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HIDRA: Head Initialization across Dynamic targets for Robust Architectures
Rafael Rego Drumond, Lukas Brinkmeyer, Josif Grabocka +1
The performance of gradient-based optimization strategies depends heavily on the initial weights of the parametric model. Recent works show that there exist weight initializations…
Handwritten Amharic Character Recognition Using a Convolutional Neural Network
Mesay Samuel Gondere, Lars Schmidt-Thieme, Abiot Sinamo Boltena +1
Amharic is the official language of the Federal Democratic Republic of Ethiopia. There are lots of historic Amharic and Ethiopic handwritten documents addressing various relevant i…
Chameleon: Learning Model Initializations Across Tasks With Different Schemas
Lukas Brinkmeyer, Rafael Rego Drumond, Randolf Scholz +2
Parametric models, and particularly neural networks, require weight initialization as a starting point for gradient-based optimization. Recent work shows that a specific initial pa…
Hyp-RL : Hyperparameter Optimization by Reinforcement Learning
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
Hyperparameter tuning is an omnipresent problem in machine learning as it is an integral aspect of obtaining the state-of-the-art performance for any model. Most often, hyperparame…
In Hindsight: A Smooth Reward for Steady Exploration
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
In classical Q-learning, the objective is to maximize the sum of discounted rewards through iteratively using the Bellman equation as an update, in an attempt to estimate the actio…
Learning Surrogate Losses
Josif Grabocka, Randolf Scholz, Lars Schmidt-Thieme
The minimization of loss functions is the heart and soul of Machine Learning. In this paper, we propose an off-the-shelf optimization approach that can minimize virtually any non-d…