Optimization

Evolving Spiking Circuit Motifs Using Weight Agnostic Neural Networks AAAI 2021 Exact Optimization of Conformal Predictors via Incremental and Decremental Learning ICML 2021 Exact Reduction of Huge Action Spaces in General Reinforcement Learning AAAI 2021 Expanding Boundaries of Gap Safe Screening JMLR 2021 Explainable Automated Graph Representation Learning with Hyperparameter Importance ICML 2021 Explaining Hyperparameter Optimization via Partial Dependence Plots NeurIPS 2021 Explicit Regularization of Stochastic Gradient Methods through Duality AISTATS 2021 Exploiting Curriculum Learning in Unsupervised Neural Machine Translation EMNLP 2021 Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach NeurIPS 2021 Exploiting Sparsity for Neural Network Verification L4DC 2021 Exploration and Estimation for Model Compression ICCV 2021 Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models ACL 2021 Exploring the loss landscape in neural architecture search UAI 2021 Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption AAAI 2021 Exponential Graph is Provably Efficient for Decentralized Deep Training NeurIPS 2021 Extracting Strong Policies for Robotics Tasks from Zero-Order Trajectory Optimizers ICLR 2021 Facility’s Perspective to Fair Facility Location Problems AAAI 2021 Factorization Machines with Regularization for Sparse Feature Interactions JMLR 2021 Fair and Efficient Allocations under Subadditive Valuations AAAI 2021 Fair and Efficient Allocations with Limited Demands AAAI 2021 FairBatch: Batch Selection for Model Fairness ICLR 2021 Fair Clustering Under a Bounded Cost NeurIPS 2021 Fair Influence Maximization: a Welfare Optimization Approach AAAI 2021 Fairness in Forecasting and Learning Linear Dynamical Systems AAAI 2021 Fairness in Long-Term Participatory Budgeting IJCAI 2021