ML Anthology

Greenewald, Kristjan

43 publications

NeurIPS 2025 Activated LoRA: Fine-Tuned LLMs for Intrinsics Kristjan Greenewald, Luis A. Lastras, Thomas Parnell, Vraj Shah, Lucian Popa, Giulio Zizzo, Chulaka Gunasekara, Ambrish Rawat, David Daniel Cox
ICML 2025 Compress Then Serve: Serving Thousands of LoRA Adapters with Little Overhead Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon
NeurIPS 2025 Know What You Don't Know: Uncertainty Calibration of Process Reward Models Young-Jin Park, Kristjan Greenewald, Kaveh Alim, Hao Wang, Navid Azizan
ICLR 2025 Partially Observed Trajectory Inference Using Optimal Transport and a Dynamics Prior Anming Gu, Edward Chien, Kristjan Greenewald
ICML 2024 Asymmetry in Low-Rank Adapters of Foundation Models Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez De Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
ICLRW 2024 Asymmetry in Low-Rank Adapters of Foundation Models Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
ICMLW 2024 Compress Then Serve: Serving Thousands of LoRA Adapters with Little Overhead Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon
NeurIPS 2024 Distributional Preference Alignment of LLMs via Optimal Transport Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan Greenewald, Jiri Navratil, Jarret Ross
ICMLW 2024 Distributional Preference Alignment of LLMs via Optimal Transport Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan Greenewald, Jiri Navratil, Jarret Ross
NeurIPS 2024 Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan Greenewald, Youssef Mroueh
NeurIPSW 2024 Neural Entropic Multimarginal Optimal Transport Dor Tsur, Ziv Goldfeld, Kristjan Greenewald, Haim H. Permuter
NeurIPSW 2024 Partially Observed Trajectory Inference Using Optimal Transport and a Dynamics Prior Anming Gu, Edward Chien, Kristjan Greenewald
NeurIPS 2024 Privacy Without Noisy Gradients: Slicing Mechanism for Generative Model Training Kristjan Greenewald, Yuancheng Yu, Hao Wang, Kai Xu
ICML 2024 Risk Aware Benchmarking of Large Language Models Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan Greenewald, Brian Belgodere, Mikhail Yurochkin, Jiri Navratil, Igor Melnyk, Jarret Ross
NeurIPS 2024 Score Distillation via Reparametrized DDIM Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan Greenewald, Vitor Campagnolo Guizilini, Timur Bagautdinov, Vincent Sitzmann, Justin Solomon
ICML 2024 Slicing Mutual Information Generalization Bounds for Neural Networks Kimia Nadjahi, Kristjan Greenewald, Rickard Brüel Gabrielsson, Justin Solomon
ICML 2024 Thermometer: Towards Universal Calibration for Large Language Models Maohao Shen, Subhro Das, Kristjan Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
TMLR 2023 $k$-Mixup Regularization for Deep Learning via Optimal Transport Kristjan Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
NeurIPS 2023 Identifiability Guarantees for Causal Disentanglement from Soft Interventions Jiaqi Zhang, Kristjan Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
ICLR 2023 Learning Proximal Operators to Discover Multiple Optima Lingxiao Li, Noam Aigerman, Vladimir Kim, Jiajin Li, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon
NeurIPS 2023 Max-Sliced Mutual Information Dor Tsur, Ziv Goldfeld, Kristjan Greenewald
AISTATS 2023 Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan Greenewald, Murat Kocaoglu
NeurIPSW 2023 Outlier-Robust Group Inference via Gradient Space Clustering Yuchen Zeng, Kristjan Greenewald, Luann Jung, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
NeurIPS 2023 Post-Processing Private Synthetic Data for Improving Utility on Selected Measures Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava
NeurIPSW 2023 Risk Assessment and Statistical Significance in the Age of Foundation Models Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan Greenewald, Brian Belgodere, Mikhail Yurochkin, Jiri Navratil, Igor Melnyk, Jarret Ross
ICMLW 2023 Slicing Mutual Information Generalization Bounds for Neural Networks Kimia Nadjahi, Kristjan Greenewald, Rickard Brüel Gabrielsson, Justin Solomon
NeurIPS 2022 $k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension Ziv Goldfeld, Kristjan Greenewald, Theshani Nuradha, Galen Reeves
ICML 2022 Entropic Causal Inference: Graph Identifiability Spencer Compton, Kristjan Greenewald, Dmitriy A Katz, Murat Kocaoglu
ICML 2022 Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets Tal Shnitzer, Mikhail Yurochkin, Kristjan Greenewald, Justin M Solomon
AISTATS 2021 High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation Kristjan Greenewald, Karthikeyan Shanmugam, Dmitriy Katz
UAI 2021 Improving Approximate Optimal Transport Distances Using Quantization Gaspard Beugnot, Aude Genevay, Kristjan Greenewald, Justin Solomon
NeurIPS 2021 Measuring Generalization with Optimal Transport Ching-Yao Chuang, Youssef Mroueh, Kristjan Greenewald, Antonio Torralba, Stefanie Jegelka
NeurIPS 2021 Sliced Mutual Information: A Scalable Measure of Statistical Dependence Ziv Goldfeld, Kristjan Greenewald
NeurIPS 2020 Active Structure Learning of Causal DAGs via Directed Clique Trees Chandler Squires, Sara Magliacane, Kristjan Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
NeurIPS 2020 Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance Ziv Goldfeld, Kristjan Greenewald, Kengo Kato
NeurIPS 2020 Entropic Causal Inference: Identifiability and Finite Sample Results Spencer Compton, Murat Kocaoglu, Kristjan Greenewald, Dmitriy Katz
AISTATS 2020 Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency Ziv Goldfeld, Kristjan Greenewald
ICML 2019 Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang, Yasaman Khazaeni
ICML 2019 Estimating Information Flow in Deep Neural Networks Ziv Goldfeld, Ewout Van Den Berg, Kristjan Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy
NeurIPS 2019 Sample Efficient Active Learning of Causal Trees Kristjan Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adsera, Guy Bresler
NeurIPS 2019 Statistical Model Aggregation via Parameter Matching Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang
NeurIPS 2017 Action Centered Contextual Bandits Kristjan Greenewald, Ambuj Tewari, Susan Murphy, Predag Klasnja
NeurIPS 2017 Time-Dependent Spatially Varying Graphical Models, with Application to Brain fMRI Data Analysis Kristjan Greenewald, Seyoung Park, Shuheng Zhou, Alexander Giessing