| 2025 | An Optimal Algorithm for Strongly Convex Min-Min Optimization. | Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky |
| 2025 | Probabilistic Explanations for Regression Models. | Frdric Koriche, Jean-Marie Lagniez, Chi Tran |
| 2025 | Robust Optimization with Diffusion Models for Green Security. | Lingkai Kong, Haichuan Wang, Yuqi Pan, Cheol Woo Kim, Mingxiao Song, Alayna Nguyen, Tonghan Wang, Haifeng Xu, Milind Tambe |
| 2025 | DF | Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang |
| 2025 | Error Bounds for Physics-Informed Neural Networks in Fokker-Planck PDEs. | Chun-Wei Kong, Luca Laurenti, Jay W. McMahon, Morteza Lahijanian |
| 2025 | A Multivariate Unimodality Test Harnessing the Dip Statistic of Mahalanobis Distances Over Random Projections. | Prodromos Kolyvakis, Aristidis Likas |
| 2025 | Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments. | Yaroslav Kivva, Sina Akbari, Saber Salehkaleybar, Negar Kiyavash |
| 2025 | Collaborative Prediction: To Join or To Disjoin Datasets. | Kyung Rok Kim, Yansong Wang, Xiaocheng Li, Guanting Chen |
| 2025 | Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient? | Hwanwoo Kim, Chong Liu, Yuxin Chen |
| 2025 | Efficiently Escaping Saddle Points for Policy Optimization. | Mohammadsadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash, Niao He, Matthias Grossglauser |
| 2025 | Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference. | Mert Ketenci, Adler J. Perotte, Nomie Elhadad, Iigo Urteaga |
| 2025 | Enumerating Optimal Cost-Constrained Adjustment Sets. | Batya Kenig |
| 2025 | Explaining Negative Classifications of AI Models in Tumor Diagnosis. | David A. Kelly, Hana Chockler, Nathan Blake |
| 2025 | Decomposition of Probabilities of Causation with Two Mediators. | Yuta Kawakami, Jin Tian |
| 2025 | Moments of Causal Effects. | Yuta Kawakami, Jin Tian |
| 2025 | Adapting Prediction Sets to Distribution Shifts Without Labels. | Kevin Kasa, Zhiyu Zhang, Heng Yang, Graham W. Taylor |
| 2025 | Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces. | Avik Kar, Rahul Singh |
| 2025 | ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression. | Avetik G. Karagulyan, Peter Richtrik |
| 2025 | Distributional Reinforcement Learning with Dual Expectile-Quantile Regression. | Sami Jullien, Romain Deffayet, Jean-Michel Renders, Paul Groth, Maarten de Rijke |
| 2025 | Fast Calculation of Feature Contributions in Boosting Trees. | Zhongli Jiang, Min Zhang, Dabao Zhang |
| 2025 | Best Possible Q-Learning. | Jiechuan Jiang, Zongqing Lu |
| 2025 | Coevolutionary Emergent Systems Optimization with Applications to Ultra-High-Dimensional Metasurface Design : OAM Wave Manipulation. | Zhengxuan Jiang, Guowen Ding, Wen Jiang |
| 2025 | Generative Uncertainty in Diffusion Models. | Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric T. Nalisnick, Stephan Mandt |
| 2025 | Lower Bounds on the Size of Markov Equivalence Classes. | Erik Jahn, Frederick Eberhardt, Leonard J. Schulman |
| 2025 | Root Cause Analysis of Failures from Partial Causal Structures. | Azam Ikram, Kenneth Lee, Shubham Agarwal, Shiv Kumar Saini, Saurabh Bagchi, Murat Kocaoglu |