeld, Kristjan H. Greenewald
2021	J	`jnl`	k-Mixup Regularization for Deep Learning via Optimal Transport. CoRR Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
2020	J	`jnl`	Active Structure Learning of Causal DAGs via Directed Clique Tree. CoRR Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
2020	A*	`conf`	Active Structure Learning of Causal DAGs via Directed Clique Trees. NeurIPS Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
2020	A*	`conf`	Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance. NeurIPS Ziv Goldfeld, Kristjan H. Greenewald, Kengo Kato
2020	J	`jnl`	Convergence of Smoothed Empirical Measures With Applications to Entropy Estimation. IEEE Trans. Inf. Theory Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Niles-Weed, Yury Polyanskiy
2020	A*	`conf`	Entropic Causal Inference: Identifiability and Finite Sample Results. NeurIPS Spencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz
2020	A	`conf`	Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency. AISTATS Ziv Goldfeld, Kristjan H. Greenewald
2020	J	`jnl`	High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. CoRR Kristjan H. Greenewald, Dmitriy A. Katz-Rogozhnikov, Karthik Shanmugam
2020	J	`jnl`	Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy
2020	J	`jnl`	The Computational Limits of Deep Learning. CoRR Neil C. Thompson, Kristjan H. Greenewald, Keeheon Lee, Gabriel F. Manso
2020	J	`jnl`	k-Variance: A Clustered Notion of Variance. CoRR Justin Solomon, Kristjan H. Greenewald, Haikady N. Nagaraja
2019	A*	`conf`	Bayesian Nonparametric Federated Learning of Neural Networks. ICML Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
2019	J	`jnl`	Bayesian Nonparametric Federated Learning of Neural Networks. CoRR Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
2019	J	`jnl`	BreGMN: scaled-Bregman Generative Modeling Networks. CoRR Akash Srivastava, Kristjan H. Greenewald, Farzaneh Mirzazadeh
2019	J	`jnl`	Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation. CoRR Ziv Goldfeld, Kristjan H. Greenewald, Yury Polyanskiy, Jonathan Weed
2019	A*	`conf`	Estimating Information Flow in Deep Neural Networks. ICML Ziv Goldfeld, Ewout van den Berg, Kristjan H. Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy
2019	B	`conf`	Optimality of the Plug-in Estimator for Differential Entropy Estimation under Gaussian Convolutions. ISIT Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Weed, Yury Polyanskiy
2019	J	`jnl`	Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity. CoRR Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy
2019	A*	`conf`	Sample Efficient Active Learning of Causal Trees. NeurIPS Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler
2019	A*	`conf`	Statistical Model Aggregation via Parameter Matching. NeurIPS Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
2019	J	`jnl`	Statistical Model Aggregation via Parameter Matching. CoRR Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
2018	J	`jnl`	Ensemble Estimation of Information Divergence Entropy Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
2018	J	`jnl`	Estimating Information Flow in Neural Networks. CoRR Ziv Goldfeld, Ewout van den Berg, Kristjan H. Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy
2017	—	`conf`	Action Centered Contextual Bandits. NIPS Kristjan H. Greenewald, Ambuj Tewari, Susan A. Murphy, Predrag V. Klasnja
2017	J	`jnl`	Similarity Function Tracking Using Pairwise Comparisons. IEEE Trans. Signal Process. Kristjan H. Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III
2017	J	`jnl`	Similarity Function Tracking using Pairwise Comparisons. CoRR Kristjan H. Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III
2017	—	`conf`	Time-dependent spatially varying graphical models, with application to brain fMRI data analysis. NIPS Kristjan H. Greenewald, Seyoung Park, Shuheng Zhou, Alexander Giessing
2016	J	`jnl`	Distance Metric Tracking. CoRR Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III
2016	J	`jnl`	Dynamic Metric Learning from Pairwise Comparisons. CoRR Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III
2016	—	`conf`	Dynamic metric learning from pairwise comparisons. Allerton Kristjan H. Greenewald, Stephen Kelley, Alfred O. Hero III
2016	J	`jnl`	Improving Convergence of Divergence Functional Ensemble Estimators. CoRR Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
2016	B	`conf`	Improving convergence of divergence functional ensemble estimators. ISIT Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
2016	J	`jnl`	Robust SAR STAP via Kronecker Decomposition. CoRR Kristjan H. Greenewald, Edmund G. Zelnio, Alfred O. Hero III
2016	J	`jnl`	Robust SAR STAP via Kronecker decomposition. IEEE Trans. Aerosp. Electron. Syst. Kristjan H. Greenewald, Edmund G. Zelnio, Alfred O. Hero III
2015	J	`jnl`	Robust Kronecker Product PCA for Spatio-Temporal Covariance Estimation. IEEE Trans. Signal Process. Kristjan H. Greenewald, Alfred O. Hero III
2014	J	`jnl`	Kronecker PCA Based Spatio-Temporal Modeling of Video for Dismount Classification. CoRR Kristjan H. Greenewald, Alfred O. Hero III
2014	—	`conf`	Regularized block Toeplitz covariance matrix estimation via Kronecker product expansions. SSP Kristjan H. Greenewald, Alfred O. Hero III
2013	—	`conf`	Kronecker sum decompositions of space-time data. CAMSAP Kristjan H. Greenewald, Theodoros Tsiligkaridis, Alfred O. Hero III