Optimization

AutoCFR: Learning to Design Counterfactual Regret Minimization Algorithms AAAI 2022 AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks AutoML 2022 AutoLoss-Zero: Searching Loss Functions From Scratch for Generic Tasks CVPR 2022 AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning NeurIPS 2022 Automated Progressive Learning for Efficient Training of Vision Transformers CVPR 2022 Automated Super-Network Generation for Scalable Neural Architecture Search AutoML 2022 Automatic differentiation of nonsmooth iterative algorithms NeurIPS 2022 Automatic Differentiation of Programs with Discrete Randomness NeurIPS 2022 Automatic Document Selection for Efficient Encoder Pretraining EMNLP 2022 Automatic Learning of Subword Dependent Model Scales Interspeech 2022 Automatic planning of liver tumor thermal ablation using deep reinforcement learning MIDL 2022 Automatic Termination for Hyperparameter Optimization AutoML 2022 Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning JMLR 2022 AutoSNN: Towards Energy-Efficient Spiking Neural Networks ICML 2022 AutoST: Towards the Universal Modeling of Spatio-temporal Sequences NeurIPS 2022 Auxiliary Learning with Joint Task and Data Scheduling ICML 2022 A Variant of Anderson Mixing with Minimal Memory Size NeurIPS 2022 A-ViT: Adaptive Tokens for Efficient Vision Transformer CVPR 2022 Balanced Self-Paced Learning for AUC Maximization AAAI 2022 Balancing utility and scalability in metric differential privacy UAI 2022 Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization AAAI 2022 Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning AISTATS 2022 Batch Bayesian optimisation via density-ratio estimation with guarantees NeurIPS 2022 Batch size-invariance for policy optimization NeurIPS 2022 Bayesian inference via sparse Hamiltonian flows NeurIPS 2022