Papers
Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
Filipe De Avila Belbute-Peres, Thomas Economon, Zico Kolter
CoMic: Complementary Task Learning & Mimicry for Reusable Skills
Leonard Hasenclever, Fabio Pardo, Raia Hadsell et al.
Communication-Efficient Distributed PCA by Riemannian Optimization
Long-Kai Huang, Sinno Pan
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
Zhishuai Guo, Mingrui Liu, Zhuoning Yuan et al.
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions
Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka et al.
Composable Sketches for Functions of Frequencies: Beyond the Worst Case
Edith Cohen, Ofir Geri, Rasmus Pagh
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation
Reinhard Heckel, Mahdi Soltanolkotabi
Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model
Ying Jin, Zhaoran Wang, Junwei Lu
Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
Prashanth L.A., Krishna Jagannathan, Ravi Kolla
Concept Bottleneck Models
Pang Wei Koh, Thao Nguyen, Yew Siang Tang et al.
Concise Explanations of Neural Networks using Adversarial Training
Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury et al.
Conditional gradient methods for stochastically constrained convex minimization
Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh et al.
Confidence-Aware Learning for Deep Neural Networks
Jooyoung Moon, Jihyo Kim, Younghak Shin et al.
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
David Stutz, Matthias Hein, Bernt Schiele
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting
Niccolo Dalmasso, Rafael Izbicki, Ann Lee
ConQUR: Mitigating Delusional Bias in Deep Q-Learning
Dijia Su, Jayden Ooi, Tyler Lu et al.
Consistent Estimators for Learning to Defer to an Expert
Hussein Mozannar, David Sontag
Consistent Structured Prediction with Max-Min Margin Markov Networks
Alex Nowak, Francis Bach, Alessandro Rudi
Constant Curvature Graph Convolutional Networks
Gregor Bachmann, Gary Becigneul, Octavian Ganea
Constrained Markov Decision Processes via Backward Value Functions
Harsh Satija, Philip Amortila, Joelle Pineau
Constructive Universal High-Dimensional Distribution Generation through Deep ReLU Networks
Dmytro Perekrestenko, Stephan Müller, Helmut Bölcskei
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning
Kimin Lee, Younggyo Seo, Seunghyun Lee et al.
Context Aware Local Differential Privacy
Jayadev Acharya, Kallista Bonawitz, Peter Kairouz et al.
Continuous Graph Neural Networks
Louis-Pascal Xhonneux, Meng Qu, Jian Tang
Continuously Indexed Domain Adaptation
Hao Wang, Hao He, Dina Katabi