Optimization

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors AAAI 2020 Bundle Adjustment on a Graph Processor CVPR 2020 Byte Pair Encoding is Suboptimal for Language Model Pretraining EMNLP 2020 Cakewalk Sampling AAAI 2020 Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data EMNLP 2020 Can Cross Entropy Loss Be Robust to Label Noise? IJCAI 2020 Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study NeurIPS 2020 Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS CVPR 2020 Can We Learn Heuristics for Graphical Model Inference Using Reinforcement Learning? CVPR 2020 CAQL: Continuous Action Q-Learning ICLR 2020 CARS: Continuous Evolution for Efficient Neural Architecture Search CVPR 2020 CASTER: Predicting Drug Interactions with Chemical Substructure Representation AAAI 2020 Causal Bayesian Optimization AISTATS 2020 CD-UAP: Class Discriminative Universal Adversarial Perturbation AAAI 2020 Certified Monotonic Neural Networks NeurIPS 2020 Channel Pruning Guided by Classification Loss and Feature Importance AAAI 2020 Channel Pruning via Automatic Structure Search IJCAI 2020 Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe NeurIPS 2020 Choosing the Sample with Lowest Loss makes SGD Robust AISTATS 2020 Closing the convergence gap of SGD without replacement ICML 2020 Coarse Correlation in Extensive-Form Games AAAI 2020 Cogradient Descent for Bilinear Optimization CVPR 2020 Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls AISTATS 2020 Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020 Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks ICML 2020