Papers
Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization
Miika Aittala, Prafull Sharma, Lukas Murmann et al.
Computing Full Conformal Prediction Set with Approximate Homotopy
Eugene Ndiaye, Ichiro Takeuchi
Computing Linear Restrictions of Neural Networks
Matthew Sotoudeh, Aditya V Thakur
Concentration of risk measures: A Wasserstein distance approach
Sanjay P. Bhat, Prashanth L.A.
CondConv: Conditionally Parameterized Convolutions for Efficient Inference
Brandon Yang, Gabriel Bender, Quoc V Le et al.
Conditional Independence Testing using Generative Adversarial Networks
Alexis Bellot, Mihaela van der Schaar
Conditional Structure Generation through Graph Variational Generative Adversarial Nets
Carl Yang, Peiye Zhuang, Wenhan Shi et al.
Conformalized Quantile Regression
Yaniv Romano, Evan Patterson, Emmanuel Candes
Conformal Prediction Under Covariate Shift
Ryan J Tibshirani, Rina Foygel Barber, Emmanuel Candes et al.
Connections Between Mirror Descent, Thompson Sampling and the Information Ratio
Julian Zimmert, Tor Lattimore
Connective Cognition Network for Directional Visual Commonsense Reasoning
Aming Wu, Linchao Zhu, Yahong Han et al.
Consistency-based Semi-supervised Learning for Object detection
Jisoo Jeong, Seungeui Lee, Jeesoo Kim et al.
Constrained deep neural network architecture search for IoT devices accounting for hardware calibration
Florian Scheidegger, Luca Benini, Costas Bekas et al.
Constrained Reinforcement Learning Has Zero Duality Gap
Santiago Paternain, Luiz Chamon, Miguel Calvo-Fullana et al.
Constraint-based Causal Structure Learning with Consistent Separating Sets
Honghao Li, Vincent Cabeli, Nadir Sella et al.
Contextual Bandits with Cross-Learning
Santiago Balseiro, Negin Golrezaei, Mohammad Mahdian et al.
Continual Unsupervised Representation Learning
Dushyant Rao, Francesco Visin, Andrei Rusu et al.
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
Emile Mathieu, Charline Le Lan, Chris J. Maddison et al.
Continuous-time Models for Stochastic Optimization Algorithms
Antonio Orvieto, Aurelien Lucchi
Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence
Fengxiang He, Tongliang Liu, Dacheng Tao
Controllable Text-to-Image Generation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz et al.
Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation
Ke Wang, Hang Hua, Xiaojun Wan
Controlling Neural Level Sets
Matan Atzmon, Niv Haim, Lior Yariv et al.
Control What You Can: Intrinsically Motivated Task-Planning Agent
Sebastian Blaes, Marin Vlastelica Pogančić, Jiajie Zhu et al.