| 2024 | Federated Experiment Design under Distributed Differential Privacy. | Wei-Ning Chen, Graham Cormode, Akash Bharadwaj, Peter Romov, Ayfer zgr |
| 2024 | Coreset Markov chain Monte Carlo. | Naitong Chen, Trevor Campbell |
| 2024 | Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation. | Vinod Kumar Chauhan, Jiandong Zhou, Ghadeer O. Ghosheh, Soheila Molaei, David A. Clifton |
| 2024 | Efficient Quantum Agnostic Improper Learning of Decision Trees. | Sagnik Chatterjee, Tharrmashastha SAPV, Debajyoti Bera |
| 2024 | Online Learning of Decision Trees with Thompson Sampling. | Ayman Chaouki, Jesse Read, Albert Bifet |
| 2024 | Probabilistic Modeling for Sequences of Sets in Continuous-Time. | Yuxin Chang, Alex J. Boyd, Padhraic Smyth |
| 2024 | Score Operator Newton transport. | Nisha Chandramoorthy, Florian T. Schfer, Youssef M. Marzouk |
| 2024 | PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model. | Abhinav Chakraborty, Anirban Chatterjee, Abhinandan Dalal |
| 2024 | Towards a Complete Benchmark on Video Moment Localization. | Jinyeong Chae, Donghwa Kim, Kwanseok Kim, Doyeon Lee, Sangho Lee, Seongsu Ha, Jonghwan Mun, Wooyoung Kang, Byungseok Roh, Joonseok Lee |
| 2024 | Random Oscillators Network for Time Series Processing. | Andrea Ceni, Andrea Cossu, Maximilian W. Stlzle, Jingyue Liu, Cosimo Della Santina, Davide Bacciu, Claudio Gallicchio |
| 2024 | Double InfoGAN for Contrastive Analysis. | Florence Carton, Robin Louiset, Pietro Gori |
| 2024 | Conditions on Preference Relations that Guarantee the Existence of Optimal Policies. | Jonathan Colao Carr, Prakash Panangaden, Doina Precup |
| 2024 | The sample complexity of ERMs in stochastic convex optimization. | Daniel Carmon, Amir Yehudayoff, Roi Livni |
| 2024 | Pure Exploration in Bandits with Linear Constraints. | Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi |
| 2024 | Consistent Hierarchical Classification with A Generalized Metric. | Yuzhou Cao, Lei Feng, Bo An |
| 2024 | The Galerkin method beats Graph-Based Approaches for Spectral Algorithms. | Vivien A Cabannnes, Francis Bach |
| 2024 | Auditing Fairness under Unobserved Confounding. | Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder |
| 2024 | Density-Regression: Efficient and Distance-aware Deep Regressor for Uncertainty Estimation under Distribution Shifts. | Ha Manh Bui, Anqi Liu |
| 2024 | Simple and scalable algorithms for cluster-aware precision medicine. | Amanda M. Buch, Conor Liston, Logan Grosenick |
| 2024 | VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates. | Guillaume Braun, Masashi Sugiyama |
| 2024 | Deep Classifier Mimicry without Data Access. | Steven Braun, Martin Mundt, Kristian Kersting |
| 2024 | Spectrum Extraction and Clipping for Implicitly Linear Layers. | Ali Ebrahimpour Boroojeny, Matus Telgarsky, Hari Sundaram |
| 2024 | Data Driven Threshold and Potential Initialization for Spiking Neural Networks. | Velibor Bojkovic, Srinivas Anumasa, Giulia De Masi, Bin Gu, Huan Xiong |
| 2024 | On the Vulnerability of Fairness Constrained Learning to Malicious Noise. | Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin M. Stangl |
| 2024 | Federated Linear Contextual Bandits with Heterogeneous Clients. | Ethan Blaser, Chuanhao Li, Hongning Wang |