3 citations · 5 across the 7 of their papers we have counts for
13 papers
Complexity of Classical Acceleration for -Regularized PageRank
Kimon Fountoulakis, David Martínez-Rubio
We study the degree-weighted work required to compute -regularized PageRank using the standard accelerated proximal-gradient method (FISTA). For non-accelerated methods (IS…
On the Statistical Query Complexity of Learning Semiautomata: a Random Walk Approach
George Giapitzakis, Kimon Fountoulakis, Eshaan Nichani +1
Semiautomata form a rich class of sequence-processing algorithms with applications in natural language processing, robotics, computational biology, and data mining. We establish th…
Learning to Add, Multiply, and Execute Algorithmic Instructions Exactly with Neural Networks
Artur Back de Luca, George Giapitzakis, Kimon Fountoulakis
Neural networks are known for their ability to approximate smooth functions, yet they fail to generalize perfectly to unseen inputs when trained on discrete operations. Such operat…
LVLM-COUNT: Enhancing the Counting Ability of Large Vision-Language Models
Muhammad Fetrat Qharabagh, Mohammadreza Ghofrani, Kimon Fountoulakis
Counting is a fundamental operation for various real-world visual tasks, requiring both object recognition and robust counting capabilities. Despite their advanced visual perceptio…
Positional Attention: Expressivity and Learnability of Algorithmic Computation
Artur Back de Luca, George Giapitzakis, Shenghao Yang +2
There is a growing interest in the ability of neural networks to execute algorithmic tasks (e.g., arithmetic, summary statistics, and sorting). The goal of this work is to better u…
On Classification Thresholds for Graph Attention with Edge Features
Kimon Fountoulakis, Dake He, Silvio Lattanzi +3
The recent years we have seen the rise of graph neural networks for prediction tasks on graphs. One of the dominant architectures is graph attention due to its ability to make pred…