Search Results for author:
Found 2 papers, 1 papers with code
DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification
In this work, we present DiSMEC, which is a large-scale distributed framework for learning one-versus-rest linear classifiers coupled with explicit capacity control to control model size.
Telling cause from effect in deterministic linear dynamical systems
Assuming the effect is generated by the cause trough a linear system, we propose a new approach based on the hypothesis that nature chooses the "cause" and the "mechanism that generates the effect from the cause" independent of each other.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
