2 citations · 4 across the 5 of their papers we have counts for
5 papers
Improving Energy Conserving Descent for Machine Learning: Theory and Practice
G. Bruno De Luca, Alice Gatti, Eva Silverstein
We develop the theory of Energy Conserving Descent (ECD) and introduce ECDSep, a gradient-based optimization algorithm able to tackle convex and non-convex optimization problems. T…
Combinatorics of Vogan diagrams for almost-Kähler manifolds
Alice Gatti
Let be a non-compact classical semisimple Lie group and let be the adjoint orbit with respect to a fixed element in . These manifolds can be equipped with an almost-Kä…
Deep Learning and Spectral Embedding for Graph Partitioning
Alice Gatti, Zhixiong Hu, Tess Smidt +2
We present a graph bisection and partitioning algorithm based on graph neural networks. For each node in the graph, the network outputs probabilities for each of the partitions. Th…
Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks
Alice Gatti, Zhixiong Hu, Tess Smidt +2
We present a novel method for graph partitioning, based on reinforcement learning and graph convolutional neural networks. Our approach is to recursively partition coarser represen…
Almost Kaehler geometry of adjoint orbits of semisimple Lie groups
Alberto Della Vedova, Alice Gatti
We study the almost Kaehler geometry of adjoint orbits of non-compact real semisimple Lie groups endowed with the Kirillov-Kostant-Souriau symplectic form and a canonically defined…