Papers
Budgeted and Non-Budgeted Causal Bandits
Vineet Nair, Vishakha Patil, Gaurav Sinha
CADA: Communication-Adaptive Distributed Adam
Tianyi Chen, Ziye Guo, Yuejiao Sun et al.
Calibrated Adaptive Probabilistic ODE Solvers
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Causal Autoregressive Flows
Ilyes Khemakhem, Ricardo Monti, Robert Leech et al.
Causal Inference under Networked Interference and Intervention Policy Enhancement
Yunpu Ma, Volker Tresp
Causal Inference with Selectively Deconfounded Data
Kyra Gan, Andrew Li, Zachary Lipton et al.
Causal Modeling with Stochastic Confounders
Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma et al.
CLAR: Contrastive Learning of Auditory Representations
Haider Al-Tahan, Yalda Mohsenzadeh
Clustering multilayer graphs with missing nodes
Guillaume Braun, Hemant Tyagi, Christophe Biernacki
Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering
Sebastian Macaluso, Craig Greenberg, Nicholas Monath et al.
Collaborative Classification from Noisy Labels
Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage et al.
Combinatorial Gaussian Process Bandits with Probabilistically Triggered Arms
Ilker Demirel, Cem Tekin
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization
Congliang Chen, Jiawei Zhang, Li Shen et al.
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
Mayee Chen, Benjamin Cohen-Wang, Stephen Mussmann et al.
Competing AI: How does competition feedback affect machine learning?
Tony Ginart, Eva Zhang, Yongchan Kwon et al.
Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions
Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov et al.
Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting
Ilja Kuzborskij, Claire Vernade, Andras Gyorgy et al.
Consistent k-Median: Simpler, Better and Robust
Xiangyu Guo, Janardhan Kulkarni, Shi Li et al.
Context-Specific Likelihood Weighting
Nitesh Kumar, Ondřej Kuželka
Contextual Blocking Bandits
Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis et al.
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors
Nikhil Mehta, Kevin Liang, Vinay Kumar Verma et al.
Continuum-Armed Bandits: A Function Space Perspective
Shashank Singh
CONTRA: Contrarian statistics for controlled variable selection
Mukund Sudarshan, Aahlad Puli, Lakshmi Subramanian et al.
Contrastive learning of strong-mixing continuous-time stochastic processes
Bingbin Liu, Pradeep Ravikumar, Andrej Risteski
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
Zachary Charles, Jakub Konečný