Optimization

Consensus Maximisation Using Influences of Monotone Boolean Functions CVPR 2021 Conservative Objective Models for Effective Offline Model-Based Optimization ICML 2021 Consistency-Sensitivity Guided Ensemble Black-Box Adversarial Attacks in Low-Dimensional Spaces ICCV 2021 Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers NeurIPS 2021 Consistent Non-Parametric Methods for Maximizing Robustness NeurIPS 2021 Consistent Right-Invariant Fixed-Lag Smoother with Application to Visual Inertial SLAM AAAI 2021 Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes NeurIPS 2021 Constrained Risk-Averse Markov Decision Processes AAAI 2021 Constrained Weight Optimization for Learning Without Activation Normalization WACV 2021 ContactOpt: Optimizing Contact To Improve Grasps CVPR 2021 Context-Aware Online Collective Inference for Templated Graphical Models ICML 2021 Contingency-aware influence maximization: A reinforcement learning approach UAI 2021 Continual learning in recurrent neural networks ICLR 2021 Continuous Doubly Constrained Batch Reinforcement Learning NeurIPS 2021 Continuous Time Analysis of Momentum Methods JMLR 2021 Continuous vs. Discrete Optimization of Deep Neural Networks NeurIPS 2021 Contrastive Losses and Solution Caching for Predict-and-Optimize IJCAI 2021 Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning AISTATS 2021 Convergence of adaptive algorithms for constrained weakly convex optimization NeurIPS 2021 Convergence Properties of Stochastic Hypergradients AISTATS 2021 Convergence rates and approximation results for SGD and its continuous-time counterpart COLT 2021 Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance NeurIPS 2021 Convex Aggregation for Opinion Summarization EMNLP 2021 Convex-Concave Min-Max Stackelberg Games NeurIPS 2021 Convex Geometry and Duality of Over-parameterized Neural Networks JMLR 2021