Search Results for author:
Found 4 papers, 2 papers with code
The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning
To measure these risks of malicious use, government institutions and major AI labs are developing evaluations for hazardous capabilities in LLMs.
Improving Energy Conserving Descent for Machine Learning: Theory and Practice
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.
Deep Learning and Spectral Embedding for Graph Partitioning
The embedding phase is trained first by minimizing a loss function inspired by spectral graph theory.
Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks
The partitioning quality is compared with partitions obtained using METIS and SCOTCH, and the nested dissection ordering is evaluated in the sparse solver SuperLU.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
