304 citations · 1.7k across the 93 of their papers we have counts for
25 papers · 1 filter
Information-Guided Diffusion Sampling for Dataset Distillation
Linfeng Ye, Shayan Mohajer Hamidi, Guang Li +3
Dataset distillation aims to create a compact dataset that retains essential information while maintaining model performance. Diffusion models (DMs) have shown promise for this tas…
The Need for Speed: Pruning Transformers with One Recipe
Samir Khaki, Konstantinos N. Plataniotis
We introduce the ne-shot runing echnique for nterchangeable etworks () framework as a tool to increase t…
A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement Learning
Parvin Malekzadeh, Konstantinos N. Plataniotis, Zissis Poulos +1
Distributional Reinforcement Learning (RL) estimates return distribution mainly by learning quantile values via minimizing the quantile Huber loss function, entailing a threshold p…
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty
Parvin Malekzadeh, Ming Hou, Konstantinos N. Plataniotis
Exploration is a significant challenge in practical reinforcement learning (RL), and uncertainty-aware exploration that incorporates the quantification of epistemic and aleatory un…
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning
Parvin Malekzadeh, Ming Hou, Konstantinos N. Plataniotis
Sample efficiency is central to developing practical reinforcement learning (RL) for complex and large-scale decision-making problems. The ability to transfer and generalize knowle…
A New Probabilistic Distance Metric With Application In Gaussian Mixture Reduction
Ahmad Sajedi, Yuri A. Lawryshyn, Konstantinos N. Plataniotis
This paper presents a new distance metric to compare two continuous probability density functions. The main advantage of this metric is that, unlike other statistical measurements,…