Optimization

High Dimensional Forecasting via Interpretable Vector Autoregression JMLR 2020 High-dimensional Robust Mean Estimation via Gradient Descent ICML 2020 High Dimensional Robust Sparse Regression AISTATS 2020 Highly smooth minimization of non-smooth problems COLT 2020 High probability guarantees for stochastic convex optimization COLT 2020 High Throughput Cryptocurrency Routing in Payment Channel Networks NSDI 2020 HirePeer: Impartial Peer-Assessed Hiring at Scale in Expert Crowdsourcing Markets AAAI 2020 History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms ICML 2020 HLHLp: Quantized Neural Networks Training for Reaching Flat Minima in Loss Surface AAAI 2020 How Decoding Strategies Affect the Verifiability of Generated Text EMNLP 2020 How Good is SGD with Random Shuffling? COLT 2020 How many samples is a good initial point worth in Low-rank Matrix Recovery? NeurIPS 2020 How the Duration of the Learning Period Affects the Performance of Random Gradient Selection Hyper-Heuristics AAAI 2020 How to Characterize The Landscape of Overparameterized Convolutional Neural Networks NeurIPS 2020 How to Train Your Deep Multi-Object Tracker CVPR 2020 How to Trap a Gradient Flow COLT 2020 HRank: Filter Pruning Using High-Rank Feature Map CVPR 2020 HS-CAI: A Hybrid DCOP Algorithm via Combining Search with Context-Based Inference AAAI 2020 Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization ICML 2020 Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function NeurIPS 2020 Hypersolvers: Toward Fast Continuous-Depth Models NeurIPS 2020 HyperSTAR: Task-Aware Hyperparameters for Deep Networks CVPR 2020 I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations IJCAI 2020 I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively ICLR 2020 IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method NeurIPS 2020