Summary of Finegates: Llms Finetuning with Compression Using Stochastic Gates, by Jonathan Svirsky et al.
FineGates: LLMs Finetuning with Compression using Stochastic Gatesby Jonathan Svirsky, Yehonathan Refael, Ofir LindenbaumFirst submitted…
Summary of On Local Overfitting and Forgetting in Deep Neural Networks, by Uri Stern et al.
On Local Overfitting and Forgetting in Deep Neural Networksby Uri Stern, Tomer Yaacoby, Daphna WeinshallFirst…
Summary of Probabilities-informed Machine Learning, by Mohsen Rashki
Probabilities-Informed Machine Learningby Mohsen RashkiFirst submitted to arxiv on: 16 Dec 2024CategoriesMain: Machine Learning (cs.LG)Secondary:…
Summary of Federated Domain Generalization with Label Smoothing and Balanced Decentralized Training, by Milad Soltany et al.
Federated Domain Generalization with Label Smoothing and Balanced Decentralized Trainingby Milad Soltany, Farhad Pourpanah, Mahdiyar…
Summary of Apar: Modeling Irregular Target Functions in Tabular Regression Via Arithmetic-aware Pre-training and Adaptive-regularized Fine-tuning, by Hong-wei Wu et al.
APAR: Modeling Irregular Target Functions in Tabular Regression via Arithmetic-Aware Pre-Training and Adaptive-Regularized Fine-Tuningby Hong-Wei…
Summary of Control Of Overfitting with Physics, by Sergei V. Kozyrev et al.
Control of Overfitting with Physicsby Sergei V. Kozyrev, Ilya A Lopatin, Alexander N PechenFirst submitted…
Summary of Explaining Model Overfitting in Cnns Via Gmm Clustering, by Hui Dou et al.
Explaining Model Overfitting in CNNs via GMM Clusteringby Hui Dou, Xinyu Mu, Mengjun Yi, Feng…
Summary of Mosld: An Extremely Parameter-efficient Mixture-of-shared Loras For Multi-task Learning, by Lulu Zhao et al.
MoSLD: An Extremely Parameter-Efficient Mixture-of-Shared LoRAs for Multi-Task Learningby Lulu Zhao, Weihao Zeng, Xiaofeng Shi,…
Summary of Gradstop: Exploring Training Dynamics in Unsupervised Outlier Detection Through Gradient Cohesion, by Yuang Zhang et al.
GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through Gradient Cohesionby Yuang Zhang, Liping Wang,…
Summary of Taen: a Model-constrained Tikhonov Autoencoder Network For Forward and Inverse Problems, by Hai V. Nguyen et al.
TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problemsby Hai V. Nguyen, Tan…