Christoforos Nalmpantis

Orcid: 0000-0002-7398-5862

According to our database1, Christoforos Nalmpantis authored at least 23 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Teaching Large Language Models to Reason with Reinforcement Learning.
CoRR, 2024

GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements.
CoRR, 2024

2023
SAED: self-attentive energy disaggregation.
Mach. Learn., November, 2023

Variational Regression for Multi-Target Energy Disaggregation.
Sensors, February, 2023

Understanding the Effects of RLHF on LLM Generalisation and Diversity.
CoRR, 2023

Neurons in Large Language Models: Dead, N-gram, Positional.
CoRR, 2023

Augmented Language Models: a Survey.
CoRR, 2023

PEER: A Collaborative Language Model.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Machine learning approaches for time series problems
PhD thesis, 2022

Neural Fourier Energy Disaggregation.
Sensors, 2022

Noise invariant feature pooling for the internet of audio things.
Multim. Tools Appl., 2022

2021
Entropy Based Feature Pooling in Speech Command Classification.
Proceedings of the Intelligent Computing, 2021

2020
On time series representations for multi-label NILM.
Neural Comput. Appl., 2020

Attention in Recurrent Neural Networks for Energy Disaggregation.
Proceedings of the Discovery Science - 23rd International Conference, 2020

2019
Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation.
Artif. Intell. Rev., 2019

A Theoretical Analysis of Pooling Operation Using Information Theory.
Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

Hyperparameter Tuning using Quantum Genetic Algorithms.
Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

A Benchmark Framework to Evaluate Energy Disaggregation Solutions.
Proceedings of the Engineering Applications of Neural Networks, 2019

Signal2Vec: Time Series Embedding Representation.
Proceedings of the Engineering Applications of Neural Networks, 2019

Imaging Time-Series for NILM.
Proceedings of the Engineering Applications of Neural Networks, 2019

2018
Data Expedition into the Swiss Twitter Corpus.
Proceedings of the 3rd Swiss Text Analytics Conference, SwissText 2018, Winterthur, 2018

Energy profile representation in vector space.
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018

Sliding Window Approach for Online Energy Disaggregation Using Artificial Neural Networks.
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018


  Loading...