Summary of Privacy For Free in the Over-parameterized Regime, by Simone Bombari and Marco Mondelli
Privacy for Free in the Over-Parameterized Regimeby Simone Bombari, Marco MondelliFirst submitted to arxiv on:…
Summary of Implicit Regularization Of Sharpness-aware Minimization For Scale-invariant Problems, by Bingcong Li et al.
Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problemsby Bingcong Li, Liang Zhang, Niao HeFirst submitted…
Summary of Sglp: a Similarity Guided Fast Layer Partition Pruning For Compressing Large Deep Models, by Yuqi Li et al.
SGLP: A Similarity Guided Fast Layer Partition Pruning for Compressing Large Deep Modelsby Yuqi Li,…
Summary of Sifm: a Foundation Model For Multi-granularity Arctic Sea Ice Forecasting, by Jingyi Xu et al.
SIFM: A Foundation Model for Multi-granularity Arctic Sea Ice Forecastingby Jingyi Xu, Yeqi Luo, Weidong…
Summary of On the Regularization Of Learnable Embeddings For Time Series Forecasting, by Luca Butera et al.
On the Regularization of Learnable Embeddings for Time Series Forecastingby Luca Butera, Giovanni De Felice,…
Summary of Enhancing Cryptocurrency Market Forecasting: Advanced Machine Learning Techniques and Industrial Engineering Contributions, by Jannatun Nayeem Pinky and Ramya Akula
Enhancing Cryptocurrency Market Forecasting: Advanced Machine Learning Techniques and Industrial Engineering Contributionsby Jannatun Nayeem Pinky,…
Summary of Momentumsmoe: Integrating Momentum Into Sparse Mixture Of Experts, by Rachel S.y. Teo et al.
MomentumSMoE: Integrating Momentum into Sparse Mixture of Expertsby Rachel S.Y. Teo, Tan M. NguyenFirst submitted…
Summary of Razor: Refining Accuracy by Zeroing Out Redundancies, By Daniel Riccio et al.
RAZOR: Refining Accuracy by Zeroing Out Redundanciesby Daniel Riccio, Genoveffa Tortora, Mara SangiovanniFirst submitted to…
Summary of Debiasing Mini-batch Quadratics For Applications in Deep Learning, by Lukas Tatzel et al.
Debiasing Mini-Batch Quadratics for Applications in Deep Learningby Lukas Tatzel, Bálint Mucsányi, Osane Hackel, Philipp…
Summary of Hierarchical Conditional Multi-task Learning For Streamflow Modeling, by Shaoming Xu et al.
Hierarchical Conditional Multi-Task Learning for Streamflow Modelingby Shaoming Xu, Arvind Renganathan, Ankush Khandelwal, Rahul Ghosh,…