Papers
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
Continuous Time Bayesian Networks with Clocks
Nicolai Engelmann, Dominik Linzner, Heinz Koeppl
Continuous-time Lower Bounds for Gradient-based Algorithms
Michael Muehlebach, Michael Jordan
Contrastive Multi-View Representation Learning on Graphs
Kaveh Hassani, Amir Hosein Khasahmadi
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning
Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi et al.
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
Arsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin et al.
ControlVAE: Controllable Variational Autoencoder
Huajie Shao, Shuochao Yao, Dachun Sun et al.
Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization
Vien Mai, Mikael Johansson
Convergence Rates of Variational Inference in Sparse Deep Learning
Badr-Eddine Chérief-Abdellatif
Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer Games
Youzhi Zhang, Bo An
Convex Calibrated Surrogates for the Multi-Label F-Measure
Mingyuan Zhang, Harish Guruprasad Ramaswamy, Shivani Agarwal