Search Results for author:
Found 9 papers, 4 papers with code
Textual Data Augmentation for Efficient Active Learning on Tiny Datasets
In this paper we propose a novel data augmentation approach where guided outputs of a language generation model, e. g. GPT-2, when labeled, can improve the performance of text classifiers through an active learning process.
Enhancing Task-Specific Distillation in Small Data Regimes through Language Generation
To overcome this challenge, we present a novel approach where knowledge can be distilled from a teacher model to a student model through the generation of synthetic data.
Robustness of Algorithms for Causal Structure Learning to Hyperparameter Choice
We find that, while the choice of algorithm remains crucial to obtaining state-of-the-art performance, hyperparameter selection in ensemble settings strongly influences the choice of algorithm, in that a poor choice of hyperparameters can lead to analysts using algorithms which do not give state-of-the-art performance for their data.
Hyperparameter Tuning and Model Evaluation in Causal Effect Estimation
We also find hyperparameter tuning and model evaluation are much more important than causal estimators and ML methods.
A Comparison of Self-Play Algorithms Under a Generalized Framework
They allow to verify and replicate existing findings, and to link is connected results.
Deep Learning in Target Space
Experimental results show the speed of using target space, and examples of improved generalisation, for fully-connected networks and convolutional networks, and the ability to recall and process long time sequences and perform natural-language processing with recurrent networks.
Open Loop In Natura Economic Planning
The debate between the optimal way of allocating societal surplus (i. e. products and services) has been raging, in one form or another, practically forever; following the collapse of the Soviet Union in 1991, the market became the only legitimate form of organisation -- there was no other alternative.
Viewpoint: Artificial Intelligence and Labour
The welfare of modern societies has been intrinsically linked to wage labour.
A Survey of Monte Carlo Tree Search Methods
Monte Carlo Tree Search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling.
