Summary of Learning Rate Optimization For Deep Neural Networks Using Lipschitz Bandits, by Padma Priyanka et al.
Learning Rate Optimization for Deep Neural Networks Using Lipschitz Banditsby Padma Priyanka, Sheetal Kalyani, Avhishek…
Summary of A Simpler Alternative to Variational Regularized Counterfactual Risk Minimization, by Hua Chang Bakker et al.
A Simpler Alternative to Variational Regularized Counterfactual Risk Minimizationby Hua Chang Bakker, Shashank Gupta, Harrie…
Summary of Tx-gen: Multi-objective Optimization For Sparse Counterfactual Explanations For Time-series Classification, by Qi Huang et al.
TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classificationby Qi Huang, Sofoklis Kitharidis, Thomas…
Summary of Autonomous Goal Detection and Cessation in Reinforcement Learning: a Case Study on Source Term Estimation, by Yiwei Shi et al.
Autonomous Goal Detection and Cessation in Reinforcement Learning: A Case Study on Source Term Estimationby…
Summary of Using Synthetic Data to Mitigate Unfairness and Preserve Privacy in Collaborative Machine Learning, by Chia-yuan Wu et al.
Using Synthetic Data to Mitigate Unfairness and Preserve Privacy in Collaborative Machine Learningby Chia-Yuan Wu,…
Summary of Cosco: a Sharpness-aware Training Framework For Few-shot Multivariate Time Series Classification, by Jesus Barreda et al.
COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classificationby Jesus Barreda, Ashley Gomez,…
Summary of Quantum-inspired Reinforcement Learning For Synthesizable Drug Design, by Dannong Wang et al.
Quantum-inspired Reinforcement Learning for Synthesizable Drug Designby Dannong Wang, Jintai Chen, Zhiding Liang, Tianfan Fu,…
Summary of Batched Online Contextual Sparse Bandits with Sequential Inclusion Of Features, by Rowan Swiers et al.
Batched Online Contextual Sparse Bandits with Sequential Inclusion of Featuresby Rowan Swiers, Subash Prabanantham, Andrew…
Summary of A Dynamic Weighting Strategy to Mitigate Worker Node Failure in Distributed Deep Learning, by Yuesheng Xu and Arielle Carr
A Dynamic Weighting Strategy to Mitigate Worker Node Failure in Distributed Deep Learningby Yuesheng Xu,…
Summary of Cross-entropy Optimization For Hyperparameter Optimization in Stochastic Gradient-based Approaches to Train Deep Neural Networks, by Kevin Li et al.
Cross-Entropy Optimization for Hyperparameter Optimization in Stochastic Gradient-based Approaches to Train Deep Neural Networksby Kevin…