A #Visual Guide to #Tuning Decision-Tree #Hyperparameters How hyperparameter tuning visually changes #decisiontrees towardsdatascience.com/visualising-de…

🔥 Read our Highly Cited Paper 📚 Improving #Hardenability Modeling: A #Bayesian #Optimization Approach to Tuning #Hyperparameters for #NeuralNetwork Regression 🔗 mdpi.com/2076-3417/14/6… 👨‍🔬 by Mr. Wendimu Fanta Gemechu et al. 🏫 @polsl_pl

How far away are truly hyperparameter-free learning algorithms? Priya Kasimbeg, Vincent Roulet, Naman Agarwal et al.. Action editor: Bryan Kian Hsiang Low. openreview.net/forum?id=6BlOC… #hyperparameters #hyperparameter #benchmark

Meet λ — your model’s simplicity dial! 🔁 Larger λ = more penalty = simpler model. ⚖️ Too small? Overfit. Too large? Underfit. Tune it right to strike the perfect balance. #MachineLearning #Hyperparameters 6/7

I am ready to select some #foundationalmodels, produce some #prompts , write some #RAGS, fine tune some #hyperparameters, select some #algorithms, and define some #Measurement metrics for a #GenerativeAI platform now that I am @awscloud certified #AI practitioner.

18/22The noise schedule is crucial: Linear schedules work but cosine schedules often perform better. The key is having enough noise at high timesteps while preserving signal at low timesteps. It's all about balance! ⚖️ #NoiseSchedule #Hyperparameters

AT4TS : Autotune for Time Series Foundation Models openreview.net/forum?id=U54Yy… #forecasting #autotuning #hyperparameters

@svpino Defaults are a crime against ML! 🤣 Manual tweaking? Stone Age! 🤖 Grid search? Baby steps. Bayesian Optimization & AutoML are where it's at. 🔥 Stop suffering! 😉 #ML #hyperparameters

Technical Implementation ⚙️ Hyperparameter Tuning Strategy: 🔧 C Parameter: [0.1, 1, 10, 100] 🎛️ Gamma Parameter: [0.001, 0.01, 0.1, 1] 🔍 GridSearchCV with 5-fold cross-validation 🎯 Scoring: 98% (to minimize false negatives) #SVM #Hyperparameters

Prior Specification for Exposure-based Bayesian Matrix Factorization openreview.net/forum?id=o5R4H… #priors #sparse #hyperparameters

Prior Specification for Exposure-based Bayesian Matrix Factorization openreview.net/forum?id=o5R4H… #priors #sparse #hyperparameters

Hyperparameters in Continual Learning: A Reality Check Sungmin Cha, Kyunghyun Cho. Action editor: Elahe Arani. openreview.net/forum?id=hiiRC… #continual #hyperparameters #hyperparameter

FoMo-0D: A Foundation Model for Zero-shot Outlier Detection openreview.net/forum?id=XCQzw… #outlier #inlier #hyperparameters

ت١١/١٧ تفاصيل تدريب الـDPO: Batch size: 512. KL_penalty (β): 0.1. معدل التعلم(Learning rate): بدأ بـ 9e-7 وتناقص إلى 5e-7 باستخدام (Cosine Annealing). تم تدريب النموذج لـ دورة(epoch) واحد على جميع البيانات في التويتة الماضية. #DPOTraining #Hyperparameters

ت١٤/٢٠ تفاصيل تدريب From Scratch (المرحلة الإنجليزية): الـBatch size ضخم: 4 مليون توكن. معدل تعلم (LR) يبدأ عالياً (3e-4) وينخفض تدريجياً بـ(cosine decay) لـ 3e-5. للتعلم السريع ثم الدقة. لا يوجد Dropout. الإعدادات مطابقة لـ Llama-2 قدر الإمكان. #Hyperparameters #DeepLearning

Optimizing Estimators of Squared Calibration Errors in Classification Sebastian Gregor Gruber, Francis R. Bach. Action editor: Masha Itkina. openreview.net/forum?id=BPDVZ… #classifiers #hyperparameters #calibration

Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Af... Qi Zhang, Yi Zhou, Shaofeng Zou. Action editor: Stephen Becker. openreview.net/forum?id=QIzRd… #adam #optimization #hyperparameters

Robustness, Stability & Generalization 🌟 Full fine-tuning (SLMs): Flexible but risks overfitting with limited data; depends on #hyperparameters like learning rate and batch size. 🔧 LoRA (LLMs): Fewer parameters lead to stable updates and retain pre-trained abilities, aiding…

Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization Sara Venturini, Marianna De Santis, Jordan Patracone et al.. Action editor: Vlad Niculae. openreview.net/forum?id=A1R1c… #hyperparameters #optimization #sparsity

Transfer Learning in $\ell_1$ Regularized Regression: Hyperparameter Selection Strategy based on ... Koki Okajima, Tomoyuki Obuchi. Action editor: Bo Han. openreview.net/forum?id=ccu0M… #lasso #hyperparameters #sparse