Search Results for author:
Found 6 papers, 2 papers with code
FAIR: Filtering of Automatically Induced Rules
The availability of large annotated data can be a critical bottleneck in training machine learning algorithms successfully, especially when applied to diverse domains.
I-SplitEE: Image classification in Split Computing DNNs with Early Exits
The recent advances in Deep Neural Networks (DNNs) stem from their exceptional performance across various domains.
HoloBeam: Learning Optimal Beamforming in Far-Field Holographic Metasurface Transceivers
To overcome this, {\it\HB} works with the discrete values of phase-shifting parameters and exploits their unimodal relations with channel gains to learn the optimal values faster.
ICQ: A Quantization Scheme for Best-Arm Identification Over Bit-Constrained Channels
We study the problem of best-arm identification in a distributed variant of the multi-armed bandit setting, with a central learner and multiple agents.
Unsupervised Learning of Explainable Parse Trees for Improved Generalisation
In this work, we propose an attention mechanism over Tree-LSTMs to learn more meaningful and explainable parse tree structures.
Cheap Bandits
We consider stochastic sequential learning problems where the learner can observe the \textit{average reward of several actions}.
