439 citations · 1.4k across the 66 of their papers we have counts for
18 papers · 1 filter
Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
Runyu Lu, Peng Zhang, Ruochuan Shi +5
Equilibrium learning in adversarial games is an important topic widely examined in the fields of game theory and reinforcement learning (RL). Pursuit-evasion game (PEG), as an impo…
Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting
Valentina Moretti, Ivan Marisca, Cesare Alippi +1
Deep learning models have grown popular in time series applications. However, the large quantity of newly proposed architectures and the often contradictory empirical results make…
BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
Luca Colombo, Fabrizio Pittorino, Daniele Zambon +3
Binary Neural Networks (BNNs), which constrain both weights and activations to binary values, offer substantial reductions in computational complexity, memory footprint, and energy…
Compensating Distribution Drifts in Class-incremental Learning of Pre-trained Vision Transformers
Xuan Rao, Simian Xu, Zheng Li +4
Recent advances have shown that sequential fine-tuning (SeqFT) of pre-trained vision transformers (ViTs), followed by classifier refinement using approximate distributions of class…
The Unreasonable Effectiveness of Randomized Representations in Online Continual Graph Learning
Giovanni Donghi, Daniele Zambon, Luca Pasa +2
Catastrophic forgetting is one of the main obstacles for Online Continual Graph Learning (OCGL), where nodes arrive one by one, distribution drifts may occur at any time and offlin…
Beyond Softmax: A Natural Parameterization for Categorical Random Variables
Alessandro Manenti, Cesare Alippi
Latent categorical variables are frequently found in deep learning architectures. They can model actions in discrete reinforcement-learning environments, represent categories in la…