75 citations · 130 across the 10 of their papers we have counts for
10 papers
SmartChoices: Augmenting Software with Learned Implementations
Daniel Golovin, Gabor Bartok, Eric Chen +7
In many software systems, heuristics are used to make decisions - such as cache eviction, task scheduling, and information presentation - that have a significant impact on overall…
Ranking architectures using meta-learning
Alina Dubatovka, Efi Kokiopoulou, Luciano Sbaiz +3
Neural architecture search has recently attracted lots of research efforts as it promises to automate the manual design of neural networks. However, it requires a large amount of c…
Flexible Multi-task Networks by Learning Parameter Allocation
Krzysztof Maziarz, Efi Kokiopoulou, Andrea Gesmundo +3
This paper proposes a novel learning method for multi-task applications. Multi-task neural networks can learn to transfer knowledge across different tasks by using parameter sharin…
Fast Task-Aware Architecture Inference
Efi Kokiopoulou, Anja Hauth, Luciano Sbaiz +3
Neural architecture search has been shown to hold great promise towards the automation of deep learning. However in spite of its potential, neural architecture search remains quite…
Importance weighting without importance weights: An efficient algorithm for combinatorial semi-bandits
Gergely Neu, Gábor Bartók
We propose a sample-efficient alternative for importance weighting for situations where one only has sample access to the probability distribution that generates the observations.…
Near-Optimally Teaching the Crowd to Classify
Adish Singla, Ilija Bogunovic, Gábor Bartók +2
How should we present training examples to learners to teach them classification rules? This is a natural problem when training workers for crowdsourcing labeling tasks, and is als…