2 citations · 2 across the 1 of their papers we have counts for
6 papers
Linear Projections of Teacher Embeddings for Few-Class Distillation
Noel Loo, Fotis Iliopoulos, Wei Hu +1
Knowledge Distillation (KD) has emerged as a promising approach for transferring knowledge from a larger, more complex teacher model to a smaller student model. Traditionally, KD i…
Weighted Distillation with Unlabeled Examples
Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal +3
Distillation with unlabeled examples is a popular and powerful method for training deep neural networks in settings where the amount of labeled data is limited: A large ''teacher''…
Group testing and local search: is there a computational-statistical gap?
Fotis Iliopoulos, Ilias Zadik
In this work we study the fundamental limits of approximate recovery in the context of group testing. One of the most well-known, theoretically optimal, and easy to implement testi…
A Local Lemma for Focused Stochastic Algorithms
Dimitris Achlioptas, Fotis Iliopoulos, Vladimir Kolmogorov
We develop a framework for the rigorous analysis of focused stochastic local search algorithms. These are algorithms that search a state space by repeatedly selecting some constrai…
Simple Local Computation Algorithms for the General Lovasz Local Lemma
Dimitris Achlioptas, Themis Gouleakis, Fotis Iliopoulos
We consider the task of designing Local Computation Algorithms (LCA) for applications of the Lovász Local Lemma (LLL). LCA is a class of sublinear algorithms proposed by Rubinfeld…
Beyond the Lovasz Local Lemma: Point to Set Correlations and Their Algorithmic Applications
Dimitris Achlioptas, Fotis Iliopoulos, Alistair Sinclair
Following the groundbreaking algorithm of Moser and Tardos for the Lovasz Local Lemma (LLL), there has been a plethora of results analyzing local search algorithms for various cons…