| 2023 | Collision Probability Matching Loss for Disentangling Epistemic Uncertainty from Aleatoric Uncertainty. | Hiromi Narimatsu, Mayuko Ozawa, Shiro Kumano |
| 2023 | Characterizing Polarization in Social Networks using the Signed Relational Latent Distance Model. | Nikolaos Nakis, Abdulkadir elikkanat, Louis Boucherie, Christian Djurhuus, Felix Burmester, Daniel Mathias Holmelund, Monika Frolcov, Morten Mrup |
| 2023 | Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. | Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang |
| 2023 | Conjugate Gradient Method for Generative Adversarial Networks. | Hiroki Naganuma, Hideaki Iiduka |
| 2023 | Active Exploration via Experiment Design in Markov Chains. | Mojmir Mutny, Tadeusz Janik, Andreas Krause |
| 2023 | Resolving the Approximability of Offline and Online Non-monotone DR-Submodular Maximization over General Convex Sets. | Loay Mualem, Moran Feldman |
| 2023 | Who Should Predict? Exact Algorithms For Learning to Defer to Humans. | Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag |
| 2023 | Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. | Henry B. Moss, Sebastian W. Ober, Victor Picheny |
| 2023 | On the Calibration of Probabilistic Classifier Sets. | Thomas Mortier, Viktor Bengs, Eyke Hllermeier, Stijn Luca, Willem Waegeman |
| 2023 | Connectivity-contrastive learning: Combining causal discovery and representation learning for multimodal data. | Hiroshi Morioka, Aapo Hyvrinen |
| 2023 | Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders. | Arnab Kumar Mondal, Lakshya Singhal, Piyush Tiwary, Parag Singla, Prathosh AP |
| 2023 | Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. | Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum |
| 2023 | Performative Prediction with Neural Networks. | Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel |
| 2023 | Matching Map Recovery with an Unknown Number of Outliers. | Arshak Minasyan, Tigran Galstyan, Sona Hunanyan, Arnak S. Dalalyan |
| 2023 | Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. | Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski |
| 2023 | Nothing but Regrets - Privacy-Preserving Federated Causal Discovery. | Osman Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken |
| 2023 | A Tale of Sampling and Estimation in Discounted Reinforcement Learning. | Alberto Maria Metelli, Mirco Mutti, Marcello Restelli |
| 2023 | On Model Selection Consistency of Lasso for High-Dimensional Ising Models. | Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima |
| 2023 | Singular Value Representation: A New Graph Perspective On Neural Networks. | Dan Meller, Nicolas Berkouk |
| 2023 | Stochastic Optimization for Spectral Risk Measures. | Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zad Harchaoui |
| 2023 | Thresholded linear bandits. | Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen |
| 2023 | Discovering Many Diverse Solutions with Bayesian Optimization. | Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner |
| 2023 | Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery. | Tyler Maunu, Thibaut Le Gouic, Philippe Rigollet |
| 2023 | Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems. | Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee |
| 2023 | Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate. | Ziye Ma, Somayeh Sojoudi |