| 2024 | Private Learning with Public Features. | Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang |
| 2024 | Structural perspective on constraint-based learning of Markov networks. | Tuukka Korhonen, Fedor V. Fomin, Pekka Parviainen |
| 2024 | Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process. | Lingkai Kong, Haotian Sun, Yuchen Zhuang, Haorui Wang, Wenhao Mu, Chao Zhang |
| 2024 | Bandit Pareto Set Identification: the Fixed Budget Setting. | Cyrille Kone, Emilie Kaufmann, Laura Richert |
| 2024 | SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. | Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hllermeier |
| 2024 | Consistency of Dictionary-Based Manifold Learning. | Samson J. Koelle, Hanyu Zhang, Octavian-Vlad Murad, Marina Meila |
| 2024 | Fair Soft Clustering. | Rune D. Kjrsgaard, Pekka Parviainen, Saket Saurabh, Madhumita Kundu, Line H. Clemmensen |
| 2024 | DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data. | Taehyo Kim, Hai Shu, Qiran Jia, Mony J. de Leon |
| 2024 | Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? | Kyurae Kim, Yi-An Ma, Jacob R. Gardner |
| 2024 | A Doubly Robust Approach to Sparse Reinforcement Learning. | Wonyoung Kim, Garud Iyengar, Assaf Zeevi |
| 2024 | Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions. | Zulqarnain Khan, Davin Hill, Aria Masoomi, Joshua T. Bone, Jennifer G. Dy |
| 2024 | Functional Flow Matching. | Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth |
| 2024 | Discriminator Guidance for Autoregressive Diffusion Models. | Filip Ekstrm Kelvinius, Fredrik Lindsten |
| 2024 | Offline Policy Evaluation and Optimization Under Confounding. | Chinmaya Kausik, Yangyi Lu, Kevin Tan, Maggie Makar, Yixin Wang, Ambuj Tewari |
| 2024 | Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. | Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky |
| 2024 | First Passage Percolation with Queried Hints. | Kritkorn Karntikoon, Yiheng Shen, Sreenivas Gollapudi, Kostas Kollias, Aaron Schild, Ali Kemal Sinop |
| 2024 | A Unified Framework for Discovering Discrete Symmetries. | Pavan Karjol, Rohan Kashyap, Aditya Gopalan, A. P. Prathosh |
| 2024 | Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm. | Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause |
| 2024 | Learning the Pareto Set Under Incomplete Preferences: Pure Exploration in Vector Bandits. | Efe Mert Karagzl, Yasar Cahit Yildirim, agin Ararat, Cem Tekin |
| 2024 | Identifiability of Product of Experts Models. | Manav Kant, Eric Y. Ma, Andrei Staicu, Leonard J. Schulman, Spencer Gordon |
| 2024 | Learning to Rank for Optimal Treatment Allocation Under Resource Constraints. | Fahad Kamran, Maggie Makar, Jenna Wiens |
| 2024 | Differentially Private Conditional Independence Testing. | Iden Kalemaj, Shiva Prasad Kasiviswanathan, Aaditya Ramdas |
| 2024 | Asynchronous Randomized Trace Estimation. | Vasileios Kalantzis, Shashanka Ubaru, Chai Wah Wu, Georgios Kollias, Lior Horesh |
| 2024 | Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations. | Krzysztof Kacprzyk, Mihaela van der Schaar |
| 2024 | Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity. | Siddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman |