Summary of Modsec-learn: Boosting Modsecurity with Machine Learning, by Christian Scano et al.
ModSec-Learn: Boosting ModSecurity with Machine Learningby Christian Scano, Giuseppe Floris, Biagio Montaruli, Luca Demetrio, Andrea…
Summary of Additive Regularization Schedule For Neural Architecture Search, by Mark Potanin and Kirill Vayser and Vadim Strijov
Additive regularization schedule for neural architecture searchby Mark Potanin, Kirill Vayser, Vadim StrijovFirst submitted to…
Summary of The Limits Of Pure Exploration in Pomdps: When the Observation Entropy Is Enough, by Riccardo Zamboni et al.
The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enoughby Riccardo Zamboni,…
Summary of Spatially Resolved Gene Expression Prediction From Histology Via Multi-view Graph Contrastive Learning with Hsic-bottleneck Regularization, by Changxi Chi et al.
Spatially Resolved Gene Expression Prediction from Histology via Multi-view Graph Contrastive Learning with HSIC-bottleneck Regularizationby…
Summary of Interpretable Modulated Differentiable Stft and Physics-informed Balanced Spectrum Metric For Freight Train Wheelset Bearing Cross-machine Transfer Fault Diagnosis Under Speed Fluctuations, by Chao He and Hongmei Shi and Ruixin Li and Jianbo Li and Zujun Yu
Interpretable modulated differentiable STFT and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine…
Summary of How Neural Networks Learn the Support Is An Implicit Regularization Effect Of Sgd, by Pierfrancesco Beneventano et al.
How Neural Networks Learn the Support is an Implicit Regularization Effect of SGDby Pierfrancesco Beneventano,…
Summary of The Benefits Of Power Regularization in Cooperative Reinforcement Learning, by Michelle Li and Michael Dennis
The Benefits of Power Regularization in Cooperative Reinforcement Learningby Michelle Li, Michael DennisFirst submitted to…
Summary of Dipper: Direct Preference Optimization to Accelerate Primitive-enabled Hierarchical Reinforcement Learning, by Utsav Singh et al.
DIPPER: Direct Preference Optimization to Accelerate Primitive-Enabled Hierarchical Reinforcement Learningby Utsav Singh, Souradip Chakraborty, Wesley…
Summary of Grad-instructor: Universal Backpropagation with Explainable Evaluation Neural Networks For Meta-learning and Automl, by Ryohei Ino
Grad-Instructor: Universal Backpropagation with Explainable Evaluation Neural Networks for Meta-learning and AutoMLby Ryohei InoFirst submitted…
Summary of Analysing Multi-task Regression Via Random Matrix Theory with Application to Time Series Forecasting, by Romain Ilbert et al.
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecastingby Romain Ilbert,…