5 citations · 6 across the 6 of their papers we have counts for
6 papers
Does Synthetic Data Help? Empirical Evidence from Deep Learning Time Series Forecasters
Hugo Cazaux, Eyjólfur Ingi Ásgeirsson, Hlynur Stefánsson
Synthetic data has transformed language model training, yet its role in time series forecasting remains poorly understood. We present a large-scale empirical study: nine experiment…
Fine-tuning Timeseries Predictors Using Reinforcement Learning
Hugo Cazaux, Ralph Rudd, Hlynur Stefánsson +2
This chapter presents three major reinforcement learning algorithms used for fine-tuning financial forecasters. We propose a clear implementation plan for backpropagating the loss…
Wireless Scheduling Algorithms in Complex Environments
Helga Gudmundsdottir, Eyjólfur I Ásgeirsson, Marijke H. L. Bodlaender +3
Efficient spectrum use in wireless sensor networks through spatial reuse requires effective models of packet reception at the physical layer in the presence of interference. Despit…
Wireless Network Stability in the SINR Model
Eyjolfur I. Asgeirsson, Magnus M. Halldorsson, Pradipta Mitra
We study the stability of wireless networks under stochastic arrival processes of packets, and design efficient, distributed algorithms that achieve stability in the SINR (Signal t…
A Fully Distributed Algorithm for Throughput Performance in Wireless Networks
Eyjolfur I. Asgeirsson, Magnus M. Halldorsson, Pradipta Mitra
We study link scheduling in wireless networks under stochastic arrival processes of packets, and give an algorithm that achieves stability in the physical (SINR) interference model…
On a game theoretic approach to capacity maximization in wireless networks
Eyjólfur Ingi Ásgeirsson, Pradipta Mitra
We consider the capacity problem (or, the single slot scheduling problem) in wireless networks. Our goal is to maximize the number of successful connections in arbitrary wireless n…