Papers
Counterbalancing Learning and Strategic Incentives in Allocation Markets
Jamie Kang, Faidra Monachou, Moran Koren et al.
Counterexample Guided RL Policy Refinement Using Bayesian Optimization
Briti Gangopadhyay, Pallab Dasgupta
Counterfactual Explanations Can Be Manipulated
Dylan Slack, Anna Hilgard, Himabindu Lakkaraju et al.
Counterfactual Explanations in Sequential Decision Making Under Uncertainty
Stratis Tsirtsis, Abir De, Manuel Rodriguez
Counterfactual Invariance to Spurious Correlations in Text Classification
Victor Veitch, Alexander D'Amour, Steve Yadlowsky et al.
Counterfactual Maximum Likelihood Estimation for Training Deep Networks
Xinyi Wang, Wenhu Chen, Michael Saxon et al.
Coupled Gradient Estimators for Discrete Latent Variables
Zhe Dong, Andriy Mnih, George Tucker
Coupled Segmentation and Edge Learning via Dynamic Graph Propagation
Zhiding Yu, Rui Huang, Wonmin Byeon et al.
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation
Gavin Brown, Marco Gaboardi, Adam Smith et al.
Credal Self-Supervised Learning
Julian Lienen, Eyke Hüllermeier
Credit Assignment in Neural Networks through Deep Feedback Control
Alexander Meulemans, Matilde Tristany Farinha, Javier Garcia Ordonez et al.
Credit Assignment Through Broadcasting a Global Error Vector
David Clark, L F Abbott, Sueyeon Chung
CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age
Dani Kiyasseh, Tingting Zhu, David Clifton
Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning
Xiong-Hui Chen, Shengyi Jiang, Feng Xu et al.
Cross-view Geo-localization with Layer-to-Layer Transformer
Hongji Yang, Xiufan Lu, Yingying Zhu
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Brian Knott, Shobha Venkataraman, Awni Hannun et al.
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
Yusuke Tashiro, Jiaming Song, Yang Song et al.
Curriculum Design for Teaching via Demonstrations: Theory and Applications
Gaurav Yengera, Rati Devidze, Parameswaran Kamalaruban et al.
Curriculum Disentangled Recommendation with Noisy Multi-feedback
Hong Chen, Yudong Chen, Xin Wang et al.
Curriculum Learning for Vision-and-Language Navigation
Jiwen Zhang, zhongyu wei, Jianqing Fan et al.
Curriculum Offline Imitating Learning
Minghuan Liu, Hanye Zhao, Zhengyu Yang et al.
Cycle Self-Training for Domain Adaptation
Hong Liu, Jianmin Wang, Mingsheng Long
D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation
Abhishek Sinha, Jiaming Song, Chenlin Meng et al.
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization
Ke Sun, Yafei Wang, Yi Liu et al.
Dangers of Bayesian Model Averaging under Covariate Shift
Pavel Izmailov, Patrick Nicholson, Sanae Lotfi et al.