Summary of Tslanet: Rethinking Transformers For Time Series Representation Learning, by Emadeldeen Eldele et al.
TSLANet: Rethinking Transformers for Time Series Representation Learningby Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min…
Summary of Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization, by Runqi Lin et al.
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularizationby Runqi Lin, Chaojian Yu, Tongliang LiuFirst submitted…
Summary of Minimizing Chebyshev Prototype Risk Magically Mitigates the Perils Of Overfitting, by Nathaniel Dean et al.
Minimizing Chebyshev Prototype Risk Magically Mitigates the Perils of Overfittingby Nathaniel Dean, Dilip SarkarFirst submitted…
Summary of Counterfactual Reasoning For Multi-label Image Classification Via Patching-based Training, by Ming-kun Xie et al.
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Trainingby Ming-Kun Xie, Jia-Hao Xiao, Pei Peng,…
Summary of Elephants Never Forget: Memorization and Learning Of Tabular Data in Large Language Models, by Sebastian Bordt et al.
Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Modelsby Sebastian Bordt,…
Summary of Anchoral: Computationally Efficient Active Learning For Large and Imbalanced Datasets, by Pietro Lesci and Andreas Vlachos
AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasetsby Pietro Lesci, Andreas VlachosFirst submitted…
Summary of The Sample Complexity Of Gradient Descent in Stochastic Convex Optimization, by Roi Livni
The Sample Complexity of Gradient Descent in Stochastic Convex Optimizationby Roi LivniFirst submitted to arxiv…
Summary of Multicalibration For Confidence Scoring in Llms, by Gianluca Detommaso et al.
Multicalibration for Confidence Scoring in LLMsby Gianluca Detommaso, Martin Bertran, Riccardo Fogliato, Aaron RothFirst submitted…
Summary of Rolling the Dice For Better Deep Learning Performance: a Study Of Randomness Techniques in Deep Neural Networks, by Mohammed Ghaith Altarabichi et al.
Rolling the dice for better deep learning performance: A study of randomness techniques in deep…
Summary of Deit-lt Distillation Strikes Back For Vision Transformer Training on Long-tailed Datasets, by Harsh Rangwani et al.
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed Datasetsby Harsh Rangwani, Pradipto Mondal,…