| 2023 | Expectation consistency for calibration of neural networks. | Lucas Clart, Bruno Loureiro, Florent Krzakala, Lenka Zdeborov |
| 2023 | Establishing Markov equivalence in cyclic directed graphs. | Tom Claassen, Joris M. Mooij |
| 2023 | Finite-sample guarantees for Nash Q-learning with linear function approximation. | Pedro Cisneros-Velarde, Sanmi Koyejo |
| 2023 | Parity calibration. | Youngseog Chung, Aaron Rumack, Chirag Gupta |
| 2023 | Combinatorial categorized bandits with expert rankings. | Sayak Ray Chowdhury, Gaurav Sinha, Nagarajan Natarajan, Amit Sharma |
| 2023 | Adaptivity Complexity for Causal Graph Discovery. | Davin Choo, Kirankumar Shiragur |
| 2023 | MFA: Multi-layer Feature-aware Attack for Object Detection. | Wen Chen, Yushan Zhang, Zhiheng Li, Yuehuan Wang |
| 2023 | An effective negotiating agent framework based on deep offline reinforcement learning. | Siqi Chen, Jianing Zhao, Gerhard Weiss, Ran Su, Kaiyou Lei |
| 2023 | Modified Retrace for Off-Policy Temporal Difference Learning. | Xingguo Chen, Xingzhou Ma, Yang Li, Guang Yang, Shangdong Yang, Yang Gao |
| 2023 | Causal inference with outcome-dependent missingness and self-censoring. | Jacob M. Chen, Daniel Malinsky, Rohit Bhattacharya |
| 2023 | Detection of Short-Term Temporal Dependencies in Hawkes Processes with Heterogeneous Background Dynamics. | Yu Chen, Fengpei Li, Anderson Schneider, Yuriy Nevmyvaka, Asohan Amarasingham, Henry Lam |
| 2023 | Differential Privacy in Cooperative Multiagent Planning. | Bo Chen, Calvin Hawkins, Mustafa O. Karabag, Cyrus Neary, Matthew T. Hale, Ufuk Topcu |
| 2023 | Enhancing Treatment Effect Estimation: A Model Robust Approach Integrating Randomized Experiments and External Controls using the Double Penalty Integration Estimator. | Yuwen Cheng, Lili Wu, Shu Yang |
| 2023 | Benign Overfitting in Adversarially Robust Linear Classification. | Jinghui Chen, Yuan Cao, Quanquan Gu |
| 2023 | Learning in online MDPs: is there a price for handling the communicating case? | Gautam Chandrasekaran, Ambuj Tewari |
| 2023 | Scalable nonparametric Bayesian learning for dynamic velocity fields. | Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen |
| 2023 | Human Control: Definitions and Algorithms. | Ryan Carey, Tom Everitt |
| 2023 | Scaling integer arithmetic in probabilistic programs. | William X. Cao, Poorva Garg, Ryan Tjoa, Steven Holtzen, Todd D. Millstein, Guy Van den Broeck |
| 2023 | Overcoming Language Priors for Visual Question Answering via Loss Rebalancing Label and Global Context. | Runlin Cao, Zhixin Li |
| 2023 | Testing conventional wisdom (of the crowd). | Noah Burrell, Grant Schoenebeck |
| 2023 | Inference for mark-censored temporal point processes. | Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth |
| 2023 | Approximating probabilistic explanations via supermodular minimization. | Louenas Bounia, Frdric Koriche |
| 2023 | Efficient Learning of Minimax Risk Classifiers in High Dimensions. | Kartheek Bondugula, Santiago Mazuelas, Aritz Prez |
| 2023 | Correcting for selection bias and missing response in regression using privileged information. | Philip A. Boeken, Noud de Kroon, Mathijs de Jong, Joris M. Mooij, Onno Zoeter |
| 2023 | Amortized Inference for Gaussian Process Hyperparameters of Structured Kernels. | Matthias Bitzer, Mona Meister, Christoph Zimmer |