Papers
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models
Shoubo Hu, Zhitang Chen, Vahid Partovi Nia et al.
Causal Inference via Kernel Deviance Measures
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
Causal Inference with Noisy and Missing Covariates via Matrix Factorization
Nathan Kallus, Xiaojie Mao, Madeleine Udell
Chaining Mutual Information and Tightening Generalization Bounds
Amir Asadi, Emmanuel Abbe, Sergio Verdu
Chain of Reasoning for Visual Question Answering
Chenfei Wu, Jinlai Liu, Xiaojie Wang et al.
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
Clebsch–Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network
Risi Kondor, Zhen Lin, Shubhendu Trivedi
Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms
Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Dominik Linzner, Heinz Koeppl
COLA: Decentralized Linear Learning
Lie He, An Bian, Martin Jaggi
Collaborative Learning for Deep Neural Networks
Guocong Song, Wei Chai
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Zhuwen Li, Qifeng Chen, Vladlen Koltun
Communication Compression for Decentralized Training
Hanlin Tang, Shaoduo Gan, Ce Zhang et al.
Communication Efficient Parallel Algorithms for Optimization on Manifolds
Bayan Saparbayeva, Michael Zhang, Lizhen Lin
Community Exploration: From Offline Optimization to Online Learning
Xiaowei Chen, Weiran Huang, Wei Chen et al.
Compact Generalized Non-local Network
Kaiyu Yue, Ming Sun, Yuchen Yuan et al.
Compact Representation of Uncertainty in Clustering
Craig Greenberg, Nicholas Monath, Ari Kobren et al.
Completing State Representations using Spectral Learning
Nan Jiang, Alex Kulesza, Satinder Singh
Complex Gated Recurrent Neural Networks
Moritz Wolter, Angela Yao
Computationally and statistically efficient learning of causal Bayes nets using path queries
Kevin Bello, Jean Honorio
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Soeren Laue, Matthias Mitterreiter, Joachim Giesen
Computing Kantorovich-Wasserstein Distances on $d$-dimensional histograms using $(d+1)$-partite graphs
Gennaro Auricchio, Federico Bassetti, Stefano Gualandi et al.
Conditional Adversarial Domain Adaptation
Mingsheng Long, ZHANGJIE CAO, Jianmin Wang et al.
Confounding-Robust Policy Improvement
Nathan Kallus, Angela Zhou
Connecting Optimization and Regularization Paths
Arun Suggala, Adarsh Prasad, Pradeep K Ravikumar