Papers
Continual Learning with Guarantees via Weight Interval Constraints
Maciej Wołczyk, Karol Piczak, Bartosz Wójcik et al.
Continual Repeated Annealed Flow Transport Monte Carlo
Alex Matthews, Michael Arbel, Danilo Jimenez Rezende et al.
Continuous Control with Action Quantization from Demonstrations
Robert Dadashi, Léonard Hussenot, Damien Vincent et al.
Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems
Jaewook J Suh, Gyumin Roh, Ernest K Ryu
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations
Nabeel Seedat, Fergus Imrie, Alexis Bellot et al.
Contrastive Learning with Boosted Memorization
Zhihan Zhou, Jiangchao Yao, Yan-Feng Wang et al.
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
Adam Foster, Arpi Vezer, Craig A. Glastonbury et al.
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning
Shuang Qiu, Lingxiao Wang, Chenjia Bai et al.
Controlling Conditional Language Models without Catastrophic Forgetting
Tomasz Korbak, Hady Elsahar, German Kruszewski et al.
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering
Peng Wang, Huikang Liu, Anthony Man-Cho So et al.
Convergence of Invariant Graph Networks
Chen Cai, Yusu Wang
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime
James-Michael Leahy, Bekzhan Kerimkulov, David Siska et al.
Convergence of Uncertainty Sampling for Active Learning
Anant Raj, Francis Bach
Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness
Kevin Scaman, Cedric Malherbe, Ludovic Dos Santos
Convolutional and Residual Networks Provably Contain Lottery Tickets
Rebekka Burkholz
Cooperative Online Learning in Stochastic and Adversarial MDPs
Tal Lancewicki, Aviv Rosenberg, Yishay Mansour
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis et al.
Coordinated Double Machine Learning
Nitai Fingerhut, Matteo Sesia, Yaniv Romano
Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations
Michael Zhang, Nimit S Sohoni, Hongyang R Zhang et al.
Correlated Quantization for Distributed Mean Estimation and Optimization
Ananda Theertha Suresh, Ziteng Sun, Jae Ro et al.
Co-training Improves Prompt-based Learning for Large Language Models
Hunter Lang, Monica N Agrawal, Yoon Kim et al.
Counterfactual Prediction for Outcome-Oriented Treatments
Hao Zou, Bo Li, Jiangang Han et al.
Counterfactual Transportability: A Formal Approach
Juan D Correa, Sanghack Lee, Elias Bareinboim
Cross-Space Active Learning on Graph Convolutional Networks
Yufei Tao, Hao Wu, Shiyuan Deng