Optimization

Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time ALT 2021 Asynchronous $ε$-Greedy Bayesian Optimisation UAI 2021 Asynchronous Decentralized Online Learning NeurIPS 2021 Asynchronous Decentralized SGD with Quantized and Local Updates NeurIPS 2021 Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees AAAI 2021 Asynchronous Stochastic Gradient Descent for Extreme-Scale Recommender Systems AAAI 2021 Asynchronous Stochastic Optimization Robust to Arbitrary Delays NeurIPS 2021 Asynchronous Teacher Guided Bit-wise Hard Mining for Online Hashing AAAI 2021 A Tale of Two Efficient and Informative Negative Sampling Distributions ICML 2021 A Theory of the Distortion-Perception Tradeoff in Wasserstein Space NeurIPS 2021 A Theory of the Risk for Optimization with Relaxation and its Application to Support Vector Machines JMLR 2021 A Trace-restricted Kronecker-Factored Approximation to Natural Gradient AAAI 2021 Auction Learning as a Two-Player Game ICLR 2021 Augmented Lagrangian Adversarial Attacks ICCV 2021 A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints JMLR 2021 A Unified Convergence Analysis for Shuffling-Type Gradient Methods JMLR 2021 A Unified Framework for Planning with Learned Neural Network Transition Models AAAI 2021 A Unified Lottery Ticket Hypothesis for Graph Neural Networks ICML 2021 A unified view of likelihood ratio and reparameterization gradients AISTATS 2021 A Universal 2-state n-action Adaptive Management Solver AAAI 2021 AutoAttend: Automated Attention Representation Search ICML 2021 AutoDropout: Learning Dropout Patterns to Regularize Deep Networks AAAI 2021 AutoFlow: Learning a Better Training Set for Optical Flow CVPR 2021 AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Auto-KWS 2021 Challenge: Task, Datasets, and Baselines Interspeech 2021