Papers
Constrained Optimization with Dynamic Bound-scaling for Effective NLP Backdoor Defense
Guangyu Shen, Yingqi Liu, Guanhong Tao et al.
Constrained Variational Policy Optimization for Safe Reinforcement Learning
Zuxin Liu, Zhepeng Cen, Vladislav Isenbaev et al.
Constraint-based graph network simulator
Yulia Rubanova, Alvaro Sanchez-Gonzalez, Tobias Pfaff et al.
Content Addressable Memory Without Catastrophic Forgetting by Heteroassociation with a Fixed Scaffold
Sugandha Sharma, Sarthak Chandra, Ila Fiete
ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers
Kaizhi Qian, Yang Zhang, Heting Gao et al.
Context-Aware Drift Detection
Oliver Cobb, Arnaud Van Looveren
Contextual Bandits with Large Action Spaces: Made Practical
Yinglun Zhu, Dylan J Foster, John Langford et al.
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces
Yinglun Zhu, Paul Mineiro
Contextual Information-Directed Sampling
Botao Hao, Tor Lattimore, Chao Qin
Continual Learning via Sequential Function-Space Variational Inference
Tim G. J. Rudner, Freddie Bickford Smith, Qixuan Feng et al.
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